In the rapidly evolving financial landscape, effective risk management has become paramount for banks and financial institutions. BCBS 239, officially titled “Principles for effective risk data aggregation and risk reporting,” is a set of guidelines issued by the Basel Committee on Banking Supervision (BCBS) to enhance banks’ risk management capabilities. This comprehensive guide explores what BCBS 239 is, why it matters, and how organisations can achieve compliance through effective data management and readiness.

Understanding BCBS 239

What Is BCBS 239?

BCBS 239 is a regulatory standard published in January 2013 by the Basel Committee on Banking Supervision. It sets out 14 principles designed to strengthen banks’ risk data aggregation capabilities and internal risk reporting practices. The standard aims to improve risk management and decision-making processes, thereby enhancing the stability of the financial system.

Purpose of BCBS 239

• Enhance Risk Management: By ensuring accurate and timely risk data, banks can better identify, measure, and manage risks.
• Improve Decision-Making: High-quality risk data supports informed strategic decisions at the board and senior management levels.
• Strengthen Financial Stability: Reduces the likelihood of systemic failures by promoting robust risk practices across the banking sector.

Scope of BCBS 239

While BCBS 239 primarily targets Global Systemically Important Banks (G-SIBs), national regulators may extend its application to Domestic Systemically Important Banks (D-SIBs) and other financial institutions as they see fit.

Key Principles of BCBS 239

BCBS 239 outlines 14 principles grouped into four categories:

I. Overarching Governance and Infrastructure

1. Governance: Banks should have strong governance arrangements, including board and senior management oversight, to ensure effective risk data aggregation and reporting.
2. Data Architecture and IT Infrastructure: Banks should design and maintain data architecture and IT infrastructure that fully support their risk data aggregation capabilities and risk reporting practices.

II. Risk Data Aggregation Capabilities

3. Accuracy and Integrity: Risk data should be accurate and reliable, requiring robust data quality controls.
4. Completeness: Risk data should capture all material risk exposures and cover all business lines and entities.
5. Timeliness: Risk data should be available in a timely manner to meet reporting requirements, especially during times of stress.
6. Adaptability: Risk data aggregation capabilities should be flexible to accommodate ad-hoc requests and changing regulatory requirements.

III. Risk Reporting Practices

7. Accuracy: Risk reports should precisely convey risk exposures and positions.
8. Comprehensiveness: Reports should cover all material risks, enabling a holistic view.
9. Clarity and Usefulness: Risk reports should be clear, concise, and tailored to the needs of the recipients.
10. Frequency: Reporting frequency should align with the needs of recipients, increasing during periods of stress.
11. Distribution: Reports should be distributed to appropriate parties securely and promptly.

IV. Supervisory Review, Tools, and Cooperation

12. Review: Supervisors should regularly review banks’ compliance with the principles.
13. Remedial Actions and Supervisory Measures: Supervisors should take appropriate action if banks fail to comply.
14. Cooperation: Supervisors should cooperate with other authorities to support the implementation of the principles.

BCBS 239 Requirements for Banks

Governance and Infrastructure

• Strong Governance Framework: Establish clear responsibilities and accountability for risk data management.
• Robust IT Infrastructure: Invest in technology that supports data aggregation and reporting needs.

Risk Data Aggregation Capabilities

• Data Quality Controls: Implement processes to ensure data accuracy, completeness, and reliability.
• Comprehensive Data Coverage: Ensure all relevant risk data across the organisation is captured and aggregated.
• Timely Data Availability: Develop systems that can provide up-to-date risk data, especially during periods of market stress.
• Flexibility: Be able to adapt to new data requirements and regulatory changes quickly.

Risk Reporting Practices

• Accurate and Insightful Reports: Produce reports that accurately reflect the bank’s risk profile and provide actionable insights.
• Tailored Reporting: Adjust reports to meet the specific needs of different stakeholders, such as the board, senior management, and regulators.
• Secure Distribution: Ensure that risk reports are delivered securely to authorised individuals.

Challenges in Achieving BCBS 239 Compliance

Data Management and Quality Issues

• Data Silos: Risk data often resides in disparate systems across various departments, leading to fragmentation.
• Inconsistent Data Definitions: Variations in how data is defined and recorded hinder aggregation and consistency.
• Inaccurate or Incomplete Data: Errors and omissions compromise the reliability of risk assessments.

Operational Complexities

• Legacy Systems: Outdated IT infrastructure may not support the required capabilities for data aggregation and reporting.
• Integration Difficulties: Merging data from multiple sources into a cohesive whole is technically challenging.
• Resource Constraints: Limited availability of skilled personnel and financial resources to implement necessary changes.

Regulatory Pressure

• Strict Expectations: Regulators expect full compliance, with little tolerance for delays or deficiencies.
• Continuous Compliance: BCBS 239 requires ongoing adherence, necessitating continuous effort and vigilance.

The Role of Data Readiness in BCBS 239 Compliance

Achieving Data Readiness is crucial for meeting the stringent requirements of BCBS 239. Data Readiness involves ensuring that data is accurate, complete, consistent, timely, and accessible.

Importance of Accurate, Complete, and Timely Data

• Effective Risk Management: Reliable data enables accurate risk assessments and proactive risk mitigation.
• Informed Decision-Making: High-quality data supports strategic decisions by the board and senior management.
• Regulatory Compliance: Demonstrates to regulators that the bank has robust risk data practices.

Facilitating Compliance Efforts

• Data Integration: Consolidating data from various sources provides a comprehensive view of risk exposures.
• Automation: Streamlining data aggregation and reporting processes reduces manual errors and increases efficiency.
• Adaptability: Being data-ready allows banks to respond swiftly to new regulatory requirements or ad-hoc information requests.

How Datactics Helps with BCBS 239 Compliance

Datactics offers advanced data quality and data management solutions that assist banks in achieving Data Readiness for BCBS 239 compliance.

Automated Data Cleansing

• Error Detection and Correction: Identifies inaccuracies in risk data and rectifies them automatically.
• Standardisation: Ensures data conforms to consistent formats and definitions across the organisation.

Data Validation

• Business Rules Implementation: Applies risk-specific validation rules to datasets, ensuring compliance with internal and regulatory standards.
• Consistency Checks: Verifies that data remains consistent across different systems and reports.

Data Integration and Consolidation

• Data Aggregation: Combines data from multiple sources to provide a comprehensive view of all risk exposures.
• Advanced Matching Algorithms: Links related data points across systems, enhancing data integrity and reliability.

Regulatory Compliance Support

• Data Preparation: Structures and formats data according to internal reporting needs and regulatory requirements.
• Automated Reporting: Supports the generation of timely and accurate risk reports, reducing manual effort.

Governance and Audit Trails

• Documentation: Maintains detailed records of data management activities, aiding in audits and regulatory reviews.
• Accountability: Assigns clear ownership and responsibility for data quality and reporting tasks.

Self-Service Data Quality Platform

• Empowering Business Users: Allows risk managers and data stewards to manage data quality independently, without heavy reliance on IT.
• User-Friendly Tools: Provides intuitive interfaces for monitoring data readiness and addressing issues promptly.

Benefits of Using Datactics’ Solutions

• Enhanced Data Accuracy and Integrity: Improves the reliability of risk data, supporting effective risk management.
• Operational Efficiency: Automates labour-intensive tasks, reducing costs and freeing up resources for strategic initiatives.
• Regulatory Confidence: Demonstrates robust compliance practices to regulators, building trust and potentially reducing supervisory scrutiny.
• Risk Reduction: Enables proactive risk identification and mitigation, safeguarding the bank’s financial stability.

Achieving Data Readiness for BCBS 239 Compliance: A Step-by-Step Approach

1. Assess Current Data Landscape

• Data Audit: Evaluate existing risk data for accuracy, completeness, and consistency.
• Identify Gaps: Determine areas where data quality or infrastructure falls short of BCBS 239 requirements.

2. Implement Data Quality Measures

• Data Cleansing: Utilise automated tools to correct errors and standardise data formats.
• Validation Processes: Establish rigorous validation against business rules and regulatory standards.

3. Enhance Data Integration

• Data Consolidation: Develop a strategy to merge data from disparate systems into a unified platform.
• Advanced Matching: Use sophisticated algorithms to link related data across the organisation.

4. Upgrade IT Infrastructure

• Invest in Technology: Ensure IT systems can support robust data aggregation and reporting capabilities.
• Scalability and Flexibility: Implement solutions that can adapt to changing needs and regulatory requirements.

5. Strengthen Governance Framework

• Policies and Procedures: Define clear guidelines for data management, risk reporting, and compliance.
• Roles and Responsibilities: Assign accountability for data quality, risk management, and reporting tasks.

6. Automate Reporting Processes

• Data Preparation: Structure data to meet the specific needs of different stakeholders.
• Automated Reporting: Implement systems that generate timely, accurate reports with minimal manual intervention.

7. Continuous Monitoring and Improvement

• Regular Reviews: Monitor data quality metrics and compliance status.
• Feedback Mechanisms: Use insights to make ongoing enhancements to data practices and systems.

To Conclude

BCBS 239 represents a significant step towards enhancing risk management and financial stability within the banking sector. Compliance with its principles is not merely a regulatory obligation but a strategic imperative that can provide a competitive advantage through improved decision-making and risk mitigation.

Achieving Data Readiness is essential for meeting the stringent requirements of BCBS 239. Banks must ensure their data is accurate, complete, consistent, and timely to support effective risk data aggregation and reporting.

Datactics offers the tools and expertise needed to navigate the complexities of BCBS 239 compliance. Through advanced data quality enhancement, data integration, and regulatory compliance support, Datactics enables banks to fulfil their obligations confidently and efficiently.

By leveraging Datactics’ solutions, financial institutions can not only mitigate the risks associated with non-compliance but also enhance operational efficiency, strengthen risk management practices, and maintain their reputation in the global financial market.

Get Started with Datactics

Ensure your organisation is fully prepared for BCBS 239 compliance with Datactics’ comprehensive data management solutions.

• Learn More: Explore Datactics’ Solutions for BCBS 239 Compliance
• Contact Us: Email at info@datactics.com

Achieve Data Readiness with Datactics and ensure seamless compliance with BCBS 239. Empower your organisation with accurate, integrated, and reliable risk data to meet regulatory demands and enhance your decision-making capabilities.

The post What is BCBS 239 and Why Is It Important? appeared first on Datactics.

In an increasingly globalised economy, transparency in financial transactions has become paramount. The Foreign Account Tax Compliance Act (FATCA) is a United States federal law designed to combat tax evasion by U.S. taxpayers holding assets in foreign accounts. This comprehensive guide explores what FATCA is, its implications for financial institutions worldwide, and how organisations can achieve compliance through effective data management and readiness.

Understanding FATCA

What Is FATCA?

Enacted in 2010 as part of the Hiring Incentives to Restore Employment (HIRE) Act, the Foreign Account Tax Compliance Act (FATCA) aims to prevent tax evasion by U.S. citizens and residents using offshore accounts. FATCA requires foreign financial institutions (FFIs) to identify and report information about financial accounts held by U.S. taxpayers or foreign entities with substantial U.S. ownership to the U.S. Internal Revenue Service (IRS).

Purpose of FATCA

• Combat Tax Evasion: FATCA seeks to detect and deter tax evasion by increasing transparency in international finance.
• Enhance Compliance: Encourages FFIs to comply with U.S. tax laws through mandatory reporting obligations.
• Promote Global Cooperation: Facilitates the exchange of tax information between countries.

Scope of FATCA

FATCA applies to a wide range of financial institutions outside the United States, including:

• Banks and Credit Unions
• Investment Entities: Mutual funds, hedge funds, private equity funds.
• Custodial Institutions
• Certain Insurance Companies

FATCA Requirements for Financial Institutions

Foreign Financial Institutions (FFIs) are required to:

Register with the IRS

• Obtain a Global Intermediary Identification Number (GIIN): Registration is necessary to be recognised as a participating FFI.

Conduct Due Diligence

• Identify U.S. Account Holders: Implement procedures to detect accounts held by U.S. persons.
• Classify Entities: Determine the FATCA status of entity account holders.

Report to the IRS

• Annual Reporting: Provide information on U.S. accounts, including:
  • Account Holder Details: Name, address, U.S. Tax Identification Number (TIN).
  • Account Information: Account number, balance or value, income, and gross proceeds.

Withhold Tax

• 30% Withholding: On certain U.S.-source payments to non-participating FFIs or account holders who fail to provide required information.

Impact on U.S. and Non-U.S. Entities

• U.S. Taxpayers: Must report foreign financial assets exceeding specified thresholds.
• Non-U.S. Entities: Required to disclose substantial U.S. ownership if classified as Passive Non-Financial Foreign Entities (NFFEs).

Challenges in Achieving FATCA Compliance

Incomplete or Inaccurate Data

• Missing TINs: Absence of U.S. Tax Identification Numbers hampers reporting.
• Erroneous Information: Inaccurate customer details lead to misreporting and potential penalties.

Data Silos

• Disparate Systems: Customer data spread across multiple platforms complicates aggregation and analysis.
• Inconsistent Formats: Variations in data standards hinder integration.

Identifying U.S. Persons

• Complex Identification: Challenges in recognising U.S. taxpayers among global customers.
• Ongoing Monitoring: Continuous scrutiny required to detect changes in account status.

Entity Classification

• Determining FATCA Status: Assessing whether entities are Passive NFFEs with substantial U.S. owners.

Technological and Resource Constraints: Legacy Systems

• Limited Capabilities: Older technology may not support FATCA compliance requirements.
• Integration Difficulties: Challenges in linking systems for comprehensive data analysis.

Resource Limitations

• Expertise Shortage: Lack of specialised staff in compliance and data management.
• Time Constraints: Meeting strict reporting deadlines demands efficient processes.

The Role of Data Readiness in FATCA Compliance

Achieving Data Readiness is crucial for FATCA compliance, ensuring that data is accurate, complete, and readily accessible for reporting purposes.

Importance of Accurate and Complete Data

• Reliable Reporting: High-quality data enables precise reporting to the IRS, avoiding penalties.
• Effective Due Diligence: Accurate data supports thorough identification and classification of account holders.

Facilitating Compliance Efforts

• Automation: Streamlines data collection, validation, and reporting processes.
• Risk Mitigation: Reduces the likelihood of non-compliance due to data errors.

How Datactics Helps with FATCA Compliance

Datactics provides advanced data quality and data management solutions that assist financial institutions in achieving Data Readiness for FATCA compliance.

Automated Data Cleansing

• Error Identification: Detects inaccuracies in customer data, such as incorrect TINs or addresses.
• Correction Mechanisms: Applies business rules to rectify common errors automatically.

Data Validation

• Standardisation: Ensures data conforms to FATCA-required formats and standards.
• Consistency Checks: Aligns data across different systems for uniformity.

Comprehensive Customer View

• Data Aggregation: Combines data from multiple sources to provide a unified profile of each account holder.
• Advanced Matching Algorithms: Uses fuzzy matching to identify U.S. persons and substantial U.S. owners in entities.

Due Diligence Automation

• Customer Screening: Automates the identification of U.S. account holders using predefined criteria.
• Entity Classification: Assists in determining the FATCA status of entities, simplifying complex assessments.

Reporting Facilitation

• Data Preparation: Structures data according to IRS reporting requirements, ensuring compliance.
• Audit Trails: Maintains detailed records of compliance activities for regulatory review and accountability.

Self-Service Data Quality Platform

• Empowering Compliance Teams: Allows non-technical staff to manage data quality and compliance processes.
• User-Friendly Tools: Provides intuitive interfaces for monitoring and addressing data issues promptly.

Benefits of Using Datactics’ Solutions

• Improved Data Accuracy: Enhances the reliability of reporting data, reducing the risk of penalties.
• Operational Efficiency: Automates labour-intensive tasks, freeing resources for strategic initiatives.
• Regulatory Confidence: Demonstrates robust compliance practices to regulators, building trust.
• Risk Reduction: Minimises potential financial penalties and reputational damage.

Achieving Data Readiness for FATCA Compliance: A Step-by-Step Approach

1. Assess Current Data Landscape

• Data Audit: Evaluate existing customer data for completeness and accuracy.
• Identify Gaps: Recognise areas where data quality is lacking.

2. Implement Data Quality Measures

• Data Cleansing: Utilise automated tools to correct errors and fill missing information.
• Standardisation: Align data formats and structures according to FATCA requirements.

3. Enhance Data Integration

• Consolidation Strategy: Develop a plan to merge data from various systems.
• Unified Customer Profiles: Create comprehensive views of account holders for accurate assessment.

4. Automate Due Diligence Processes

• Customer Identification: Use advanced algorithms to identify U.S. persons and entities with substantial U.S. ownership.
• Entity Classification: Simplify the determination of FATCA status for complex entities.

5. Prepare for Reporting

• Data Structuring: Organise data in line with IRS reporting specifications.
• Testing and Validation: Ensure data accuracy through rigorous testing before submission.

6. Establish Data Governance Framework

• Policies and Procedures: Define clear guidelines for data management and compliance.
• Roles and Responsibilities: Assign accountability for data quality and compliance tasks.

7. Continuous Monitoring and Improvement

• Regular Reviews: Monitor data quality metrics and compliance status.
• Feedback Mechanisms: Implement processes for ongoing enhancement based on insights gained.

Conclusion

The Foreign Account Tax Compliance Act (FATCA) represents a significant regulatory challenge for financial institutions worldwide. Compliance requires meticulous data management, thorough due diligence, and accurate reporting. Achieving Data Readiness is essential to meet these demands, ensuring that data is accurate, complete, and accessible.

Datactics offers the tools and expertise needed to navigate the complexities of FATCA compliance. Through advanced data quality enhancement, data integration, and compliance support, Datactics enables financial institutions to fulfil their obligations confidently and efficiently.

By leveraging Datactics’ solutions, organisations can not only mitigate the risks associated with non-compliance but also enhance operational efficiency and strengthen their reputation in the global financial market.

Get Started with Datactics

Ensure your organisation is fully prepared for FATCA compliance with Datactics’ comprehensive data management solutions.

• Learn More: Explore Datactics’ Solutions for FATCA Compliance
• Contact Us: Email at info@datactics.com

Achieve Data Readiness with Datactics and ensure seamless compliance with the Foreign Account Tax Compliance Act. Empower your organisation with accurate, consolidated, and compliant data to meet regulatory demands and maintain trust in the global financial community.

The post What is the Foreign Account Tax Compliance Act (FATCA) and Why Is It Important? appeared first on Datactics.

In today’s data-driven business landscape, organisations rely heavily on data to make informed decisions, comply with regulations, and maintain a competitive edge. Data Readiness refers to the state of being fully prepared to use data effectively and efficiently for these purposes. It involves ensuring that data is accurate, consistent, complete, and accessible, making it fit for analysis, reporting, and operational use.

Understanding Data Readiness

Data Readiness is not just about having data; it’s about having high-quality data that is ready to support business objectives. It encompasses several key aspects:

• Data Quality: Ensuring data is accurate and reliable.
• Data Integration: Combining data from various sources into a cohesive whole.
• Data Governance: Implementing policies and procedures to manage data effectively.
• Data Accessibility: Making data available to those who need it when they need it.
• Regulatory Compliance: Ensuring data practices meet legal and industry standards.

By achieving Data Readiness, organisations can unlock the full potential of their data assets, driving efficiency and innovation.

Why Data Readiness Matters

1. Informed Decision-Making

High-quality, ready-to-use data enables organisations to perform accurate analyses, leading to better strategic decisions. Whether it’s forecasting market trends or evaluating internal performance, Data Readiness provides a solid foundation for reliable insights.

2. Operational Efficiency

Data Readiness streamlines processes by reducing errors and redundancies. When data is clean and accessible, teams can work more efficiently, saving time and resources.

3. Regulatory Compliance

Industries such as finance and healthcare are subject to stringent regulations regarding data handling. Achieving Data Readiness ensures that organisations meet these obligations, avoiding penalties and protecting their reputation.

4. Competitive Advantage

Organisations that prioritise Data Readiness can respond swiftly to market changes, innovate faster, and offer better customer experiences. This agility provides a significant edge over competitors.

5. Enhanced Customer Satisfaction

Accurate and timely data allows for personalised customer interactions. By understanding customer needs and behaviours through reliable data, organisations can tailor their services, increasing satisfaction and loyalty.

Key Components of Data Readiness

Data Quality

At the heart of Data Readiness is Data Quality. This means data is:

• Accurate: Correct and free from errors.
• Complete: Contains all necessary information.
• Consistent: Uniform across different systems.
• Valid: Complies with required formats and standards.

High Data Quality ensures that decisions based on data are sound and trustworthy.

Data Integration

Data often resides in silos across various departments. Data Integration involves bringing this data together to provide a unified view. This process eliminates inconsistencies and enables comprehensive analysis.

Data Governance

Data Governance refers to the policies, procedures, and standards that govern how data is managed and used. It ensures that data is handled responsibly and that there is accountability for its quality and security.

Data Accessibility

For data to be useful, it must be accessible to those who need it. This means implementing systems that allow authorised users to retrieve data easily while maintaining appropriate security controls.

Regulatory Compliance

Compliance with regulations such as FSCS, FATCA, EMIR, and BCBS 239 is essential, especially in highly regulated industries. Data Readiness includes ensuring that data practices meet these legal requirements.

Challenges in Achieving Data Readiness

Despite its importance, achieving Data Readiness can be challenging due to:

Data Silos

Disparate data systems can lead to fragmented information, making it difficult to obtain a complete picture.

Poor Data Quality

Errors, duplicates, and outdated information undermine trust in data and can lead to incorrect conclusions.

Complex Regulations

Navigating various regulatory requirements requires meticulous data management and documentation.

Limited Resources

Organisations may lack the necessary tools or expertise to manage data effectively.

Technological Limitations

Legacy systems may not support modern data integration and governance needs.

How Datactics Supports Data Readiness

Datactics offers advanced solutions to help organisations overcome these challenges and achieve Data Readiness.

Augmented Data Quality (ADQ) Platform

Datactics’ ADQ platform leverages artificial intelligence (AI) and machine learning (ML) to automate and enhance data quality processes.

Key Features

• Automated Data Cleansing: Identifies and corrects errors, ensuring data is accurate and reliable.
• Advanced Matching Algorithms: Uses fuzzy matching to eliminate duplicates and link related records.
• Self-Service Interface: Empowers business users to manage data quality without heavy reliance on IT.
• Real-Time Monitoring: Provides continuous oversight of data quality, with alerts for any issues.
• Regulatory Compliance Support: Ensures data meets standards required by regulations like FSCS, FATCA, EMIR, and BCBS 239.

Benefits of Using Datactics’ Solutions

• Improved Data Quality: Achieve higher levels of accuracy and consistency.
• Operational Efficiency: Reduce manual effort through automation.
• Enhanced Compliance: Simplify adherence to complex regulations.
• Scalability: Handle large volumes of data with ease.
• Better Decision-Making: Base strategies on reliable, ready-to-use data.

Achieving Data Readiness: A Step-by-Step Approach

1. Assess Current Data State

Begin by evaluating the current condition of your data. Identify areas where data quality is lacking or where silos exist.

2. Implement Data Governance Framework

Establish policies and procedures for data management. Define roles and responsibilities to ensure accountability.

3. Enhance Data Quality

Use tools like Datactics’ ADQ platform to automate data cleansing and validation processes.

4. Integrate Data Sources

Consolidate data from various systems to create a unified view. This may involve implementing data warehousing or data lakes.

5. Improve Data Accessibility

Ensure that authorised users can access the data they need. Implement user-friendly interfaces and appropriate access controls.

6. Monitor and Maintain

Continuously monitor data quality and governance compliance. Regularly update processes to adapt to changing needs and regulations.

The Role of Data Readiness in Regulatory Compliance

Financial Services Compensation Scheme (FSCS)

Compliance with FSCS requires accurate and timely reporting. Data Readiness ensures that the necessary data is available and reliable.

Foreign Account Tax Compliance Act (FATCA)

FATCA mandates reporting of foreign financial accounts. Achieving Data Readiness helps organisations manage this data effectively.

European Market Infrastructure Regulation (EMIR)

EMIR requires detailed transaction reporting. Data Readiness facilitates the accurate aggregation and submission of this information.

Basel Committee on Banking Supervision (BCBS 239)

BCBS 239 sets principles for risk data aggregation and reporting. Data Readiness supports adherence to these principles by ensuring data is consistent and reliable.

Data Readiness and Artificial Intelligence

As organisations adopt AI and machine learning technologies, Data Readiness becomes even more critical.

Data Quality for AI

AI algorithms depend on high-quality data. Poor data can lead to inaccurate models and flawed insights.

Accelerating AI Initiatives

Data Readiness accelerates AI projects by providing clean, well-structured data, reducing the time spent on data preparation.

Datactics’ Contribution

Datactics’ solutions prepare data for AI applications, ensuring that organisations can leverage these technologies effectively.

Conclusion

Data Readiness is essential for organisations seeking to harness the full power of their data. It enables better decision-making, ensures compliance, and drives operational efficiency. Achieving Data Readiness involves addressing data quality, integration, governance, accessibility, and compliance.

Datactics provides the tools and expertise needed to attain Data Readiness. By automating data quality processes and supporting data governance, Datactics helps organisations overcome challenges and unlock the full potential of their data assets.

Get Started with Datactics

Ready to achieve Data Readiness and transform your data management practices? Discover how Datactics can empower your organisation.

• Learn More: Explore Data Readiness Solutions
• Contact Us: Email at info@datactics.com

Achieve Data Readiness with Datactics and unlock the full potential of your data assets. Empower your organisation with accurate, compliant, and accessible data to drive informed decisions and strategic growth.

The post What is Data Readiness and Why Is It Important? appeared first on Datactics.

In the complex world of finance, safeguarding consumers’ interests is paramount. The Financial Services Compensation Scheme (FSCS) plays a crucial role in protecting customers of authorised financial services firms in the United Kingdom. This comprehensive guide explores what the FSCS is, why it matters, and how organisations can ensure compliance with its regulations through effective data management and readiness.

Understanding the FSCS

What Is the FSCS?

The Financial Services Compensation Scheme (FSCS) is the UK’s statutory compensation scheme for customers of authorised financial services firms. Established under the Financial Services and Markets Act 2000, the FSCS became operational on 1 December 2001. It acts as a safety net, providing compensation to consumers if a financial services firm fails or ceases trading.

Purpose of the FSCS

• Consumer Protection: The primary aim is to protect consumers from financial loss when firms are unable to meet their obligations.
• Financial Stability: By ensuring confidence in the financial system, the FSCS contributes to overall market stability.
• Regulatory Compliance: Encourages firms to adhere to regulations, knowing that failure impacts both customers and the broader industry.

Coverage of the FSCS

The FSCS covers a wide range of financial products and services, including:

• Deposits: Banks, building societies, and credit unions.
• Investments: Investment firms and stockbrokers.
• Insurance: Life and general insurance policies.
• Home Finance: Mortgage advice and arrangement.

Compensation Limits

As of the latest regulations:

• Deposits: Up to £85,000 per eligible person, per authorised firm.
• Investments: Up to £85,000 per person.
• Insurance: 90% of the claim with no upper limit for most types, 100% for compulsory insurance (e.g. third-party motor insurance).

Regulatory Requirements for Financial Institutions

Obligations Under FSCS Regulations

Financial institutions authorised by the Financial Conduct Authority (FCA) or the Prudential Regulation Authority (PRA) have specific obligations:

• Maintain Accurate Records: Keep up-to-date and precise customer data to facilitate compensation processes.
• Produce a Single Customer View (SCV): Consolidate all accounts held by a customer into a single record.
• Timely Reporting: Be prepared to provide necessary data to the FSCS promptly in the event of a firm’s failure.

Single Customer View (SCV)

The SCV is a regulatory requirement that mandates firms to create a consolidated view of each customer’s aggregate protected deposits. It enables the FSCS to:

• Identify Eligible Customers Quickly: Determine who is entitled to compensation without delay.
• Calculate Accurate Compensation Amounts: Ensure customers receive the correct compensation.
• Facilitate Prompt Payouts: Aim to reimburse customers within seven days of a firm’s failure.

Challenges in Achieving FSCS Compliance

Data Silos and Fragmentation

• Multiple Systems: Customer data may be spread across various systems and departments.
• Inconsistencies: Differing data formats and standards hinder consolidation.

Poor Data Quality

• Inaccuracies: Errors in customer details can delay compensation.
• Incomplete Records: Missing information complicates eligibility assessments.

Regulatory Complexity

• Evolving Requirements: Keeping up with changes in FSCS regulations demands ongoing attention.
• Detailed Compliance: Meeting stringent SCV standards requires meticulous data management.

Technological Constraints

• Legacy Systems: Outdated technology may not support efficient data aggregation.
• Integration Difficulties: Challenges in merging data from disparate sources.

Resource Limitations

• Staff Expertise: Lack of skilled personnel in data management and compliance.
• Time Pressures: Regulatory deadlines necessitate swift action.

The Role of Data Readiness in FSCS Compliance

Data Readiness refers to the state of having data that is accurate, complete, and readily accessible for use. Achieving Data Readiness is vital for FSCS compliance:

Efficient SCV Production

• Accurate Aggregation: Combines customer accounts accurately for the SCV.
• Speed: Enables quick generation of SCV files, meeting regulatory timelines.

Regulatory Compliance

• Data Integrity: High-quality data ensures adherence to FSCS requirements.
• Audit Trails: Proper data management provides documentation for regulatory scrutiny.

Enhanced Customer Trust

• Prompt Compensation: Efficient processes lead to timely payouts, maintaining customer confidence.
• Transparency: Clear communication facilitated by accurate data.

How Datactics Supports FSCS Compliance

Datactics offers advanced data management solutions that help financial institutions achieve Data Readiness, specifically addressing the challenges associated with FSCS compliance.

Automated Data Cleansing

• Error Identification: Detects inaccuracies in customer data, such as incorrect contact details.
• Correction Mechanisms: Applies rules to correct common errors automatically.

Data Validation

• Standardisation: Ensures data conforms to required formats and industry standards.
• Consistency Checks: Aligns data across different systems for uniformity.

Single Customer View Creation

• Data Matching: Uses sophisticated algorithms to link related records across systems.
• Duplication Removal: Eliminates duplicate entries to create a true SCV.

Advanced Matching Algorithms

• Fuzzy Matching: Recognises and matches records that may not be identical but represent the same customer.
• Hierarchical Matching: Considers relationships between accounts and customers.

Compliance Monitoring

• Real-Time Insights: Monitors data quality metrics relevant to FSCS requirements continuously.
• Alerts and Notifications: Signals when data falls below acceptable standards.

Audit Trails

• Documentation: Maintains detailed records of data management activities.
• Accountability: Supports regulatory audits with transparent processes.

Self-Service Data Quality Platform

• Empowering Business Users: Allows non-technical staff to manage data quality.
• Intuitive Tools: User-friendly interfaces for data cleansing and monitoring.

Benefits of Using Datactics’ Solutions

• Enhanced Data Accuracy: Improves reliability and trustworthiness of customer data.
• Operational Efficiency: Reduces time and resources needed for compliance tasks.
• Regulatory Confidence: Demonstrates robust data practices to regulators.

To Conclude

The Financial Services Compensation Scheme (FSCS) is a critical component of the UK’s financial safety net, protecting consumers and maintaining confidence in the financial system. For financial institutions, complying with FSCS regulations is not only a legal obligation but also a matter of customer trust and operational efficiency.

Achieving Data Readiness is essential for meeting FSCS requirements, particularly in producing accurate Single Customer Views and ensuring timely compensation payouts. The challenges of data silos, poor data quality, and regulatory complexity necessitate robust data management solutions.

Datactics provides the expertise and technology needed to overcome these challenges. Through data quality improvements, data integration, and compliance support, Datactics enables financial institutions to meet their FSCS obligations confidently and efficiently.

Get Started with Datactics

Ensure your organisation is fully prepared for FSCS compliance with Datactics’ comprehensive data management solutions.

• Learn More: Explore Datactics’ Solutions for FSCS Compliance
• Contact Us: Email at info@datactics.com
• Visit Our Website: www.datactics.com

Achieve Data Readiness with Datactics and ensure seamless compliance with the Financial Services Compensation Scheme. Empower your organisation with accurate, consolidated, and compliant data to protect your customers and uphold your reputation in the financial industry.

The post What is the Financial Services Compensation Scheme (FSCS) and Why Is It Important? appeared first on Datactics.

In the aftermath of the 2008 financial crisis, regulators worldwide sought to enhance the stability and transparency of financial markets. The European Market Infrastructure Regulation (EMIR) is a key piece of European Union legislation introduced to address these concerns, specifically targeting the over-the-counter (OTC) derivatives market. This comprehensive guide explores what EMIR is, why it matters, and how organisations can ensure compliance through effective data management and readiness.

Understanding EMIR

What Is EMIR?

The European Market Infrastructure Regulation (EMIR) is an EU regulation that came into force on 16 August 2012. It aims to reduce systemic risk, increase transparency, and strengthen the infrastructure of OTC derivatives markets. EMIR imposes requirements on OTC derivative contracts, central counterparties (CCPs), and trade repositories.

Purpose of EMIR

• Enhance Financial Stability: By regulating OTC derivatives, EMIR seeks to mitigate the risks that these complex financial instruments pose to the financial system.
• Increase Transparency: Mandates the reporting of derivative contracts to trade repositories, providing regulators with a clear view of market activities.
• Reduce Counterparty Risk: Introduces central clearing and risk mitigation techniques to minimise the risk of default by counterparties.

Scope of EMIR

EMIR applies to:

• Financial Counterparties (FCs): Banks, investment firms, insurance companies, UCITS funds, pension schemes, and alternative investment funds.
• Non-Financial Counterparties (NFCs): Corporations not in the financial sector that engage in OTC derivative contracts exceeding certain thresholds.
• Central Counterparties (CCPs)
• Trade Repositories (TRs)

EMIR Requirements for Financial Institutions

1. Trade Reporting

Mandatory Reporting

• Obligation: All counterparties and CCPs must report details of any derivative contract (OTC and exchange-traded) to a registered trade repository.
• Deadline: Reports must be submitted no later than one working day following the execution, modification, or termination of a contract.

Information Required

• Counterparty Details: Identification of both parties involved.
• Contract Details: Type, underlying asset, maturity, notional value, price, and settlement date.
• Valuation and Collateral Data: Regular updates on the mark-to-market or mark-to-model valuations and collateral posted.

2. Central Clearing

Clearing Obligation

• Eligible Contracts: Standardised OTC derivatives determined by the European Securities and Markets Authority (ESMA) must be cleared through authorised CCPs.
• Thresholds: Non-financial counterparties exceeding specified clearing thresholds become subject to the clearing obligation.

Benefits of Central Clearing

• Risk Reduction: CCPs stand between counterparties, reducing the risk of default.
• Transparency: Enhanced monitoring of exposures and positions.

3. Risk Mitigation Techniques for Non-Cleared Trades

For OTC derivatives not subject to central clearing:

Timely Confirmation

• Requirement: Contracts must be confirmed within specified timeframes, typically on the same day or within two business days.

Portfolio Reconciliation

• Frequency: Regular reconciliation of portfolios with counterparties, frequency depending on the number of outstanding contracts.

Portfolio Compression

• Purpose: Reduce counterparty credit risk by eliminating redundant contracts.

Dispute Resolution

• Procedures: Establish robust processes to identify, record, and monitor disputes with counterparties.

Margin Requirements

• Collateral Exchange: Implementation of initial and variation margin requirements to mitigate counterparty credit risk.

Challenges in Achieving EMIR Compliance

Complex Reporting Requirements

• Data Volume: Managing over 80 data fields per trade, leading to significant data processing demands.
• Data Accuracy: Ensuring precise and complete information to avoid misreporting.

Inconsistent Data Standards

• Multiple Systems: Disparate data sources with varying formats complicate aggregation.
• Data Silos: Fragmented data hinders the creation of a unified view of trading activities.

Integration with Trade Repositories and CCPs

• Technical Connectivity: Establishing secure and efficient links for data transmission.
• Submission Errors: Risks of failed or delayed reporting due to technical issues.

Regulatory Changes

• Evolving Requirements: Keeping abreast of amendments to EMIR and related technical standards.
• Cross-Border Compliance: Managing obligations across different jurisdictions with overlapping regulations.

Legacy Systems

• Inadequate Infrastructure: Older systems may lack the capability to handle EMIR’s demands.
• Scalability Issues: Difficulty in scaling systems to accommodate increased data volumes.

Resource Limitations

• Expertise Shortage: Need for specialised knowledge in EMIR compliance and data management.
• Budget Constraints: Allocating sufficient resources for system upgrades and compliance initiatives.

The Role of Data Readiness in EMIR Compliance

Data Readiness refers to the state of having accurate, complete, and accessible data that is prepared for use in compliance reporting and risk management.

Importance of Accurate and Complete Data

• Regulatory Compliance: Ensures all reporting obligations are met accurately and on time.
• Risk Management: Provides reliable data for monitoring exposures and implementing risk mitigation techniques.

Facilitating Compliance Efforts

• Efficiency: Streamlines reporting processes, reducing manual effort and errors.
• Transparency: Enhances visibility into trading activities, supporting internal oversight and regulatory scrutiny.

How Datactics Helps with EMIR Compliance

Datactics offers advanced data quality and data management solutions that assist financial institutions in achieving Data Readiness for EMIR compliance.

Automated Data Cleansing

• Error Detection and Correction: Identifies inaccuracies in trade data and rectifies them automatically.
• Standardisation: Ensures data conforms to required formats and industry standards, facilitating seamless reporting.

Data Validation

• Business Rules Implementation: Applies EMIR-specific validation rules to datasets.
• Consistency Checks: Verifies data consistency across different systems and reports.

Unified Data View

• Data Aggregation: Combines data from various sources to provide a comprehensive view of trading activities.
• Advanced Matching Algorithms: Links related data points across systems for accurate reporting and risk assessment.

Reporting Facilitation

• Data Preparation: Structures and formats data according to trade repository requirements, ensuring compliance with technical standards.
• Automated Submission: Integrates with trade repositories and CCPs for seamless data transmission.

Risk Mitigation Measures

• Portfolio Reconciliation Support: Automates reconciliation processes with counterparties, ensuring discrepancies are identified and resolved promptly.
• Dispute Resolution Tracking: Monitors and documents dispute resolution activities, maintaining compliance records.

Self-Service Data Quality Platform

• Empowering Business Users: Allows compliance officers and data stewards to manage data quality without heavy reliance on IT.
• User-Friendly Tools: Provides intuitive interfaces for monitoring data readiness and addressing issues promptly.

Benefits of Using Datactics’ Solutions

• Improved Data Accuracy: Enhances the reliability of reported data, reducing the risk of regulatory penalties.
• Operational Efficiency: Automates labour-intensive tasks, freeing resources for strategic initiatives.
• Regulatory Confidence: Demonstrates robust compliance practices to regulators, building trust.
• Risk Reduction: Minimises potential financial penalties and reputational damage.

Achieving Data Readiness for EMIR Compliance: A Step-by-Step Approach

1. Assess Current Data Landscape

• Data Audit: Evaluate existing trade data for completeness and accuracy.
• Identify Gaps: Recognise areas where data quality is lacking.

2. Implement Data Quality Measures

• Data Cleansing: Utilise automated tools to correct errors and standardise data formats.
• Validation Processes: Establish rigorous validation against EMIR requirements.

3. Enhance Data Integration

• Consolidation Strategy: Develop a plan to merge data from various systems into a unified platform.
• Advanced Matching: Use sophisticated algorithms to link related data points.

4. Automate Reporting Processes

• Data Preparation: Structure data according to trade repository specifications.
• Automated Submission: Integrate systems for seamless reporting to TRs and CCPs.

5. Implement Risk Mitigation Techniques

• Portfolio Reconciliation: Automate reconciliation with counterparties to identify discrepancies.
• Dispute Resolution Procedures: Establish protocols for efficient dispute management.

6. Establish Data Governance Framework

• Policies and Procedures: Define clear guidelines for data management and compliance.
• Roles and Responsibilities: Assign accountability for data quality and compliance tasks.

7. Continuous Monitoring and Improvement

• Regular Reviews: Monitor data quality metrics and compliance status.
• Feedback Mechanisms: Implement processes for ongoing enhancements based on insights gained.

To Conclude

The European Market Infrastructure Regulation (EMIR) represents a significant regulatory framework aimed at enhancing the stability and transparency of the financial markets within the European Union. Compliance with EMIR is a complex task that requires meticulous data management, robust reporting mechanisms, and effective risk mitigation strategies.

Achieving Data Readiness is essential for meeting EMIR’s stringent requirements. Financial institutions must ensure that their data is accurate, complete, and readily accessible to fulfil reporting obligations and manage risks effectively.

Datactics offers the tools and expertise needed to navigate the complexities of EMIR compliance. Through advanced data quality enhancement, data integration, and compliance support, Datactics enables organisations to fulfil their obligations confidently and efficiently.

By leveraging Datactics’ solutions, financial institutions can not only mitigate the risks associated with non-compliance but also enhance operational efficiency, strengthen risk management practices, and maintain their reputation in the financial industry.

Get Started with Datactics

Ensure your organisation is fully prepared for EMIR compliance with Datactics’ comprehensive data management solutions.

• Learn More: Explore Datactics’ Solutions for EMIR Compliance
• Contact Us: Email at info@datactics.com
• Visit Our Website: www.datactics.com

Achieve Data Readiness with Datactics and ensure seamless compliance with the European Market Infrastructure Regulation. Empower your organisation with accurate, consolidated, and compliant data to meet regulatory demands and enhance your position in the financial markets.

The post What is the European Market Infrastructure Regulation (EMIR) and Why Is It Important? appeared first on Datactics.

Datactics has secured the ‘Most Innovative Technology for Regulatory Compliance’ award at this year’s A-Team Group RegTech Insight Awards USA.

The Belfast-based firm, which has made its name specializing in innovative solutions to challenging data problems, developed its Data Readiness solution in response to the prevalence of data-driven regulations across both sides of the Atlantic. 

Data Readiness grew out of Datactics’ close work with banking customers in the UK, primarily around data used to identify and reporting on customer deposits in line with stringent regulation from the Financial Conduct Authority (FCA) and Prudential Regulatory Authority (PRA).  

In 2024, Datactics developed Data Readiness as a specific defined solution to measure and prepare data to specific regulatory standards, offering the solution with a range of deployment options, including as-a-service.  

Behind the solution

Matt Flenley, Head of Marketing at Datactics, noted, “This award is brilliant news for all our talented developers and engineers back home. We’ve a long record of working alongside customers to help them with specific problems they’re encountering, and for which the risk of bad data affecting their ability to demonstrate compliance is often significant.

“With our experience in developing rule-sets for customers seeking to comply with UK depositor protection regulations, alongside international standards such as BCBS 239, we felt the time was right to offer this solution as its own piece of regulatory compliance technology.

“We’d like to thank the A-Team panel and all those who saw fit to recognise the approach we’ve taken here – thank you all so much!” 

Angela Wilbraham, CEO at A-Team Group, and host of the 4th annual RegTech Insight Awards USA 2024, commented, “Congratulations to Datactics for winning the Most Innovative Technology for Regulatory Compliance award in this year’s A-Team Group RegTech Insight Awards USA 2024.

“These awards celebrate providers of leading RegTech solutions, services and consultancy and are uniquely designed to recognise both start-up and established providers who are creatively finding solutions to help with regulatory challenges, and span a wide range of regulatory requirements.

“Our congratulations for their achievement in winning this award in a highly competitive contest.” 

For more on Datactics, visit www.datactics/get-data-readiness 

For more on A-Team Group, visit https://a-teaminsight.com/category/regtech-insight/  

The post Datactics Snaps Up Award For Regulator-Ready Data appeared first on Datactics.

It’s October, the Northern Hemisphere nights are drawing in, and for many it’s time when things take a scarier turn. But for public sector leaders exploring AI, that fright need not apply to your data. It definitely shouldn’t be something that haunts your digital transformation dreams.

With a reported £800m budget unveiled by the previous government to address ‘digital and AI’, UK public sector departments are keen to be the first to explore the sizeable benefits that AI and automation offer. The change of government in July 2024 has done nothing to indicate that this drive has lessened in any way; in fact, the Labour manifesto included the commitment to a “single unique identifier” to “better support children and families”[1].

While we await the first Budget of this Labour government, it’s beyond doubt that there is an urgent need to tackle this task amid a cost-of-living crisis, with economies still trying to recover from the economic shock of COVID and deal with energy price hikes amid several sizeable international conflicts.

However, like Hollywood’s best Halloween villains, old systems, disconnected data, and a lack of standardisation are looming large in the background.

Acting First and Thinking Later

It’s completely understandable that the pressures would lead us to this point. Societal expectations from the emergence of ChatGPT, among others, have only fanned the flames, swelling the sense that technology should just ‘work’ and leading to an overinflated belief in what is possible.

Recently, LinkedIn attracted some consternation[i][2] by automatically including members’ data in its AI models without seeking express consent first. For whatever reason, the idea that people would just accept this change was overlooked. It took the UK’s Information Commissioner’s Office, the ICO, to intervene for the change to be withdrawn – in the UK, at least.

A dose of reality is the order of the day. Government systems are lacking integrated data, and clear consent frameworks of the type that LinkedIn actually possesses seldom exist in one consistent way. Already lacking funds, the public sector needs to act carefully, and mindfully, to prevent their AI experiments (which is, after all, what they are) from leading to inaccuracies and wider distrust from the general public.

Streamlining Data and Consent in One Single View

One solution is for Government departments to form one, holistic set of consents concerning use of data for AI, especially Large Language Models and Generative AI – similar to communication consents under the General Data Protection Regulation, GDPR.

The adoption of a flexible consent management policy, one which can be updated and maintained for future developments and tied to an interoperable, standardised single view of citizen (SCV), will serve to support the clear, safe development of AI models into the future. The risks of building models now, on shakier foundations, will only serve to erode public faith. The evidence of the COVID-era exam grades fiasco[3] demonstrates the risk that these models present to real human lives.

Of course, it’s not easy to do. Many legacy systems contain names, addresses and other citizen data in a variety of formats. This makes it difficult to be sure that when more than one dataset includes a particular name, that name actually refers to the same individual. Traditional solutions to this problem use anything from direct matching technology to the truly awful exercise of humans manually reviewing tens of thousands of records in spreadsheets. This is one recurring nightmare that society really does need to stop having.

Taking Refuge in Safer Models

Intelligent data matching uses a variety of matching algorithms and well-established machine learning techniques to reconcile data held in old systems, new ones, documents, even voice notes. Such approaches could help the public sector to streamline their SCV processes, managing consents more effectively. The ability to understand who has opted in, marrying opt-ins and opt-outs to demographic data is critical. This approach will help model creators to interpret the inherent bias in the models built on those consenting to take part, to understand how reflective of society the predictive models are likely to be – including whether or not it is actually safe to use the model at all.

It’s probable that this transparency in process could also lead to greater trust in the general public to take part in data sharing in this way. In the LinkedIn example, the news that data was being used without explicit consent, raced around like wildfire on the platform itself. This sort of outcome cannot be what LinkedIn anticipated, which in and of itself is a concern about the mindset of the model creators.

It Doesn’t Have to Be a Nightmare

It’s a spooky enough season without adding more fear to the bonfire; certainly, this article isn’t intended as a reprimand. The desire to save time and money to deliver better services to a country’s citizens is a major part of many a civil servant’s professional drive. And AI and automation offer so many opportunities for much better outcomes! For just one example, NHS England’s AI tool already uses image recognition to detect heart disease up to 30 times faster than a human[4] . Mid and South Essex (MSE) NHS Foundation used a predictive analytical machine learning model called Deep Medical to reduce the rate at which patients either didn’t attend appointments or cancelled with short notice (referred to as Did Not Attend, or DNA). Its pilot project identified which patients were more likely to fall into the DNA category, developed personalised reminder schedules, and through identifying frail patients who were less likely to attend an appointment, highlighted them to relevant clinical teams.[5]

The time for taking action is now. Public sector organisations, government departments and agencies should focus on the need to develop systems that will preserve and maintain trust in the AI-led future. This blog has shown that better is possible, through a dedicated desire to align citizen data and their consents to contact. In a society where people have trust and transparency in the ways that their data will be used to train AI, the risk of nightmare scenarios can be averted and we’ll all sleep better at night.

[1] https://www.ropesgray.com/en/insights/viewpoints/102jc9k/labour-victory-the-implications-for-data-protection-ai-and-digital-regulation-i

[2] https://etedge-insights.com/in-focus/trending/linkedin-faces-backlash-for-using-user-data-in-ai-training-without-consent/

[3] https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7894241/#:~:text=COVID%2D19%20prompted%20the%20UK,teacher%20assessed%20grades%20and%20standardisation.

[4] https://www.healthcareitnews.com/news/emea/nhs-rolls-out-ai-tool-which-detects-heart-disease-20-seconds

[5] https://www.nhsconfed.org/publications/ai-healthcare

[i]

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The oak-panelled setting of historic Toynbee Hall provided the venue for the 2024 Datactics Summit, which this year carried a theme of ‘Data-Driven Return on Investment.’

Attendees gathered for guest speaker slots covering:

• Danske Bank UK’s Lyndsay Shields presenting a ‘Data Management Playbook’ covering the experiences of beginning with a regulatory-driven change for FSCS compliance, through to broader internal evangelisation on the benefits of better data;

• Datactics’ own data engineer, Eugene Coakley, in a lively discussion on the data driving sport, drawing from his past career as a professional athlete and Olympic rower with Team Ireland;

• and Renfrewshire HSCP’s Bobby McClung explaining how automation and the saving of person-hours or even days in data remediation was having a material impact on the level of care the organsation is now able to deliver to citizens making use of its critical services.

The Datactics Customer Awards in full

In recent months, the team at Datactics has worked to identify notable achievements in data in the past year. Matt Flenley, Head of Marketing at Datactics, presented each with a specific citation, quoted below.

Data Culture Champion of the Year – Lyndsay Shields, Danske Bank UK

“We’re delighted to be presenting Lyndsay with this award. As one of our longest-standing customers, Lyndsay has worked tirelessly to embed a positive data culture at Danske Bank UK. Her work in driving the data team has helped inform and guide data policy at group level, bringing up the standard of data management across Danske Bank.

“Today’s launch of the Playbook serves to showcase the work Lyndsay and her team have put into driving the culture at Danske Bank UK, and the wider culture across Danske Bank.”

Data-Driven Social Impact Award – Renfrewshire Health and Social Care Partnership

“Through targeted use of automation, Renfrewshire Health and Social Care Partnership has been able to make a material difference to the operational costs of local government care provision.

“Joe Deary’s early vision and enthusiasm for the programme, and the drive of the team under and alongside Bobby, has effectively connected data automation to societally-beneficial outcomes.”

Data Strategy Leader of the Year – RBC Brewin Dolphin

“RBC Brewin Dolphin undertook a holistic data review towards the end of 2023, culminating in a set of proposals to create a rationalised data quality estate. The firm twinned data this strategy with technology innovation including being early adopters of ADQ from Datactics. They overcame some sizeable hurdles, notably supporting Datactics in our early stages of deployment. Their commitment to being an ambitious, creative partner makes them stand out.

“At Datactics we’re delighted to be giving the team this award and would also like to thank them for being exemplars of patience in the way they have worked with us this year in particular.”

Datactics Award for Partner of the Year – Solidatus

“Solidatus and Datactics have been partnered for the last two years but it’s really in 2023-2024 that this partnership took off.

“Ever since we jointly supported Maybank, in Malaysia, in their data quality and data lineage programme, we have worked together on joint bids and supported one another in helping customers choose the ‘best of breed’ option in procuring data management technology. We look forward to our next engagements!”

Datactics Data Champion of the Year – NHSBSA

“For all the efforts Tony, Nick and team have made to spread the word about doing more with data, we’d like to recognize NHS Business Services Authority with our Datactics Data Champion of the Year award.

“As well as their advocacy for our platform, applying it to identify opportunities for cost savings and efficiencies across the NHS, the team has regularly presented their work to other Government departments and acted as a reference client on multiple occasions. Their continued commitment to the centrality of data as a business resource is why they’re our final champions this year, the Datactics Data Champion 2024.”

Gallery of Winners

Toasting success at Potter & Reid

The event closed with its traditional visit to Shoreditch hot spot Potter & Reid. Over hand-picked canapés and sparkling drinks, attendees networked and mingled to share in the award winners’ achievements in demonstrating what data-driven culture and return on investment looks like in practice. Keep an eye out for a taster video from this year’s event!

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At Datactics, maintaining the highest information security standards has always been at the core of our operations. This unwavering commitment has recently been formally recognised with our achievement of the ISO 27001:2022 Certification for our Information Security Management System (ISMS).

It is a major milestone in achieving ISO27001 and a powerful validation of our continuous efforts to protect client data and ensure the integrity, confidentiality, and availability of our information assets. In this blog, I’ll share our journey of achieving ISO 27001:2022.

The journey toward ISO 27001:2022 Certification

Our path to ISO certification began in Q4 2023, with invaluable support from industry experts at Vertical Structure.

The process started with a thorough evaluation of our existing security posture, carefully measuring it against the rigorous requirements set by ISO 27001. This stage involved a deep dive into our policies, procedures, and infrastructure to identify potential vulnerabilities and areas for improvement.

Following the evaluation, the DevOps team implemented targeted improvements over several months to strengthen our security framework. These efforts came to a head in January 2024 with a successful Stage 1 audit conducted by NQA. This initial audit was instrumental, providing us with crucial feedback and pinpointing specific areas for improvement.

The rigorous Stage 2 audit

By June 2024, we prepared for the critical Stage 2 audit and welcomed NQA back to the Datactics headquarters for an intensive review

This audit was exhaustive. For five days, the auditors scrutinized every facet of our ISMS. The audit team delved into our operations, from software development processes to client support systems and internal IT protocols. The auditors even spot-tested Datactics staff on their knowledge and understanding of Information Security Management within the company. This thorough examination ensured that no stone was left unturned.

Thanks to the hard work of our entire team, we successfully passed the audit! Datactics earned the ISO 27001:2022 certification, reinforcing our compliance with global information security standards and demonstrating our proactive approach to maintaining a secure operational environment.

Beyond certification: A commitment to excellence

For Datactics, the ISO 27001 certification is more than just a formal recognition; it embodies our ongoing commitment to excellence in information security and sets the stage for future advancements.

Achieving ISO 27001 is a significant milestone for Datactics and is the result of hard work and dedication from the entire team as we aim to grow and improve our security posture, proving the team’s dedication to providing secure and reliable policies and procedures that protect ourselves and our clients.

This milestone is more than just an endpoint; it marks the beginning of an ongoing journey. As we continue to innovate and expand our platform, maintaining a robust information security practice will remain a top priority. Backed strongly by our senior management team, we are ready to build on this foundation, creating a more secure, process-driven, and impactful data quality platform that will positively influence the industry.

As we continue our journey, the ISO 27001:2022 Certification for Information Security Management System reinforces our dedication to building a more secure, process-driven, and impactful data quality platform that will positively influence the industry. As a team, we are excited to see what comes next.

About ISO 27001:2022

The ISO 27001 certification is recognised as the global benchmark for managing information security. Datactics accreditation has been issued by NQA, a leading global independently accredited certification body that provides assessments (audits) of organisations to various management system standards since 1988. The process was supported by Vertical Structure, who conduct technical security training, helping companies to achieve certification to international standards such as ISO27001.

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Datactics, a leader in data quality software has achieved ISO 27001:2022 Certification for Information Security Management System.

The ISO 27001 certification is recognised globally as a benchmark for managing information security. The rigorous certification process, conducted by NQA and Vertical Structure, involved an extensive evaluation of Datactics’ security policies, procedures, people, and controls. Achieving this certification demonstrates Datactics’ dedication to safeguarding client data and maintaining information assets’ integrity, confidentiality, and availability.

Victoria Wallace, Senior DevOps & Security Specialist, stated: “Security is at the heart of everything that Datactics does and achieving ISO 27001:2022 certification is a testament to the team’s unwavering commitment in this technical field. Showcasing the extensive work that went into this prestigious achievement proves that dedication and determination can lead to significant success, both within Datactics and across our client ecosystem. Achieving and maintaining this certification is a key part of Datactics’ progress in enhancing our secure, process-driven, and powerful data quality platform.”

Tom Shields, Cyber & Information Security Consultant at Vertical Structure, said “It was a pleasure working with the team at Datactics. Their enthusiastic approach to ISO 27001 Information Security and the associated business risk mitigation was evident in every interaction. Involvement from top to bottom was prioritised from day one, allowing us to integrate into their team from the very outset. The opportunity to guide such organisations in certifying to ISO 27001 is a privilege for us, and we look forward to continuing to work alongside their team in the future.

About ISO 27001:2022 Certification

Datactics’ accreditation has been issued by NQA, a leading global independently accredited certification body. NQA has provided assessments (audits) of organisations to various management system standards since 1988.

Founded in 2006, Vertical Structure is an independent cyber security consultancy with a ‘people-first’ approach. Vertical Structure specialises in providing people-focused security and penetration testing services for web applications, cloud infrastructure and mobile applications.

Vertical Structure also conducts technical security training, helping companies to achieve certification to international standards such as ISO 27001, Cyber Essentials and CAIQ and are proud to be an Amazon Web Services® Select Consulting Partner.

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2004 Athens Olympic Games

Twenty years ago, I represented Team Ireland in the 2004 Athens Olympic Games, in the men’s lightweight rowing four. The experience was both challenging and rewarding – training for the Olympics required immense dedication, teamwork, and resilience. But the camaraderie with my teammates, plus the thrill of representing my country on the world stage, was unparalleled.

Whilst the experience of the Olympics was incredible, adjusting to life outside the professional world of sport was challenging. I spent many years searching for job satisfaction after retiring from international sport in 2008, until an opportunity for something new within the world of software development presented itself during the Pandemic. I’d always been interested in tech, but balancing work and raising two young kids made it difficult to find the time to upskill and consider a career move.

Everything changed in April 2020, when I was furloughed from my job and discovered a Masters in Software Development offered by Queen’s University, Belfast. The course provided an excellent opportunity to earn whilst I learned, allowing me to develop my skills without financial strain. As I progressed through the program, I found myself particularly drawn to data analysis and by the end of the program (15 months later), I had the fortunate opportunity to meet Datactics’ CEO, Stuart Harvey.

Finding my new team

Stuart felt like the career guidance teacher I never had. During our first initial meeting, he recognised that my unique skill set and experience would lend themselves to developing a career in data and suggested that I join the Data Engineering team at Datactics. Because working in the tech industry doesn’t hinge solely on writing code, it can be just as valuable to have skills in problem-solving, creative thinking, effective communication, and teamwork; all of which I developed as a rower.

Not long into the role, I felt a familiar sense of camaraderie and teamwork underpinning daily life at Datactics. The collaborative environment mirrored the tight-knit dynamic of my rowing team, where each member’s contribution is crucial to success and every team member is valued. I also found myself applying the same principles I learnt in professional sport – precision and accuracy- to my work at Datactics. A typical day for me involves working across financial services and government, ensuring data quality and integrity for businesses worldwide. I still get the reward of working in a team, but my responsibilities now are more data quality rule-building than rowing; less oar technique and more data engineer skills.

A data-driven sport

In hindsight, my interest in data is not all that surprising. Rowing is a data-driven sport, with every stroke, race, and training session meticulously recorded and analysed. Having accurate and reliable data helped me understand my performance, identify areas for improvement, and strategise for future races. Now, instead of improving the performance of myself and my team, I use these same data-driven principles to help our customers enhance their performance and achieve their goals.

Transitioning from the world of sport to software has been uniquely challenging and rewarding, with rowing providing me with more transferable skills than I ever expected. I still get to leverage the lessons I learned on the water and enjoy the daily camaraderie of working with an incredible team. As the Paris Games mark twenty years since I represented my country, I’m reminded of some amazing times representing Team Ireland and look forward to seeing where the athletes of Paris 2024 will go in their careers. I’m also reminded that the Olympic spirit, and the value of teamwork, has never left me.

About Eugene

Eugene is a Senior Data Engineer at Datactics. Datactics provides leading data quality and matching software, augmented by machine learning and designed for non-technical business users. Eugene assists clients with their data quality ambitions, providing hands-on support and data quality expertise. At Datactics, we have developed our professional services offering, Datactics Catalyst, to deliver practical support in your data strategy. From augmenting your data team to work on specific data projects to delivering specialised training, our professional services team support data leaders in reaching their goals. Find out more here.

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What is Data Quality and why does it matter?

 

Data Quality refers to how fit your data is for serving its intended purpose. Good quality data should be reliable, accurate and accessible. 

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Kubernetes: An Introduction 

In the ever-evolving world of engineering, scalability isn’t just a feature—it’s a necessity. As businesses and data continue to grow, the ability to scale applications efficiently becomes critical. At Datactics, we are at the forefront of integrating cutting-edge AI/ML functionality that enhances our Augmented Data Quality solutions. To align with current standards and ensure optimal AI/ML scalability with Kubernetes, our AI/ML team has integrated K8s into our infrastructure and deployment strategies.

What is Kubernetes? 

Kubernetes, also known as K8s, is an open-source platform designed to automate the deployment, scaling, and management of containerised applications. It adjusts the number of containerised applications to match incoming traffic, ensuring adequate resources to handle requests seamlessly.

Docker containers, managed through an API layer often using FastAPI, function like fully equipped packages of software, including all necessary dependencies. Kubernetes enables ‘horizontal scaling’—increasing or decreasing the number of container instances based on demand—using various load balancing and rollout strategies to make the process appear seamless. This method helps evenly spread traffic among containers, preventing overload and optimising resources. 

Kubernetes for Data Management

Every day, companies handle a lot of complicated data from different sources, at different velocities, and scales. This includes important tasks like cleaning, combining, matching, and resolving errors. It’s crucial to suggest and enforce Data Quality (DQ) rules in your data pipelines and efficiently identify DQ issues, ensuring these processes are automated, scalable, and responsive to fluctuating demands. 

Many organisations use Kubernetes (K8s) to automate deploying, scaling, and managing applications in containers across multiple machines. With features like service discovery, load balancing, self-healing, automated rollouts, and rollbacks, Kubernetes has become a standard for managing applications that are essential for handling complex data—both in the cloud and on-premise. Implementing AI/ML scalability with Kubernetes allows these organisations to process large volumes of data efficiently and respond quickly to changes in data flow and processing demands.

Real-World Scenario: The Power of Kubernetes 

It’s Friday at 5pm, and just as you’re about to leave the office, your boss informs you that transaction data for last month has been uploaded to the network share in a CSV document and it needs to be profiled immediately. The CSV file is massive—about a terabyte of data—and trying to open it in Excel would be disastrous. This is where Datactics and Kubernetes come to the rescue.  

You could run a Python application that might take all weekend to process, meaning you’d have to keep checking its progress and your weekend would be ruined. Instead, you could use Kubernetes to scale out Datactics’ powerful Profiling tools and complete the profiling before you even leave the building. Company saved. Weekend saved. 

Application of Kubernetes 

The world has grown progressively faster, and speed in the digital realm is king: speed in service delivery, speed in recovery in the event of a failure, and speed to production. We believe that the AI/ML features offered by Datactics should adhere to the same high standards. No matter how much data your organisation handles or how many data sources there are, it’s important to adjust resources to meet demand and reduce waste during the most critical moments. 

At Datactics, AI/ML features are deployed as Docker containers and FastAPI. Depending on your particular environment, we might run these containers on a single machine like AWS EC2 and deploy a single instance of each AI/ML feature, which is suitable for experiments and proof of concepts. However, for a fully operational infrastructure capable of supporting a large organisation, Kubernetes is essential. 

Kubernetes helps deploy Docker containers by providing a blueprint with deployment details, necessary resources, and any dependencies like external storage. This blueprint facilitates horizontal scaling to support additional instances of each AI/ML feature. 

Conclusion 

Kubernetes proved to be a game-changer for scaling Datactics’ AI/ML services, ultimately leading to a robust solution that ensures our AI/ML features can dynamically scale according to client needs. We tailor our deployment strategies to meet the diverse needs of our clients. Whether the requirement is a simple installation or a complex, scalable infrastructure, our commitment is to provide solutions that ensure our clients’ applications are efficient, reliable, and scalable. 

We aim to meet any specific requirements, always exploring various potential deployment setups preferred by our clients. If your organisation is looking to enhance its data processing capabilities, get in touch with us here. Let us help you optimise your data management strategies with the power of Kubernetes and our innovative AI/ML solutions. 

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Read Chloe’s Q&A from the panel session, ‘Challenges and opportunities facing SMEs in the security and public safety sectors’, below:

What made you want to join the forum?

For starters, techUK is always a pleasure to work with – my colleagues and I at Datactics have several contacts at techUK that we speak with regularly and it’s clear that they care about the work they’re doing. It never feels like a courtesy call – you always come away with valuable actions to follow up on. Having had such positive experiences with techUK before, I felt encouraged to join the Security and Public Safety SME forum. Being a part of the Security and Public Safety SME Forum is exciting- you’re in a room full of like-minded people who want to make a difference. 

What are your main hopes and expectations from the forum?

I’ve previously participated in techUK events where senior stakeholders from government departments have led open and honest conversations about gaps in their knowledge. It’s refreshing to see them hold their hands up and say ‘We need help and we want to hear from SMEs’.

I think it would be great to see more of this in the Security and Public Safety SME forum, with people not being afraid to ask for help and demonstrating a desire to make a change.

What are, in your opinion, the main challenges faced by the SME community in the security and public safety sectors?

One of the challenges we face as SMEs is that we have to be deliberate about the work we do. We might see an opportunity that we know we’re a good fit for, but before we can commit, we need to think about it more than just ‘do we fit the technical criteria?’ We need to think about how it’s going to affect wider aspects of the company – Do we have sufficient staffing? Do they need security clearance? What is the delivery timeline?

If we aren’t being intentional, we risk disrupting our current way of working. We have a loyal and happy customer base and an excellent team of engineers, developers, and PMs to manage and support them, but even if a brilliant data quality deal lands on our desk, if it would take an army to deliver it, we may not be able to commit the same resources that a big consultancy firm can and, ultimately, we may have to pass on it.  

Moreover, our expertise lies specifically in data quality. As a leading DQ vendor, we excel in this area. However, if a project requires both data quality and additional data management services, we may not be the most suitable candidate, despite being the best at delivering the data quality component.

What are your top 3 areas of focus that the forum should address?

Ultimately, I think the goal of this forum should be steered by asking the question ‘How do we make people feel safe’?

A big challenge is always going to be striking the balance between tackling the issues that affect people’s safety, whilst navigating those bigger ‘headline’ stories that can have a lasting effect on the public. For instance, if you google ‘Is the UK a safe place to live?’, largely speaking the answers will say that ‘yes, the UK is a very safe place to live’. However, people’s perceptions don’t always align with that. I remember reading an article last year about how public trust in police has fallen to the lowest levels ever, so I think that would be a good place to start.  

From a member’s perspective though, more selfishly, I’d like to get the following out of the forum – 

• Access to more SME opportunities 

• Greater partnership opportunities 

• More insights into procurement and access to the market 

In your opinion, why is networking and collaboration so important? Have you any success stories to share?

Our biggest success in networking and collaboration is having so many customers willing to endorse us and share our joint achievements.

We focus on understanding our customers, learning how they use our product, and listening to their likes and dislikes. This feedback shapes our roadmap and shows customers how much we value their input. This approach not only creates satisfied customers, but also turns them into advocates for our product. They mention us at conferences, in speeches, and in reference requests, and even help other customers with their data management strategies.

For us, networking is about more than just making new contacts; it’s about helping our customers connect and build relationships. Our customers’ advocacy is incredibly valuable because prospective customers like to hear success stories from them, perhaps more than salespeople.

About Datactics

Datactics specialises in data quality solutions for security and public safety. Using advanced data matching, cleansing, and validation, we help law enforcement and public safety agencies manage and analyse large datasets. This ensures critical information is accurate and accessible, improving response times, reducing errors, and protecting communities from threats.

For more information on how we support security and public safety services, visit our GovTech and Policing page, or reach out to us via our contact us page.

The post Insights from techUK’s Security and Public Safety SME Forum appeared first on Datactics.

Our quick ADQ in three minutes guide can be downloaded from the button below the graphic. Happy reading! As always, don’t hesitate to get in touch if you’re looking for an answer that you can’t find here. Simply hit ‘Contact us’ with your query and let us do the rest.

Wherever you are on your data journey, we have the expertise, the tooling and the guidance to help accelerate your data quality initiatives. From connecting to data sources, through rule building, measuring and into improving the quality of data your business relies on, let ADQ be your trusted partner.

If you would like to read some customer stories of how we’ve already achieved this, head on over to our Resources page where you’ll find a wide range of customer case studies, white papers, blogs and testimonials.

To get hold of this infographic, simply hit Download this! below.

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Belfast, Northern Ireland – 5th April, 2024 – Datactics, a leading provider of data quality and matching software, has been recognised in the 2024 Gartner Magic Quadrant for Augmented Data Quality Solutions for a third year running.  

Gartner included only 13 data quality vendors in the report, where Datactics is named a Niche Player. Datactics’ Augmented Data Quality platform (ADQ) offers a unified and user-friendly experience, optimising data quality management and improving operational efficiencies. By augmenting data quality processes with advanced AI and machine learning techniques, such as outlier detection, bulk remediation, and rule suggestion, Datactics serves customers across highly regulated industries, including financial services and government.

In an era where messy, unreliable and inaccurate data poses a substantial threat to organisations, the demand for data quality solutions has never been greater. Datactics stands out for its user-friendly, scalable, and highly efficient data quality solutions, designed to empower business users to manage and improve data quality seamlessly. Its solutions leverage AI and machine learning to automate complex data management tasks, thereby significantly enhancing operational efficiency and data-driven decision-making across various industries. 

“We are thrilled to be included in the 2024 Gartner Magic Quadrant for Augmented Data Quality Solutions,” said Stuart Harvey, CEO of Datactics. “Our team’s dedication and innovative approach is solving the complex challenges of practical data quality for customers across industries.

We believe the report significantly highlights our distinction from traditional observability solutions, showcasing Datactics’ focus on identifying, measuring and remediating broken data. We are committed to assisting our clients to create clean, ready-to-use data via the latest techniques in AI and have invested heavily in automation to reduce the manual effort required in rule building and management while retaining human-in-the-loop supervision. It is gratifying to note that Gartner recognises Datactics for its ability to execute and completeness of vision.”

Datactics’ solutions are designed to empower data leaders to trust their data for critical decision-making and regulatory compliance. For organisations looking to enhance their data quality and leverage the power of augmented data management, Datactics offers a proven platform that stands out for its ease of use, flexibility, and comprehensive support. 

Magic Quadrant reports are a culmination of rigorous, fact-based research in specific markets, providing a wide-angle view of the relative positions of the providers in markets where growth is high and provider differentiation is distinct. Providers are positioned into four quadrants: Leaders, Challengers, Visionaries and Niche Players. The research enables you to get the most from market analysis in alignment with your unique business and technology needs.

Gartner does not endorse any vendor, product or service depicted in its research publications and does not advise technology users to select only those vendors with the highest ratings or other designation. Gartner research publications consist of the opinions of Gartner’s research organization and should not be construed as statements of fact. Gartner disclaims all warranties, expressed or implied, with respect to this research, including any warranties of merchantability or fitness for a particular purpose.

GARTNER is a registered trademark and service mark of Gartner and Magic Quadrant is a registered trademark of Gartner, Inc. and/or its affiliates in the U.S. and internationally and are used herein with permission. All rights reserved.

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Tia Cheang, Director of IT Data and Information Services at Gallagher, recently delivered an interview with Tech-Exec magazine drawing from her knowledge and experience in shaping the future of the insurance industry at one of the world’s largest insurance brokers. You can read the article here.

Tia is also one of DataIQ’s Most Influential People In Data for 2024 (congratulations, Tia!). We took the opportunity to ask Tia a few questions of our own, building on some of the themes from the Tech-Exec interview.

In the article with Tech-Exec, you touched on your background, your drive and ambition, and what led you to your current role at Gallagher. What are you most passionate about in this new role?

In 2023, I started working at Gallagher after having an extensive career in data in both public and private sectors. This job was a logical next step for me, as it resonates with my longstanding interest in utilising data in creative ways to bring about beneficial outcomes. I was eager to manage a comprehensive data transformation at Gallagher to prepare for the future, aligning with my interests and expertise.

I am responsible for leading our data strategy and developing a strong data culture. We wish to capitalise on data as a route to innovation and strategic decision-making. Our organisation is therefore creating an environment where data plays a crucial role in our business operations, to allow us to acquire new clients and accomplish significant results rapidly. The role offers an exciting opportunity to combine my skills and lead positive changes in our thinking towards data and its role in the future of insurance.

The transition to making data an integral part of business operations is often challenging. How have you found the experience? 

At Gallagher, our current data infrastructure faces the typical challenges that arise when a firm is expanding. Our data warehouses collect data from many sources, which mirrors the diverse aspects of our brokerage activities. These encompass internal systems, such as customer relationship management (CRM), brokerage systems, and other business applications. We handle multiple data types in our data estate, ranging from structured numerical data to unstructured text. The vast majority of our estate is currently hosted on-premise using Microsoft SQL Server technology, however, we also manage various other departmental data platforms such as QlikView. 

“…we want data capabilities that provide flexibility and agility, to enable us to quickly react to new market opportunities.”

A key challenge we face is quickly incorporating new data sources obtained through our mergers and acquisitions activity. These problems affect our data management efforts in terms of migration, seamless data integration, maintaining data quality, and providing data accessibility. 
To overcome this, we want data capabilities that provide flexibility and agility, to enable us to quickly react to new market opportunities. Consequently, we are implementing a worldwide data transformation to update our data technology, processes, and skills to provide support for this initiative. This transformation will move Gallagher data to the cloud, using Snowflake to leverage the scalability and elasticity of the platform for advanced analytics. Having this flexibility gives us a major advantage, offering computational resources where and when they are required.

How does this technology strategy align with your data strategy, and how do you plan to ensure data governance and compliance while implementing these solutions, especially in a highly-regulated industry like insurance?

Gallagher’s data strategy aims to position us as the leader in the insurance sector. By integrating our chosen solutions within the Snowflake platform, we strive to establish a higher standard in data-driven decision-making. 

This strategy involves incorporating data management tools such as Collibra, CluedIn, and Datactics into our re-platforming efforts, with a focus on ensuring the compatibility and interoperability of each component. We are aligning each tool’s capabilities with Snowflake’s powerful data lake functionality with the support of our consulting partners to ensure that our set of tools function seamlessly within Snowflake’s environment.

“…we are contemplating upcoming AI and automation regulations and considering how to futureproof our products and approaches…”

We are meticulously navigating the waters of data governance and compliance. We carefully plan each stage to ensure that all components of our data governance comply with the industry regulations and legislation of the specific region. For example, we are contemplating upcoming AI and automation regulations and considering how to futureproof our products and approaches to comply with them.

The success of our programme requires cooperation across our different global regions, stakeholders, and partners. We are rethinking our data governance using a bottom-up approach tailored to the specific features of our global insurance industry. We review our documentation and test the methods we use to ensure they comply with regulations and maintain proper checks and balances. We seek to understand the operational aspects of a process in real-world scenarios and evaluate its feasibility and scalability.

Could you expand on your choice of multiple solutions for data management technology? What made you go this route over a one-stop shop for all technologies?

We have selected “best of breed” solutions for data quality, data lineage, and Master Data Management (MDM), based on a requirement for specialised, high-performance tools. We concentrated on high-quality enterprise solutions for easy integration with our current technologies. Our main priorities were security, scalability, usability, and compatibility with our infrastructure. 

By adopting this approach, we achieve enhanced specialisation and capabilities in each area, providing high-level performance. This strategy offers the necessary flexibility within the organisation to establish a unified data management ecosystem. This aligns with our strategic objectives, ensuring that our data management capability is scaleable, secure, and adaptable.

Regarding the technologies we have selected, Collibra increases data transparency through efficient cataloguing and clear lineage; CluedIn ensures consistent and reliable data across systems; and Datactics is critical for maintaining high-quality data. 

“As we venture into advanced analytics, the importance of our data quality increases.”

In Datactics’ case, it provides data cleansing tools that ensure the reliability and accuracy of our data, underpinning effective decision-making and strategic planning. The benefits of this are immense, enhancing operating efficiency, reducing errors, and enabling well-informed decisions. As we venture into advanced analytics, the importance of our data quality increases. Therefore, Datactics was one of the first technologies we started using.

We anticipate gaining substantial competitive advantages from our strategic investment, such as improved decision-making capabilities, operational efficiency, and greater customer insights for personalisation. Our ability to swiftly adapt to market changes is also boosted. Gallagher’s adoption of automation and AI technologies will also strengthen our position, ensuring we remain at the forefront of technological progress.

On Master Data Management (MDM), you referred to the importance of having dedicated technology for this purpose. How do you see MDM making a difference at Gallagher, and what approach are you taking?

Gallagher is deploying Master Data Management to provide a single customer view. We expect substantial improvements in operational efficiency and customer service when it is completed. This will improve processing efficiency by removing duplicate data and offering more comprehensive, actionable customer insights. These improvements will benefit the insurance brokerage business and will enable improved data monetisation and stronger compliance, eventually enhancing client experience and increasing operational efficiency.

Implementing MDM at Gallagher is foundational to our ability to enable global analytics and automation. To facilitate it, we need to create a unified, accurate, and accessible data environment. We plan to integrate MDM seamlessly with our existing data systems, leveraging tools like CluedIn to manage reference data efficiently. This approach ensures that our MDM solution supports our broader data strategy, enhancing our overall data architecture.

“By including data quality activities in our approach, we anticipate significant benefits from the MDM initiative.”

Data quality is crucial in Gallagher’s journey to achieve this, particularly in establishing a unified consumer view via MDM. Accurate and consistent data is essential for consolidating several client data sources into a master profile; we see it as essential, as without good data quality the benefits of our transformation will be reduced. By including data quality activities in our approach, we anticipate significant benefits from the MDM initiative. We foresee a marked improvement in data accuracy and consistency throughout all business units. We want to empower users across the organisation to make more informed, data-driven decisions to facilitate growth. Furthermore, a single source of truth enables us to streamline our operations, leading to greater efficiencies by removing manual processes. Essentially, this strategic MDM implementation transforms data into a valuable asset that drives innovation and growth for Gallagher.

Looking to the future of insurance, what challenges do you foresee in technology, data and the insurance market?

Keeping up with the fast speed of technology changes can be challenging. We are conducting horizon scanning on new technologies to detect emerging trends. We wish to include new tools and processes that will complement and improve our current systems as they become ready.

“We prioritise the security of our data assets and our clients’ privacy because it is essential for our reputation and confidence in the market.”

Next is ensuring robust data security and compliance, particularly when considering legislation changes about AI and data protection. Our approach is to continuously strengthen our data policies as we grow and proactively manage our data. We prioritise the security of our data assets and our clients’ privacy because it is essential for our reputation and confidence in the market.

Finally, we work closely with our technology partners to leverage their expertise. This collaborative approach ensures that we take advantage of new technologies to their maximum capacity while preserving the integrity and effectiveness of our current systems. 

Are there any other technologies or methodologies you are considering for improving data management in the future beyond what you have mentioned?

Beyond the technologies and strategies already mentioned, at Gallagher, we plan to align our data management practices with the principles outlined in DAMA/DMBOK (Data Management Body of Knowledge). This framework will ensure that our data management capabilities are not just technologically advanced but also adhere to the best practices and standards in the industry.

In addition to this, we are always on the lookout for emerging technologies and methodologies that could further enhance our data management. Whether it’s advancements in AI, machine learning, or new data governance frameworks, we are committed to exploring and adopting methodologies that can add value to our data management practices.

For more from Tia, you can find her on LinkedIn.

The post Shaping the Future of Insurance: Insights from Tia Cheang appeared first on Datactics.

Why does FSCS compliance matter?

HSBC Bank plc (HBEU) and HSBC UK Bank plc (HBUK)’s January 2024 fine, imposed by the Prudential Regulation Authority (PRA) for historic failures in deposit protection identification and notification, alongside the 2023 United States banking crisis, jointly serve as stark reminders of the importance of depositor protection regulation.

Both events, emblematic of the broader challenges faced by the banking sector, underscore the necessity of rigorous data governance and quality for FSCS compliance and depositor protection.

HSBC’s penalty, the second largest imposed by the PRA, highlights the consequences of inadequate data management practices, while the 2023 US banking crisis, characterised by the failure of three small-to-midsize banks, reveals the systemic risks posed by liquidity concerns and market instability.

These incidents draw attention not only to the pressing issues of today, but also to the enduring mechanisms put in place to safeguard financial stability. The Financial Services Compensation Scheme (FSCS), established in the United Kingdom, embodies such a mechanism, created to instil consumer confidence and prevent the domino effect of bank runs.

What is Single Customer View (SCV)?

The FSCS’s role becomes especially pivotal in times of uncertainty: if a bank collapses, the FSCS’s compensation mechanism needs to activate almost instantaneously to maintain this confidence.

According to the Prudential Regulation Authority (PRA) Rulebook (Section 12), firms are required to produce a Single Customer View (SCV) — a comprehensive record of eligible guaranteed deposits — within 24 hours of a bank’s failure or whenever the PRA or FSCS requests it.

This response, underscored by the accuracy and rapidity of depositor information, is a bulwark designed to avert a banking crisis by ensuring timely compensation for affected customers. Over time, as the FSCS has amplified depositor protection to cover up to £85,000 per individual, the 24-hour SCV mandate has marked a significant stride towards a more secure and robust financial sector, solidifying the foundation where depositor trust is paramount.

What data challenges does SCV pose?

When it comes to implementing the SCV regulation, the devil lies in the details. The demand for accuracy and consistency in depositor records translates into specific, often arduous, data quality challenges. Financial institutions must ensure that each depositor’s record is not only accurate but also aligned with SCV’s granular requirements:

Below are 5 data challenges associated with SCV:

• Identification and rectification of duplicated records– Duplication can occur due to disparate data entry points or legacy systems not communicating effectively.
• Lack of consistency across records– Customer details may have slight variations across different systems, such as misspelt names or outdated addresses, which can impede the quick identification of accounts under SCV mandates.
• Data timeliness– SCV necessitates that data be updated within a 24-hour window, requiring real-time (or near-real-time) processing capabilities. Legacy systems, often built on batch processing, may struggle to adapt to this requirement.
• Discrepancies in account status — determining if an account is active, dormant, or closed — must be resolved to prevent compensation delays or errors.
• Aggregating siloed data– the comprehensive nature of depositor information mandated by SCV involves aggregating data across multiple product lines, account types, and even geographical locations for international banks, a task that can be formidable given the legacy data structures and the diversity of regulatory environments.

The HSBC fine, in particular, underscores the ramifications of inaccurate risk categorisation under the depositor protection rules and the insufficiency of stress testing scenarios tailored to depositor data. Without robust data quality controls, banks risk misclassifying depositor coverage, which could potentially lead to regulatory sanctions and reputational damage.

Why integrate SCV with wider data strategies?

By incorporating meticulous data standards and validation processes as part of an enterprise strategy, banks can transform data management from a regulatory burden into a strategic asset.

The crux of effective depositor protection lies not just in adhering to SCV requirements, but in embracing a broader perspective on data governance and quality. This means positioning SCV not in isolation but as a critical component of a comprehensive account and customer-level data strategy.

To overcome these challenges, financial institutions must not only deploy advanced data governance and quality tooling but also foster a culture of data stewardship where data quality is an enterprise-wide responsibility and not one that is siloed within IT departments. By incorporating meticulous data standards and validation processes as part of an enterprise strategy, banks can transform data management from a regulatory burden into a strategic asset.

An enterprise approach involves:

• Unified Data Governance Frameworks: Establishing unified data governance frameworks that ensure data accuracy, consistency, and accessibility across the enterprise.

• Advanced Data Quality Measures: Implementing advanced data quality measures that address inaccuracies and inconsistencies head-on, ensuring that all customer data is up-to-date and reliable.

• Integration with Broader Business Objectives: Aligning SCV and other regulatory data requirements with broader business objectives, including risk management, customer experience enhancement, and operational efficiency.

• Leveraging Technology and Analytics: Employing cutting-edge technology and analytics to streamline data management processes, from data collection and integration to analysis and reporting.

How does Datactics support FSCS compliance?

The recent HSBC fine and the 2023 US banking crisis serve as critical catalysts for reflection on the role of depositor protection regulation and the imperative of a holistic data strategy.

FSCS regulatory reporting compliance underscores the evolution of depositor protection in response to financial crises, whilst the challenges presented by these regulations highlight the need for advanced data governance and quality measures.

At Datactics, we understand that the challenges posed by regulations like SCV indicate broader issues within data management and governance.

Our approach transcends the piecemeal addressing of regulatory requirements; instead, we advocate for and implement a comprehensive data strategy that integrates SCV within the wider context of account and customer-level data management.

Our solutions are designed to support regulatory compliance but also to bolster the overall data governance and quality framework of financial institutions.

We work closely with our clients to:

• Identify and Address Data Quality Issues: Through advanced analytics and machine learning, we pinpoint and rectify data quality issues, ensuring compliance and enhancing overall data integrity.

• Implement Robust Data Governance Practices: We help institutions establish and maintain robust data governance practices that align with both regulatory requirements and business goals.

• Foster a Culture of Data Excellence: Beyond technical solutions, we emphasise the importance of fostering a culture that values data accuracy, consistency, and transparency.

We are committed to helping our customers navigate FSCS compliance, not by addressing regulations in isolation but by integrating them into a broader, strategic and more sustainable framework of account and customer-level data management. By doing so, we ensure compliance and protection for depositors whilst paving the way for a more resilient, trustworthy, and efficient banking sector.

The post FSCS compliance: The Future of Depositor Protection appeared first on Datactics.