Why Data Quality for Insurers is Key to Compliance

Emily WashingtonJanuary 18, 2021

Case Study: How a Leading Insurer Leveraged Data Quality to Ensure Regulatory Compliance

Insurers navigate a slew of regulatory rules and laws. With so many regulations to manage, ensuring data quality for insurers is a top priority because penalties for non-compliance range from bad press to substantial fines. The span of fines, penalties and company damage depend on the type of insurance company you operate. For example, a large, multi-line insurer that provides auto, home, commercial and life insurance coverage must overcome numerous compliance challenges. A small, private insurer offering only life insurance is subject to fewer regulations but are equally challenging to manage.

Large insurers manage millions of policies across business lines and reconcile all premium inaccuracies in the general ledger. As a publicly held company, these business entities are subject to Sarbanes-Oxley (SOX). SOX requires insurers to establish extensive data quality controls for financial and accounting protocols, and enhanced security.

The National Association of Insurance Commissioners’ Model Audit Rule (NAIC MAR) closely aligns with SOX, ensuring both financial and accounting data is accurate, auditable and trustworthy. As a result, insurers face additional financial audit and reporting requirements. These regulations require businesses to establish uniform enterprise financial controls and ongoing reporting processes.

Minimizing Regulatory Compliance Risks

Insurance carriers large and small are increasingly working with third party and IoT data, insurtech providers along with internally distributed environments, raising the potential for compliance violation risks such as premium inaccuracies in the general ledger.

To solve data quality and regulatory challenges, insurers must track data lineage to establish an audit trail for data’s lifecycle and implement data quality and financial controls under a single data governance framework. Additionally, modern automation technologies help eliminate the reliance on manual quality controls within distributed environments. Manual controls are prone to human error, resulting in data inaccuracies and potentially concealed compliance issues.

By establishing a governance framework to standardize internal controls across a breadth of data environments, insurers leverage automated data lineage, providing end-to-end data quality monitoring and reconciliation rules, eliminating manual process inefficiencies and errors. Prioritizing data quality also provides auditability of financial practices and processes to detect and eradicate compliance, operational and reporting gaps.

Integrated data quality, data lineage and data governance also provides insurers with unprecedented transparency into data movement and quality metrics. Merging efforts empowers insurers to establish a data catalog with 3D data lineage.

3D lineage visualization capabilities helps insurers understand in context every detail on each financial calculation. As a result, insurers can quickly uncover the root cause of problems and build reports and workflows that alert data owners and stewards to potential inspection and resolution issues. Any reconciliation failures or potential integrity threats are identified and sent to the right resource. Insurers now ensure swift correction to avoid regulatory compliance fines, which is a considerable advantage in the insurance sector.

Recognizing the Importance of Data Quality and Data Catalogs for Insurance Companies

Overall, a comprehensive data catalog with 3D lineage provides insurers with end-to-end transparency and data quality. Subsequently, insurers not only benefit from their ability to trust their data, but also meet their compliance requirements to execute expedited audits, implement internal controls and provide accurate and timely financial reports.

With a unified framework, insurers are well-positioned to ensure data quality and ongoing compliance with revised, expanded or new regulations. This not only helps mitigate risk but minimizes costs and increases efficiencies.

Are you looking for additional information about data quality and regulatory compliance in the insurance industry? Check out this case study: https://www.infogix.com/resources/how-a-leading-insurer-leveraged-data-quality-to-ensure-regulatory-compliance/.

For additional resources on regulatory compliance, check out this article from Computer Weekly: https://www.computerweekly.com/feature/Top-four-compliance-considerations-for-SMEs.

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Case Study: How a Leading Insurer Leveraged Data Quality to Ensure Regulatory Compliance