Data Analytics in the Insurance Industry

Data analytics is at work every time Amazon tells a customer he or she may want to buy a product, each time Facebook recommends a resource page, and when a life insurance company assesses risk and set rates for potential policyholders. It’s an area governed by layers of laws and rules that are impacting the highly regulated insurance industry in a significant way.

THIS ARTICLE PROVIDES PRACTICAL GUIDANCE FOR ATTORNEYS on managing data analytics in the insurance industry. It focuses on data related to complaints, claims, call centers, privacy, and security. Rules and regulations on how companies need to keep specific types of data are also discussed.

Rules and Regulations

The Health Insurance Portability and Accountability Act, the New York Department of Financial Services Rule Cyber Security Rule, and the General Data Protection Regulation speak to an insurer’s obligation to make sure that data is protected from cybersecurity threats and that breaches of data are properly and timely reported. Specific types of data that are governed by these rules include protected health information (PHI), personally identifiable information (PII), and personal financial information (PFI). These rules and regulations do not speak to the collection of data or how an insurer may use the data.

Although legislators and regulators have addressed these issues, they are beyond the scope of this article. Insurance companies analyze their data and look for ways to provide a better customer service experience, streamline processes, create efficiencies, reduce claims and complaints, and detect and reduce fraud.

A consistent, repeatable process should be outlined and defined to clearly articulate the process for collecting data and to help ensure data that is collected may be accurately measured, analyzed, and assessed. If all employees charged with collecting and reporting on data are not following the same process and data is not collected on a regular basis and for a specified period of time (e.g., quarterly or monthly), then measuring and analyzing the data will not work. Specificity, clear definitions, and a consistent, repeatable process are imperative.

To read the full practice note in Lexis Practice Advisor, follow this link.

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