IAIS Presents Supervisory Considerations for Big Data Use in Insurance

The paper highlights a number of potential benefits and risks associated with the use of big data analytics across the insurance product life cycle. This information can help supervisors to develop appropriate and proportionate responses to rapid advancements in big data analytics enabling technologies and applications in a manner that ultimately promotes and encourages the consistent delivery of fair outcomes to customers. The paper focuses on the use of algorithms and advanced analytics capabilities by insurers to make decisions based on patterns, trends, and linkages and the availability to insurers of new data sources, collectively referred to as “big data analytics.” To help understand the potential benefits and risks of the use of big data analytics by insurers, the paper considers the new ways in which insurers are able to collect, process, and use data across various stages of the insurance product lifecycle, namely product design, marketing, sales and distribution, pricing and underwriting and claims handling. Finally, the paper highlights potential supervisory considerations on the use of big data analytics in insurance to ensure the fair treatment of customers as described in Insurance Core Principles (ICPs) 18 and 19.

The paper discusses the following key issues for insurance supervisors to consider:

• Opportunities may exist for supervisors to obtain insights from data collected and shared by insurers to assess the effectiveness of advice and suitability of products offered to customers. Supervisors could compare these insights with other metrics, such as complaints rates or product related key performance indicators to assess the effectiveness of advice and product suitability after products have been sold.
• As a starting point to address concerns about the increasing complexity of algorithms and potential lack of transparency in their development and use, supervisors may consider the applicability of existing requirements to the use of algorithms, including general principles relating to the management of risks taken by the insurer and the fair treatment of customers.
• Supervisors may consider the applicability of existing requirements to the use of algorithms, including general principles relating to the management of risks taken by the insurer and the fair treatment of customers. Additional issues that might require supervisory consideration in this respect include defining appropriate governance principles for the use of algorithms; focusing on measures implemented by insurers to ensure error and bias-free programming of algorithms to the extent reasonably possible; and reviewing the reliability of the algorithm, the accuracy and relevance of the specific data sets being used, and their correlation with the specific customer outcomes that are intended to be achieved.
• Third parties are often also used to provide ongoing support for various technical operational elements such as cloud services or other platforms, the design of algorithms, and provision or sourcing of large volumes of data not previously available to insurers. Supervisors may need to consider how insurers manage potential customer risks related to data sharing with these third parties, specifically in light of ICP 19.12. Supervisors may also consider the appropriateness of requiring insurers to extend their policies and procedures on the use of big data analytics to third party providers as part of their general governance arrangements for outsourcing where applicable. More active supervisory coordination and cooperation within and beyond the jurisdiction or region may be necessary to facilitate information exchange and to strengthen supervisory oversight in this regard.
• Supervisors should consider the steps taken by insurers to obtain the necessary consent to collect and use these types of data for specific purposes in a manner consistent with the fair treatment of customers. It would be useful for supervisors to collaborate with relevant data protection agencies, other consumer protection forums, and industry bodies in their respective jurisdictions to determine appropriate ways to mitigate potential customer risks arising from the use of big data analytics for insurance purposes. Developments relating to data and consumer protection frameworks globally may also provide helpful insights in this regard.

Keywords: International, Insurance, Big Data, Fintech, Suptech, Regtech, Artificial Intelligence, Machine Learning, Cloud Computing, Conduct Risk