Today, liability risk is a growing concern for the industry, especially in the face of complex emerging risks such as climate change. For liability (re)insurers the issue is not that their data is bad, but that it is often not in a form that today’s rapidly developing liability models can use effectively. Data has always been the underpinning of the insurance industry, from catastrophe modeling to reinsurance placement. In a hardening market, underwriting performance and pricing improvements are increasingly important and the enhanced data and analytical capabilities this data can unlock are key to making intelligent, informed risk management decisions.
But liability (re)insurers are increasingly realizing that they don’t have the capability to get their data model-ready. Underwriters capture a variety of information, for example, but it’s often inconsistent across lines of business and/or products. Having good (i.e., reliable, detailed, and complete), clean data is the first step to modeling risk but getting there can be challenging and/or costly.
Companies encumbered with legacy systems or that don’t have the internal digital talent to allocate to data cleansing/augmentation can license large databases from a variety of vendors. But this is an expensive option that still might not capture the specifics of the business units you’re concerned with. For companies looking for a more cost-effective solution, outsourcing data services can offer a more attractive and streamlined alternative.
Enter Arium, Verisk’s data-driven liability risk modeling solution. Arium’s portfolio modeling software provides a framework to measure enterprisewide liability risk, to monitor that risk over time, and to model loss. But Arium also offers API-driven data services that enable an enhanced view of risk. Our semi-automated process ensures that liability (re)insurers and brokers can retain control over their data while having it enhanced in a way that can help them obtain robust modeling results that can drive more informed decision-making. For example, Arium can help enhance liability and casualty exposure data by adding:
- The subsidiaries of named insureds facilitated by the Dunn and Bradstreet corporate hierarchy structure that provides a more comprehensive view of portfolio exposure
- Size metrics (such as employee count and revenue) that add value to policy data by providing exposure details (especially important in liability where understanding who has the “deep pockets” can be critical)
- Information on industry classifications using federal North American Industry Classification System (NAICS) codes that describe specific industries within which insureds operate to facilitate identifying areas of clash
- Coding for the many lines of business that are included within the liability space
A recent article by Sachin Kulkarni in the Insurance Journal highlighted “practical and pragmatic concerns around business disruption, the high cost of upgrading legacy systems, organizational inertia, and a general lack of in-house digital talent.” It concludes by noting that these issues “can be addressed effectively by building a robust data strategy that is closely aligned with the organization’s business objectives and data maturity, and turning strategy into action by onboarding a data-driven, insurance-focused technology partner.” Arium can be that partner and help take (re)insurers and brokers toward a deep understanding of the underlying risk in their liability (re)insurance portfolio—helping turn it from a relative unknown to a valuable asset.