The need for faster, more flexible rule development is driven by a convergence of pressures across the underwriting ecosystem. Insurers are incorporating new and increasingly complex data sources, such as electronic health records (EHRs), each requiring new logic to interpret and assess effectively. Without robust rules, the value of these data sources is difficult to fully realize and incorporate into underwriting workflows.
At the same time, underwriting manuals are typically written in narrative form based on medical literature and must be translated into structured logic that automated systems can execute. The translation process is highly manual and resource-intensive, often resulting in bottlenecks in rule creation. Furthermore, as new medical research emerges, underwriting guidelines evolve, and manuals must be updated. As medical guidance changes, rules must also be revisited and refined, contributing to rule development workloads.
Each new data source or use case drives the creation of additional rule sets, often managed by small teams or individual experts. As a result, insurers need more rules, across more inputs, at greater speed – but the traditional development process remains difficult to scale.