A cumbersome, paper-based underwriting processing system resulted in slow and inconsistent decisions. The processing logic was coded in COBOL and hard to change. This logic triggered more referrals to underwriters and therefore used up many hours of underwriter time. If a single application triggered multiple referral conditions, multiple referral reports were generated, causing delays and increased expense. External reports, such as motor vehicle reports, were always ordered, often more than once per application, because the manual process made it hard to keep track of reports ordered or their value to a decision.
A centralized decision service combined business rules with risk models implemented by predictive analytics. Business rules ensure that external data is brought into the decision-making process only when it makes a difference. This method speeds approvals, increases straight-through processing, and reduces costs. The decision service is used across multiple systems to ensure consistency and is offered to partners so that agents can write policies while a prospect is waiting, avoiding the need for them to return later. Quote counts and new business have increased because agents can write policies immediately.
The risk models are objective, which improves risk management and regulatory compliance, and changes to business rules can be made without IT involvement, resulting in improved agility and business control. This quantitative measure of risk serves as an objective standard for evaluating future performance and makes it possible to track results by agent, geographic region, or other criteria.
Benefits