Automated underwriting in insurance

With RPA, machine learning (ML) and artificial intelligence (AI), you can reduce processing time by eliminating repetitive manual tasks, creating a visible impact on response time for quotes and the issuance of policies.

Digitization of data from different sources and AI evaluation are giving rise to big data and predictive analysis. RPA bots can search hundreds of data sources per potential policy, examining in seconds what would take manual underwriting much longer to cover in order to pinpoint an applicant's risk factors.

Aggregate and integrate data from disparate sources, from paper documentation to multiple legacy and API-based digital systems using automated processes. For example, Automation Co-Pilot makes it possible for underwriters to log in to various systems from a single screen, reducing complexity and enabling better time management.

Check each policy against underwriting guidelines and receive instant alerts when something doesn’t match. Using RPA, you will miss fewer potential risks when evaluating an applicant for risk and policy offerings.

By automating the simpler tasks, employees gain time and resources for higher yield areas with more value. Actions like tailoring individual policies, or pricing and managing “mid-risk” applications, are able to move front and center.

With Automation 360, Automation Co-Pilot, Document Automation and other RPA support, your call center representatives can have unified policyholder data across the organization in real-time. Many customer requests, such as updating their policy, can be automatically handled through machine learning (ML), intelligent software bots.