Use Cases for RPA in Insurance Industry

Use Cases for RPA in the Insurance Industry

RPA Implementation, based on business rules can make decisions consistently and accurately all the time. Standardized and automated processes result in a reduction in processing costs and FTE. Most companies can achieve an ROI within 6 months of their investment. RCA can lead to increased personalization by being able to virtualize the underwriting process to a large extent. This can help reach a wider customer base. RPA in Insurance has already helped leading insurance companies to create a unified customer profile that can aid customer calls intelligently.


Policy Administration & Compliance Reporting

AURO RPA Virtual Enterprise Workforce ensures end-to-end policy data administration and upkeep so your staff put customer-care first without having to worry about Compliance Reporting as digital workers manage automated compliance reporting for the PRA.


By using machine learning and artificial intelligence, a scalable underwriting decision engine can be built. The system can learn from historical transactions and automate underwriting decisions.

Claims management

Virtual Enterprise Workers manage and process claims by referencing policy entitlements, straight through resolutions, approvals, and escalations as per the configured rules. Automation of processings of insurance policies following notification of death helps your staff to focus on the human touch much needed in times of the loss.

Market and Competitive analysis

Realign labor-intensive activities of market positioning, offers aggregation and competitor analysis to be performed by your virtual enterprise workers so you can concentrate on market differentiation strategy.

Case Study


productivity gains


For policy migration process, consolidation of an insurer’s set of policy books, spread across tens of legacy systems with high support costs and an error-prone and unintuitive operational overhead, requiring continued training for staff was required.


Automation of the policy migration process comprised of tens of systems and numerous policy books, all with different data formats, historical context and data conventions /shorthands interfacing. Also, cleansing of data on the move, by cross-referencing against external systems.