AI insights fuel accelerated underwriting
Determined to revamp its operations, the reinsurer's leadership team started a complete digital transformation of systems and processes. The focus was to explore how advanced analytics, data science, and machine learning could support faster and more informed decisions.
Genpact was the chosen partner for this initiative because of our data, analytics, and digital expertise, and our track record of reimagining thousands of operations in the insurance industry.
So, we jumped into action. First, we developed a blueprint to get to a cloud-based infrastructure that would support the data needed for ML. We then connected data across multiple systems into one data pipeline. This approach allowed us to design two AI-driven risk prediction models based on the company's historical risk data:
- Model 1 predicts the likelihood of risk falling within the reinsurer's underwriting remit
- Model 2 predicts the likelihood that these risks will remain with the ceding carrier
Our AI experts then developed a data pipeline integrating new and varied data sources. This approach enhanced the risk prediction models with diverse datasets to continuously improve their accuracy. Plus, the system saves all the different versions of the models so the reinsurer has a repository of ML models they can test or deploy at any time in the future.
Finally, we added the ability for underwriters to add case-specific information without affecting underlying algorithms. Viewing the output of the AI models through a user-friendly dashboard, underwriters can input their feedback, which aids in continuous machine learning and in refining predictive outcomes.
What's more, they have a complete and transparent view of the data that feeds these models to build trust in the insights the ML models provide, which, in turn, boosts user adoption.