What if insurers could make better and faster decisions about policies, underwriting and pricing?
A global insurer sought to make more informed and timely business decisions surrounding policy conditions, underwriting practices, and pricing strategies. They struggled to access data and analytics, and it was tedious when they could.
We developed a real-time risk analytics and pricing solution with predictive AI modeling, allowing the insurer to make timely and data-driven decisions. The solution uses machine learning to model risk and expected losses and provides risk-based pricing with dynamic assumption settings. The platform provides real-time reporting and tracking of exposure, risk, expected losses, and overdue debtors.
The insurer’s modelling and pricing tool is a user-facing platform with a dashboard interface. It’s used by various teams to quantify, manage, and report on risk. Primarily, the tool is used by two groups: underwriters to help make data-driven decisions when underwriting and pricing risks; and management to access real-time reporting and intelligence.
The underlying data is pulled directly from the data warehouse, and relevant custom calculations and models display the desired outputs. The platform features:
“The speed at which they understood our problems and created tangible solutions was impressive. The tool was effectively built over three months […]. The use was immediate and required only limited fine-tuning thereafter.”