Boosting Risk Assessment Accuracy by 35%: How Machine Learning Cut Claim Rates and Operational Costs for a Manila-Based Insurer
Challenges
An insurance company based in Manila was struggling with outdated risk assessment models, which led to inaccurate pricing, higher claim rates, and increased operational costs. The manual risk assessment processes were slow and prone to errors, impacting the company’s profitability.
Need Assessments
The company needed a data science solution to develop advanced risk assessment models using machine learning and predictive analytics. The goal was to improve the accuracy of risk assessments by 30% and reduce claim rates by 15%, enhancing profitability and operational efficiency.
Solution
Omnilab Enterprise Solutions implemented a data science solution that involved developing and deploying machine learning models to analyze historical claim data and predict risk more accurately.
The new models increased the accuracy of risk assessments by 35% and reduced claim rates by 18%. The company also experienced a 20% reduction in operational costs due to more efficient risk management and pricing strategies.
