Insurers are often hindered by issues with their conventional underwriting processes that lead to lower bind rates and higher operational costs. Some of the pain points include:
- A time-consuming and labor-intensive process of verifying application information
- Inaccurate information from customers/agents leading to premium leakage and poor claims experience
- Extremely iterative and cumbersome process leading to poor customer satisfaction
UWSmartFill, Tiger Analytics’ AI-powered underwriting data prefill solution, is built to meet your unique requirements. It leverages external data sources to prefill applications and ensures a high fill rate at top speed. Our machine learning classifiers help you predict underwriting questions even where the data is not directly available from external data stores.
Insurers are often hindered by issues with their conventional underwriting processes that lead to lower bind rates and higher operational costs. Some of the pain points include:
- A time-consuming and labor-intensive process of verifying application information
- Inaccurate information from customers/agents leading to premium leakage and poor claims experience
- Extremely iterative and cumbersome process leading to poor customer satisfaction
UWSmartFill, Tiger Analytics’ AI-powered underwriting data prefill solution, is built to meet your unique requirements. It leverages external data sources to prefill applications and ensures a high fill rate at top speed. Our machine learning classifiers help you predict underwriting questions even where the data is not directly available from external data stores.
