Predictive Risk Analytics

Better life and health insurance with higher approval and lower risk.

Power underwriting decisions for speed and reliability
― with predictive risk analytics under the hood.

Unlock predictive insights from new digital data sources

Optimize underwriting with an instant and accurate assessment of an individual’s health status ― without a medical exam.

Improve sales conversions with faster underwriting decisions

Offer instant coverage to customers with pre-qualified health scores.

Increase underwriting approval without raising risk

Stratify risks with more clarity and granularity to identify healthy customers across all groups ― even those with pre-existing conditions.

See how Lydia powers underwriting decisions.

Pre-underwriting

HOW

Save time on non-approvals and help customers apply confidently with tailored products and coverage recommendations.

Who

Both agents and customers save time in choosing the right insurance products. Agents see higher sales conversions in this improved and accelerated qualifying process.

Accelerated underwriting

HOW

Accurately assess risk and safely offer fluidless underwriting to AI-qualified customers for instant coverage without a medical exam.

Who

Minimizing the hassle of medical exams improves both customer experience and satisfaction, while agents experience much less administrative work to close deals.

Relaxed underwriting

HOW

Confidently identify healthy people to insure within groups typically rejected or over-priced by the traditional underwriting rules.

Who

Previously rejected or out-priced customers can now access and afford insurance. It means Lydia-powered insurers can sustainably serve customers whom their competitors cannot.

+80%

decision alignment between Lydia AI and human underwriters

Using machine learning models to accelerate underwriting decisions is a major trend; however, there has not been an established industry best-standard practice for how to validate its use in underwriting. [Lydia and Taiwan Life] worked together to develop a methodology to translate machine learning predictive output results into data-driven reference markers that are compatible with use by actuaries and underwriters.

Max Ang
Celent APAC Insurance Technology Research Leader

80%

of cases being underwritten and completed in less than 7 days with Lydia

Get in touch

And get ready to reimagine your business with Lydia