OCTAVE Lapse Prevention – Solving for Union Assurance’s policy lapsation, by predicting likelihood of policies lapsing

High policy lapsation is observed in the insurance industry accounting to a significant premium loss to the insurance company. Lapse rate can be as high as 50% during the first year of the policy period at. Lapsed policies are likely to turn out to be churn policies if proper customer interventions are not executed.

Objective of lapse prevention use case is to prevent churn by proactively identifying and intervening with customers who are likely to churn. Advanced analytics model predicts the likelihood of the policy lapses in the next 6 months and recommend retention interventions based on customer types and account types

Predictive modelling: 40+ features in different domains including policy information, payment history and customer information are fed into the advanced analytics model to predict the likelihood of a customer to "Lapse and stay Lapsed" in the next 6 months. Model prediction scores are used in each month to rank all policies by risk of churn.

Prioritized lapse outreach: The score is used to reach out to high-to-medium premium value and churn risk customers using prioritized outreach strategy to reduce initial lapsation.

Using modeling insights and intervention strategies, ~20-30% reduction in the churn rate can be achieved by the use case. This can be translated to the saving on loss premium collection to determine the financial impact of the use case.