Predict policy level lapses for insurance provider

Client

Leading South East Asia-based insurance provider catering to small and medium businesses.

OPPORTUNITY

The client wanted to develop a model to predict lapses at the policy level. The aim of the model was creating cost-effective interventions to target high-value customers with high likelihood of lapse.

SOLUTION

SG Analytics decided to design a classification model to predict the probability of lapse, using the following approach:
  • We created a data mart that combined demographic data with policy characteristics.
  • Our data scientists developed a logistic model to predict the probability of a customer lapse on premium payments using variables such as age, gender, marital status, income, household size, mode of payment, payment frequency, timeliness of payment, etc.
  • The team also designed other models based on Kernel-based SVM Regression and Tree-based Regression techniques.
  • Finally, we calculated the lifetime value index for all the customers. Based on the lifetime value, we identified the customers that should be targeted for business growth.

VALUE DELIVERED

►
1
Achieved 85% accuracy on unseen data, with an MCC score of 71.
►
2
Reduced probability of lapsing from 16% to 7%.
 

DOWNLOAD WHITEPAPER



*By sharing the information you have entered, you give your express consent to SG Analytics to use the provided information to contact you with relevant information related to its offerings and services as and when required. SG Analytics secures all your personal information from unauthorized access, use or disclosure. For more information, please visit our privacy policy.

DOWNLOAD Case Study



*By sharing the information you have entered, you give your express consent to SG Analytics to use the provided information to contact you with relevant information related to its offerings and services as and when required. SG Analytics secures all your personal information from unauthorized access, use or disclosure. For more information, please visit our privacy policy.

DOWNLOAD



DOWNLOAD



ISOISO
GDPA