India's largest platform and marketplace for GCC & AI leaders and professionals

Sign in

India's largest platform and marketplace for GCC & AI leaders and professionals

3AI Digital Library

Minimizing Policy Attrition

3AI August 16, 2020

Leading Life Insurance Company In Japan

Problem Statement

  • A high attrition in the customer base due to competition and miss-selling (45% is overall lapse rate)
  • Expectation was to build an approach to retain policies and to set up an early warning system to identify a potential attrition cases to prevent further revenue leakage

Analytics Led Approach

  • Attrition trends in the data over the years were analyzed and an approach was designed to provide a solution to contain further revenue leakage
  • Predictive attrition model was built to predict the propensity of policies to attrite
  • Given are high level process steps which were followed :
    • Data Load Exploration
    • Model variable Creation
    • Analytical Model Development
    • Business rules

Business Impact

  • Raw data was mined, and a methodology was built for developing a predictive attrition model to provide a probability score to influence the decisions to follow the case by the customer.
  • Model output was segmented to optimize the approach to follow the case and provided insights to treat each policy based on the segmented matrix Re-evaluate;Retain;Grow;Protect– for example, Retain is the quadrant high value and high risky policy, retaining such policies will optimize the effort as well as cost
  • Primary users, retention team were provided with insights for customer retention..

Critical Success Factors

  • 20% of the in-force portfolio has been identified with 69% of the premium to be at risk of attrition (Approx. $ 1.3 BN premium at risk)
  • Formulated a growth strategy to retain existing customers as well as grow their business
  • Integrated attrition prediction with every customer touch point system through a web service

    3AI Trending Articles

  • Generating powerful learning experiences!

    Featured Article: Author: Amita Mirajkar, EXL As technology permeates every aspect of our lives, the education sector stands on the verge of a transformative change, courtesy Generative AI. Last few months, we have seen a surge of concern across institutions of higher learning as Generative AI programs, such as ChatGPT, gain popularity. According to MarketResearch, Generative […]

  • The Evolution of Generative AI and Human Creativity: Ethical Concerns and Future Perspectives

    Featured Article Author: Bhabani Chatterjee, Capgemini Invent Generative AI revolutionized notions of creativity — in manufacturing, product design, content creation, and problem-solving across various domains. These advancements not only push human invention further but also open up a new world for enterprises and individuals. Of course, ethical implications abound, but the excitement is undeniable. The […]

  • POV: Executive’s guide to build GenAI COE Effectively

    Featured Article Author: Mausam Deb (Healthcare & Life Science – AI Leadership Consultant) Generative AI (aka LLM) is no less than a rage for the last few years. The democratization of technology achieved by OpenAI through its GPT-3.5 model is remarkable. Market size of GenAI is growing in leaps and bounds. Every company in the […]

  • AI is changing the way doctors think about providing care

    While robots and computers will probably never completely replace doctors and nurses, machine learning/deep learning and AI are transforming the healthcare industry, improving outcomes, and changing the way doctors think about providing care. Machine learning is improving diagnostics, predicting outcomes, and just beginning to scratch the surface of personalized care. Imagine walking in to see […]