ICICI Prudential Life Insurance CFO Dhiren Salian discusses the role of Data Analytics

Harnessing Advanced Data Analytics for Compliance Risk Management and Personalized Customer Solutions: Insights from ICICI Prudential Life Insurance CFO, Dhiren Salian.

In a rapidly evolving insurance industry, data analytics has emerged as a crucial tool for managing compliance risks and delivering personalized solutions to customers. Dhiren Salian, CFO of ICICI Prudential Life Insurance, sheds light on the significant role that data analytics plays in these areas. Through advanced data analytics systems, ICICI Prudential Life Insurance gains valuable insights, enabling quick decision-making and effective risk management strategies. Moreover, leveraging data science and technology empowers the company to analyze various customer factors and develop personalized insurance products, pricing models, and marketing strategies. Join us as we delve into the insights shared by Dhiren Salian, highlighting the impact of data analytics in managing compliance risks and creating tailored experiences for customers.

What is the role of Data Analytics in managing compliance risks better?

Advanced data and predictive analytics systems are a great aid to the insurance industry as they provide sharp insights and enable quick business decision making. By leveraging data analytics, we are better equipped to assess and mitigate compliance risks. It facilitates analysis of historical data, market trends and risk indicators thereby enabling us to detect patterns, anticipate risks and develop effective risk management strategies.

How are you leveraging data analytics to build personalised solutions for customers?

We have been leveraging data science and technology to ensure that our customers are on course to achieve their long-term financial goals. A variety of machine learning models have been deployed to enable us to analyse multiple factors such as customer demographics, behaviour, preferences, risk profiles and household data. These insights allow us to develop insurance products, pricing models and marketing strategies.

For instance, the deployment of advanced machine learning models has enabled the Company to improve persistency across all cohorts. We have seen improvement in the 13^th month persistency ratio of the Company from 81% at March 2020 to 85% at March 2023. Similarly, the 61^st month persistency ratio improved from 50% at March 2020 to 66% at March 2023.

Data analytics is aiding us in understanding customer challenges and has enabled us to offer a virtually paperless and hassle-free onboarding experience for certain pre-selected segments of customers .

What future innovations can be seen in the field of data science & analytics in the next two years?

We believe data science and analytics will continue to play a vital role in underwriting. Advanced predictive modelling techniques using deep learning & natural language processing combined with extensive data sources, such as electronic health records, wearables, and genetic information, will enable more accurate risk assessment and personalised and faster underwriting decisions.

Insurers will leverage customer data, including past interactions, preferences and feedback to provide customised recommendations, streamlined application processes, and faster claims settlement. Chatbots and virtual assistants powered by data analytics will play a significant role in delivering personalised customer support and guidance.