How this insurance company is unlocking the power of data scienceBorn as a digital native, IndiaFirst Life Insurance’s thought process, design, and implementation has been largely digital from its inception.

According to Sankaranarayanan R, Chief Technology, and Data Officer, IndiaFirst Life Insurance, the company was the first insurer to fully digitalize new business processes and made that available in Tab, that too in offline mode.

Currently, IndiaFirst Life Insurance is overcoming the challenge of crunching the time to market for integrating with the new-age distributors. To overcome this, an API Store has been implemented on the cloud which offers the ability to integrate with distributors of varied digital capabilities.

The company has recently created an Intelligent Data Hub for all Structured Data and is in the process of developing a streamlined repository of Unstructured Data (Voice, Text, Video, and other forms of communication Data).

“In addition to that and the various tools that we use like R & Python, we recently invested in IBM Watson to crunch the timelines to deploy the Models we develop. It’s also expected to help us in experimenting with more iterations across various Data Science Techniques within the same timeframe,” said Sankaranarayanan.

There is an internal team of data scientists who have been regularly churning out analytical models, both Predictive as well as Prescriptive.

“Our quest is to continuously try and identify any area where we can either impact the top-line or bottom-line, or help in faster & correct decision-making, or attain a quicker time-to-market using the power of data science”, he added.

The company’s analytical models kick in at each stage, right from Lead Generation, suggesting the right Product to the Customer, Predicting Sales, Hiring the right Candidates, Customer Retention, to having an Analytical Solution at each step of the journey.

“We have come up with various Personas, and currently, once the customer is onboarded, the Segmentation is carried out. We have plans to integrate this at an early stage in the Customer Life Cycle. Given these various Analytical Models right from Product Suitability, Lead Conversion, and Persona-based Segmentation, our next natural step is to implement Hyper-personalization in all relevant areas,” Sankaranarayanan maintained.

As of now, Hyper-personalised Communication Scripts for our Customers has been developed to optimize the retention efforts based on the Predictive Models

Talking about facing challenges while leveraging data analytics, Sankaranarayanan said that life insurance is a long-term contract but underwritten at a point of time (immediately after the sale) with the data that are received at that time.

“Given that various need-based products help a customer during their lifetime, it is important that the data reflects the recent aspects of the customer, so that we can help them with the right product. We face a challenge here in terms of upgrading the data”, he said.

The second challenge is an outcome of the constant war between convenience and the amount of data that is sought.

“All the data we seek is to help the customer with the right engagement, but at times convenience overtakes, and only the mandatory data that is needed for accepting the risk is provided. So, the right engagement with the customer becomes a challenge. The solution for this is data enrichment, which we constantly work on. With data enrichment comes various challenges like the source, trustworthiness and value of the enrichment comes into play. Irrespective of the challenges, it is a must for us.” Sankaranarayanan averred.





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