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Pooja Thayyil

Pooja Thayyil

Pooja is a part of the data sciences team, and is involved in predictive modeling and research on machine learning algorithms and metrics. She has done her graduation from St. Xavier’s College with Economics & Statistics with Distinction and also has a Masters Degree in Economics from the University of Mumbai.

Recent Posts:

4 Stages of Predictive Modeling and How Business Aspects Influence Them

The first step in predictive modeling is defining the problem. Once done, historical data is identified, and the analytics team can now begin the actual work of model development. In this blog, we touch on the business factors that influence model development. If you find this interesting and want a deeper dive, you’ll have the opportunity to download our whitepaper that goes into more detail on this topic.

    Related Posts

    Data and Innovation: 2 Sides of the Same Coin

    As we set our feet in 2023, having experienced a roller-coaster ride last year thanks to the geopolitical tensions and some lingering rub-off effects of COVID-19, it drives home that "change is the only constant." Like any other industry, insurance is undergoing paradigm changes at different levels, whether recruiting potential candidates or customer onboarding, to name a few. However, a common thread that ties the myriad business functions of an insurance company has been data and innovation. There has been an ever-increasing need for insurance providers to use data and embrace innovation in their routine activities, eventually to stand the cut-throat competition.

    Intelligent Risk Assessment in Insurance

    Risk Management is a core function within the insurance industry. It is a vital responsibility of the underwriting team. Insurance companies collect data scattered across different business units in various formats – some of which are paper and digital, most of which are typically unstructured. The underwriting team doesn't have immediate access to the information required for internal and external decision-making, resulting in delays in making decisions and costly mistakes.

    Why Does the Long-term Nature of Life Insurance Products Make Customer Retention Difficult?

    Most insurers offer similar products and services, which makes it challenging to attract new customers and retain them. As an industry, insurance is low-touch, and insurers seldom interact with their customers. A report shows that the top companies have an average customer retention rate of 93 - 95 percent, while insurance companies have an average of 84 percent.