Insuranceciooutlook

How does data analytics benefits insurers?

Insurance CIO Outlook | Thursday, January 19, 2023

An insurance company that can correctly predict the needs of prospective customers by looking through data trends and the complete view of a customer’s previous interactions with the brand has much more potential to make the sale than an insurance company just using conventional methods of selling

Fremont, CA: Insurance is a data-driven industry. Every day there are new players in the competition, and each one of them has a mine of data, but only the ones converting that data into useful insights and using them in their decision-making can make it a gold mine. According to the findings of a recent study, 86% of insurance companies are working on Insurance data analytics mechanisms for optimum predictions of big data reports. Insurance companies using data analytics solutions have witnessed significant improvements in decision-making underpinned by business intelligence to improve customer conversion. The key benefits offered by data analytics are:

Customer Acquisition and Personalization

Customer acquisition through a lead generation of high quality has become progressively tougher at a time when information is available at our fingertips and attention is fleeting. Even if you manage to capture the prospect’s attention, tracking different lead information from different sources can get tricky through paper and spreadsheet-based processes in place. 

Meaningful and Deeper Customer Engagement

Satisfied customers drive revenue and brand equity of businesses. Enhanced customer satisfaction is the result of initiatives on advocacy, referral marketing, and brand identity creation. If a business is successful in fulfilling customer expectations, it will automatically register accelerated and unprecedented growth. According to a McKinsey report, satisfied policyholders are 80% more likely to opt for policy renewals.

An insurance company that can correctly predict the needs of prospective customers by looking through data trends and the complete view of a customer’s previous interactions with the brand has much more potential to make the sale than an insurance company just using conventional methods of selling.

Mitigating Claims Fraud

Claims fraud continues to be a major challenge in the insurance sector. The Coalition of Insurance Fraud estimates that $80 billion is lost annually from fraudulent claims in the USA alone. Additionally, fraud makes up 5-10% of claims costs for insurers in the North American region. However, insurance companies using data analytics have seen considerable improvements in their fraud detection process. With the application of data analytics, insurance claims fraud detection becomes speedier and more accurate.

Predicting Accurate Risk for Underwriting

Underwriting is a complex task for insurers, and it can be simplified through insurance underwriting analytics. For example, the data trend would predict a higher auto insurance premium for a customer who has been engaged in rough driving than that for a customer whose data trend predicts a lesser risk profile. Such data can also come in handy during insurance claims automation as insurers can accelerate the policyholder’s journey from FNOL to recovery.

The application of advanced analytics in the insurance underwriting process encourages underwriters to concentrate on subjective tasks that call for judgment and intuitive decision-making while enabling systems to handle back-office 

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