Insurance Data Analytics for Better Decision Making

1. Insurance Data Analytics for Better Decision Making

2. Introduction • Insurance Data Analytics Improving Decision-making • Managing Claims • Calculating Risk • Leveraging Customer Insights • Balancing Customer Acquisition and Profits • Conclusion 1 2 Table of Contents 3

3. Introduction Data is a gold mine for insurers to make capable decisions in the competitive industry. Insurance Data Analytics improves decision-making in crucial tasks like underwriting, premium calculation, and risk prediction. With the availability of Big Data, insurers need to leverage the right data into relevant insights. The solution for managing such a large volume of data and benefitting from it is Insurance Technology; therefore, insurers are increasingly considering partnerships with insurtechcompanies.

4. How? Insurance Data Analytics is improving decision-making for insurers.

5. Data Analytics Improving Decision-making • Managing • Claims Calculating Risk • Balancing Customer Acquisition and Profits • Leveraging Customer Insights

6. Managing Claims • With the use of insurtech in predictive analysis, frauds have been minimized to a remarkable low enhancing accuracy of insurance data analytics. • Identification of the applicants who are likely to commit fraud is easier for insurers by insurance technology and hence, claims auditing decisions would be more accurate.

7. Calculating Risk • Insurance data analytics works as a primary base for any policy-making by underwriters. • Data like one person’s address, area of residence, distance from a fire station, and even unstructured data of a person’s social media is crucial for insurance software to guide analytical decision making.

8. Leveraging Customer Insights • Morgan Stanley and BCG global customer survey reveal Insurance customers are in favor of digitalizing their insurance experience completely. • This can be possible by rightly predicting customer behavior with the acquisition of relevant data to suggest a customized insurance policy for customers as required.

9. Balancing Customer Acquisition and Profits • To enhance customer acquisition, insurers need to reduce cost but it will also reduce their profits. Therefore, with Insurance data analytics, insurers manage customer acquisition and profits hand in hand. • This is done by insurance technology solutions for running insurance processes with the wise help of analytical decision making.

10. Conclusion • Insurance data analytics empowers the insurance carriers to conduct an efficient analysis of data available and come out with the best possible decisions for every insurance task and process. • With the rising competition in the field, insurers trust insurance technology to guide their analytical decisions to not leave any scope for human error.

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