Importance of Predictive Analytics in Insurance

1. Importance of Predictive Analytics in Insurance

2. Table of Contents 1 Introduction 2 Importance of Predictive Analytics • Risk Evaluation • Fraud Prediction • Enhanced Customer Services 3 Conclusion 2

3. Introduction As known, data is the centre of the insurance industry. Predictive Analytics provides insurers with the means to gather and process more data. It enables insurance businesses to utilize quality data for better risk mitigation, improved policy formation, timely fraud detection and improved customer satisfaction.

4. Benefits of Insurance Agency CRM Software • Fraud Prediction Risk Evaluation • Enhanced Customer Services

5. Risk Evaluation Predictive Analytics help insurers to accurately predict risk. It leads to accurate risk assessment and help determine policy premiums on which insurers’ losses or gains depend.

6. Fraud Prediction It assists in the timely detection of insurance fraud and false claims. It exposes suspicious claims, identifies risk via risk scoring and if necessary subject to further investigation.

7. Enhanced Customer Services Predictive Analytics in insuranceunderwriting provides insurers with a closer view of their data quality. It improves operational efficiencies and increases profitability.

8. Conclusion Predictive Analytics in insurance has enhanced decision-making power and enabled more automation in the industry. It has deliberately enhanced industry operations and improved business insights. It has empowered insurers and opened up fresh opportunities in insurance coverage and underwriting.

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