Data and analytics play a critical role in insurance sales and distribution, underwriting, fraud prevention, and claims management. Predictive analytics uses data & statistical algorithms to forecast behaviour and continues to disrupt the insurance sector.
Predictive analytics helps insurance companies get deeper customer insight, enabling them to create tailored financial products. It also helps insurers uncover potential revenue opportunities, while proactively reducing risks and losses.
In the event of an emergency, weather data and analytics can help mitigate weather-related losses, plan for resource demands and more effectively manage cash reserves. Predictive analytics can help avert damage with real-time insight into weather conditions.
Predictive analytics can also map trends to keep the organisation ahead of the market when predicting risk. With sensors on wearables, cars and buildings, insurers now have access to even more data such as driving behavior and accurately assess risk and potentially fraudulent activities.
With predictive analytics, insurers can get the most out of valuable data and shift the focus from collecting insurance premiums to providing new services.
Considering the role data plays in fraud prevention, insurance companies need to have powerful analytics that help their data experts to derive critical insights and make informed decisions.
Please follow this link to see the infographic – Insurers: Use predictive analytics to deliver business results
Disclaimer: This infographic has been designed by IBM.