Predictive insurance analytics uses techniques like data mining, machine learning, AI etc. to comprehend a variety of data and bring out trends and insights that are critical for an insurance business. Whether it is claims, underwriting or customer retention, insurers are now applying predictive analytics to become more efficient and accurate. Here are top three use cases of predictive insurance analytics.
One of the most important uses of predictive insurance analytics is risk assessment. Data from multiple applications and devices (in-vehicle devices, IoT devices, wearables etc.) is analysed to predict different types of risks for policy holders. Since the level of risk has a direct impact on the premium, it is very important for insurers to calculate the risk accurately.
For example, in the case of vehicle insurance, predictive analytics help in determining the risk posed by policy holders of a certain age group, area etc. and this helps them to create a competitive, yet profitable premium.
Fraud insurance claims cause a big dent in the revenue of insurance companies every year. By applying predictive insurance analytics, insurers are able to flag suspicious cases and trigger automated actions to halt the claim process. The system dives through historical data to identify behavioural patterns that point to suspected fraud and trigger the next actions automatically.
Using predictive analytics, insurers analyse the data gathered from various customer interaction platforms, call centers, social media etc. to profile customers and categorize them into different buckets. This helps them to offer personalized solutions basis customer behaviour and past interactions. They are also able to ascertain which customers are happy and which customers are likely to exit in the near future. Insurers are able to customize their marketing and customer service processes using the insights from predictive analytics. They are able to understand their customer in details and deliver a great experience to different customer types.
Undoubtedly, predictive insurance analytics is empowering insurers to enrich customer experience, innovate marketing, improve risk management and make better strategic decisions.