Making insurance companies more effective and profitable, and customers happier

This motor may be beyond repair, but AI's impact on the insurance industry is just getting started. Applications include models to rapidly and efficiently assess car damage

Deep learning has the potential to impact many parts of the insurance industry, from customer-facing processes to risk assessment to backend processes. Ultimately, deep learning and AI will make insurance companies more effective and profitable — and a better fit for customers.

How to harness the complexity of data science in insurance

With its inherently complex processes and an abundance of data, insurance is an industry ripe for AI and deep learning. In fact, there are a range of areas where deep learning can create vast improvement in insurance processes and the customer experience.

For instance, embedding AI into the claims process can lead to significant improvement in customer service while reducing cost and time for companies. The ability to wield data for better understanding of customer sentiment and experience is priceless. And AI can even be used to take the inherent bias out of insurance pricing and give customers more fair and appropriate prices.

Deep learning and AI can also help with risk assessment, automatically flagging unusual or fraudulent activity. And with the ability to apply deep learning’s pattern recognition to language and images, companies can improve pricing processes for both personal and commercial insurance products.

Peltarion has expertise in the insurance sector. The Peltarion Platform is set up to support deep learning methods, operationalize AI and enable non-experts to both understand and apply the deep learning process.

AI and its related technologies will have a seismic impact on all aspects of the insurance industry

McKinsey

02/ Read about the use case methods within insurance