How AI and Machine Learning Will Help with Distribution, Underwriting, Pricing, Claims

Artificial intelligence (AI) and machine learning are transformative tools for the insurance industry, allowing carriers and MGAs that use them to differentiate themselves. According to an Accenture report, those utilizing AI and machine learning to their full potential are leveraging data to drive faster and more personalized customer experiences, increasing claimant satisfaction, and generating significant efficiencies in insurance underwriting. However, many insurance companies are underutilizing the power of AI and machine learning and are not reaping the benefits these tools provide.

Artificial intelligence is the simulation of human intelligence processes by machines, especially computer systems. Machine learning is a branch of AI and computer science that uses data and algorithms to imitate how humans learn, gradually improving the accuracy of analytics and processes.

AI and Distribution

According to a McKinsey report, enough information about individual behavior is known, with AI algorithms creating risk profiles, that cycle times for purchasing automobile, commercial, or life insurance can be reduced to minutes. Auto and homeowners insurers have offered instant quotes for some time, but as telematics and in-home internet of things (IoT) devices proliferate and pricing algorithms mature, they will continue to improve their ability to issue policies immediately to a broader range of customers.

In addition, online behavior data can assist insurance agents, MGAs, and carriers in creating targeted marketing campaigns for customer acquisition.

AI and Underwriting, Pricing

A survey of underwriters conducted by Accenture for its AI research found that up to 40% of underwriters’ time is spent on non-core and administrative activities. Incorporating an AI underwriting solution and automation into underwriters’ workflow provides additional bandwidth for them to focus on risk evaluations of submissions. With machine learning, underwriters can swiftly sift through more abstract sources of information, such as Yelp reviews, social media postings, and SEC filings, assembling relevant data to assess the insurance carrier’s potential risk better, determine more accurate premiums, and write more profitable business.

Risk assessment supported by AI intelligence can also assist insurers and MGAs in better tailoring plans so that clients pay for only what they need. It can also reduce human error in the application process, increasing the likelihood that customers will receive programs customized to their specific needs.

AI and Claims

Claims evaluation can be a difficult and time-consuming process, but AI can help. Machine learning tools can quickly identify claim components and forecast potential costs. Commercial auto insurers, for example, can identify damage severity and repair costs through images, sensors, and historical data to help accelerate claims settlements. Both the insurer and the customer benefit as a result.

AI is essential to the insurance industry’s future for speed to market, improved efficiencies and risk assessments, accurate pricing, and enhanced customer satisfaction.