What should Insurers do next in the age of AI?

The insurance industry has always been data-driven, relying on extensive information and analytics to assess risks and make decisions. With the rise of Artificial Intelligence (AI), the industry is seeing a significant transformation in the way insurance companies operate. AI has enabled insurers to automate processes, improve customer experiences, and reduce costs. In this blog, I write about some of the key AI use cases in the insurance industry and the impact of AI on the industry roles.

 

When we talk about Insurance & AI, the key obvious use cases which come to mind are:

  1. Fraud Detection: Insurance fraud is a significant problem for the insurance industry, costing billions of dollars every year. AI can help identify fraudulent claims by analysing patterns in data and identifying anomalies. AI models can also learn from past fraud cases and improve their accuracy over time.
  2. Risk Assessment: AI can help insurers assess risk more accurately by analysing data from various sources such as social media, credit scores, and driving behavior. This data can help insurers make more informed decisions and provide personalised insurance policies for customers.
  3. Service Chatbots: AI-powered chatbots can provide customers with quick and efficient support, reducing the need for human customer service representatives. Chatbots can answer customer queries, provide quotes, and even assist with claims processing.
  4. Underwriting: AI can help automate the underwriting process by analysing data and providing insights into the risk profile of a customer. This can help insurers make more informed decisions and provide policies that are tailored to individual needs.
  5. Predictive Maintenance: AI can help insurers predict when equipment such as vehicles or machinery is likely to fail. This can help insurers schedule maintenance proactively and reduce the risk of claims.

 

Asides from the obvious use cases, a few outlier use cases which can really move the needle for both insurance companies & their customers are hidden in plain sight. Use cases in the area of distribution especially lead generation to conversion cycle and financial needs analysis are among the list of powerful use cases which benefits companies with additional revenue streams while enriching customer’s experience. Comprehensive Health Offerings can also change the paradigm of Health Insurance industry with companies being able to manage & reduce their Claims Loss Ratios by proactively assessing and managing customer health, all of this would not have been possible without AI solutions.

 

Impact of AI on Industry roles:

While AI has the potential to transform the insurance industry, it also has the potential to displace people from their jobs – and it is not a matter of if but when for AI solutions to become embedded in businesses. Many of the tasks that AI can perform, such as data analysis and customer support, are currently performed by humans. As AI becomes more prevalent, these jobs may become redundant, and people may need to re-skill themselves to stay relevant in the job market.

Insurance companies can help their employees adapt to the changing job market by providing training and upskilling programs. These programs can help employees learn new skills such as data analysis, programming, and machine learning. By investing in employee training, insurance companies can ensure that their employees remain competitive and relevant in the job market.

In addition to re-skilling, insurance companies can also explore new job roles that are emerging as a result of AI. For example, insurance companies may need data scientists and machine learning experts who can help build and maintain AI models. These roles require specialised skills that may not currently be present in the industry.