How generative AI will transform the insurance industry
Generative AI has the potential to transform the insurance industry. Kainos’ Data & AI Director, Gary Hunter spoke at ABI’s Annual Conference 2024 on the ‘Generative AI: transforming the insurance industry through innovation and growth’ panel, and this article explores how this rapidly developing area can improve outcomes for consumers and businesses alike.
What are the benefits of using generative AI in the insurance industry?
Improved customer experience
AI can be used to provide personalised recommendations and allow customers to act on a self-service basis to access information or services faster and more efficiently. For example, generative AI can create customised insurance quotes, policies and claims based on a customer’s profile, feedback and preferences.
Improved employee experience
Employees can find the information they need in real time, allowing them to expedite processes and deliver a more personalised, efficient experience for customers. AI can automate tasks, such as data entry, document summarisation and claims processing- allowing employees to focus on value-add work.
Improved time and cost efficiencies
With back-office processes becoming more efficient and data more accessible, organisations can set performance benchmarks and compare data across their departments, identifying areas for improvement and improving customer insights. AI can also identify fraudulent behaviour, reducing fraud related losses and improve risk assessment to help insurers to assess risk better and price policies accordingly.
How can generative AI be used within the insurance industry?
Document analysis
Generative AI can help automate and enhance the process of extracting, validating, and summarising information from various types of documents, such as policy contracts, claims forms, invoices, or evidence like medical records. Natural language models can be used to understand the content and context of the documents and generate summaries, classifications, or validations in natural language. For example, document analysis can help speed up the claims processing, reduce errors and costs, and improve customer satisfaction and loyalty.
Compliance monitoring
Reports can be created to monitor activities or performance in line with various insurance regulations or standards such as Consumer Duty. Modern data solutions, combined with AI can be used to help insurers comply, as it can be used to assess large data sets, create reporting and allow insurers to be proactive rather than reactive in the regulatory sphere. Middle office employees can be alerted to issues or regulatory violations and be given an explanation using natural language, with actions recommended to solve problems.
Virtual agents
Chatbots with greater capabilities can be built for customers to use on a self-service basis. Generative AI can facilitate natural conversations with large language models which can be trained with organisational and wider information sources. For example, virtual agents can help customers with common queries, claims, policy updates, or renewals and provide relevant information and guidance.
Contact centre insights
Voice and text data from contact centres can be analysed to generate insights and recommendations to improve customer service, sales and retention. Natural language responses and scripts can be generated for agents to use when communicating with customers, as well as sentiment analysis and emotion detection to gauge customer satisfaction and feedback. For example, contact centre insights can help identify customer needs, preferences, and pain points and suggest personalised offers, solutions, or cross-selling opportunities.
While this article does consider some of the potential benefits of generative AI within the insurance industry, insurers must also consider the quality of their data, ethical implications and how they can keep their data secure.
Download our latest whitepaper ‘Generative AI in FSI: Data, ethics, regulation and security,’ where we consider how financial services organisations can maximise the impact of their generative AI implementation.