How AI is redefining underwriting practices
Underwriting is traditionally heavily reliant on human expertise and judgement, particularly within the initial review process when underwriters analyse and assess the risk of insuring a person or asset using multiple sources of data. While AI is currently affecting the insurance industry, it has the potential to disrupt the traditional role of underwriters by blending both human expertise and judgement with machine accuracy.
AI and the future of risk management
Risk management forms the core of insurance underwriting and has a major knock-on effect, with the initial evaluation of potential risks associated with a customer determining the appropriate premiums and coverage terms they are offered. Historically this has been a manual process, requiring the analysis of multiple documents, multiple different data sources, claims history and then applying professional judgement.
Where can AI enhance this process?
Agentic AI, a more advanced form of AI, is designed to respond autonomously to solve complex multi-step problems using multiple data sources, expediting the initial review stage for underwriters by collating and examining all sources needed to evaluate potential customer risk. It is important to note that while AI will be used to collate the relevant data from multiple sources and suggest relevant action, it is the historical expertise of the underwriter that is essential to make any final decisions. AI enables underwriters to make faster and better data-driven decisions with greater confidence, rather than replace the human role in the process.
How can AI extract the relevant information underwriters need?
Natural language processing analyses unstructured data sets such as medical records and extracts the relevant data for underwriters to make their decision. This removes the need for manually scanning through various documents to retrieve the customer information needed and can flag any critical risk indicators. The chances of data sources or risk factors being missed through subjectivity or misclassification can be mitigated and arm underwriters with all the relevant information needed.
Fraud detection and risk segmentation
With fraud costing the insurance industry over £2 billion a year, fraud detection and prevention is always a high priority for insurers. Anomaly detection through application comparison against existing datasets can be automated with AI and provide actionable insight that cannot be achieved manually and give underwriters the confidence that fraudulent activity is being detected and stopped while they continue their work.
Furthermore, AI is being used to complete more refined risk segmentation by underwriters so that more nuanced subcategories for customers can be created and enable underwriters to create more personalised policy offers to their customers.
The evolving role of underwriters
As AI continues to be integrated into routine tasks, the role of underwriters will shift from execution towards strategy and oversight in some key areas:
While these advancements are helping to automate many aspects of underwriting, the role of underwriters is still integral to the process and the technology cannot replace human expertise. As the insurance industry continues to embrace AI, underwriters will remain indispensable, leveraging the power of AI technology to enhance their expertise and deliver better outcomes for insurers and their customers.
If you are interested in seeing how AI can help automate the initial review step in your underwriting process, watch our Automating Underwriting demo below.