While new technology-driven solutions are helping P&C insurers speed and streamline their claims process, there are growing fears that artificial intelligence (AI) may fuel more fraud.
A current survey of 75 P&C insurance executives conducted by Digital Insurance for Origami Risk finds nearly half experienced an increase in fraud claims in the past year. Further, 56% recognize AI is making it easier for policyholders to file fraudulent claims, adding yet another wrinkle.
The good news: three in four of those polled expect AI to have a substantial impact on claims management over the next 12-18 months. The ability of carriers to integrate new AI-driven solutions into their existing claims processes will help determine how quickly and effectively they can spot potential fraud, mitigate the risk, and reduce their claim costs.
Finding successful claims solutions
Whether your enterprise is an insurtech with a new core technology platform or an established carrier with a legacy system, here are six keys to achieve success with these powerful new claims solutions.
1. Focus on ROI. Before getting caught up in the excitement over new claims technology, focus on your company's vision for its claims operation and define the project's business objective accordingly. Decide how you'll measure your return on investment (ROI) and the timeframe for achieving results. While carriers with new no-code or low-code core systems can readily integrate with systems of intelligence through APIs, it may take those with legacy systems longer to get up to speed while their IT teams configure the integration or determine how to securely run their claims data through an outsourced provider and receive, assign and process the output.
2. Start small. Do your homework upfront and focus on simple projects that drive value. If curtailing fraud is a top priority, there's an abundance of AI-driven solutions to flag suspicious claims that require investigation by experienced adjusters and expedite claims without markers for processing and payment. You can use the fraud solution as a starting point for integrating AI technology into your claims process, get some small wins and build from there. On the other hand, trying to revamp your end-to-end claims process all at once might take 18 months or longer to implement. The lengthy time may cause the initiative to lose momentum, damage morale and lead to poor outcomes.
3. Engage internal stakeholders at all levels. As with any technology investment, you need to demonstrate value upstream with senior leadership and downstream with the claims professionals and adjusters using the new solution. Adjusters will want to know how the technology will help them do their jobs better, faster and more efficiently. Involving them early in choosing a new solution will help get them fully onboard with the implementation.
4. Set priorities to drive results. In selecting an AI-driven solution to help address claims fraud, learn what's needed for full implementation. If you have a legacy system, get your IT team's input on the time and resources needed to build and complete the integration framework. Recognize how much training and support will be needed to get your claims team fully up to speed. In terms of measurement, you'll know your spend prior to implementation and will be able to track improvements over time. Get feedback from adjusters on their progress with the system and any support or enhancements needed to help them further elevate their performance.
5. Recognize the need for change management. Determine how any new solution will impact your claims adjusters, supervisors, and other team members. How does it change what they do? What learning needs to take place for them to get maximum benefit from the new capability? Ideally, any new solution should be intuitive so team members can get up to speed quickly, appreciate the benefits and be encouraged by the results.
6. Make informed decisions on whether (and what) to build or buy. With AI-driven fraud detection solutions it generally makes sense to buy versus build. Several providers have invested years developing solutions built on tremendous volumes of data that may be almost impossible to replicate – and they may become even more valuable if there's a new wave of AI-driven fraud on the horizon. On the contrary, it typically makes sense to invest in building your own language models into your core system for generative AI. These solutions help facilitate your organization's communications with insureds, agents and brokers and ideally should be developed internally.
With the Digital Insurance study finding 25% of P&C carriers poised to increase their tech spending for claims management significantly in the year ahead, choosing and implementing solutions based on clear objectives, starting small and engaging stakeholders may help drive timely and meaningful results from new investments in AI.
