When an insurer’s digital transformation includes AI, medical claims processing costs can fall as much as 50 percent1. And no wonder — AI enables them to navigate the claims lifecycle with greater speed, accuracy, and economy to deliver significant value. Why settle for less?
Whether you’re just starting your AI journey or already several years into it, the key is to ensure that your AI adoption involves the right combination of process design, technology, and operational excellence so that you get the most out of your AI investment.
Speed to value — accelerating the claims lifecycle
AI can accelerate even complex claims to a fraction of the typical timeframes. For instance, a claim involving multiple properties and specialized business lines can be initiated in minutes with AI, when it would typically take half an hour or more.2 When you multiply that time savings across numerous, complex claims each year, the AI-driven value proves significant. Time is money, after all.
AI achieves this value by significantly reducing manual intervention throughout each step of the claims process, including at first notice of loss (FNOL), adjudication, fraud detection, settlement, and regulatory and management reporting. For example, we saved an international property and casualty underwriter 33% in costs to process 50,000 claims per year. By using AI-driven efficiencies to lower administrative expenses like this, insurers can improve their bottom line.
Here’s a closer look at how AI drives a better claims process:
FNOL digitization
Nowadays, most carriers have a digital intake channel where policyowners can quickly enter their claim request, FNOL details, and supporting documentation. Review time can be slow, especially when it involves the interpretation of legal papers, medical reports, etc. Customer dissatisfaction tends to creep in during this waiting period. By combining technologies such as optical character recognition with natural language processing, insurers can rapidly convert customers’ submitted data into actionable information, often in a matter of minutes, rather than taking days or weeks. This leads to faster evaluation of complex claims and better prediction of resolution time, leading to higher customer satisfaction.
Intelligent adjudication
Adjudication has typically been a lengthy and people-driven process. Digitally transformed insurance companies eliminate this speed bump with AI-enabled first-step system adjudication and automatic adjustor assignments. For instance, in a relatively straightforward claim involving windshield damage or a fender bender, a claimant needn’t wait for an adjustor to come assess the damage before generating a quote. Instead, the claimant can submit images, videos, and other documentation digitally, which the adjustor can then swiftly assess using AI and advanced analytics. Although human judgment will generally still come into play, digital shortcuts lead to faster claims resolution, lower insurer costs and higher customer satisfaction. As systems get smarter, they can automate decisions on payments/repudiation and assess subrogation and recovery potential, further mitigating insurer losses.
Streamlined fraud management
Thanks to machine learning, insurance companies can build predictive models to detect fraud with greater precision, in real time. For example, a fleet company may file a claim for axle damage, goods damage, driver injury, etc. On further evaluation, the company may file another claim citing more damages to the same vehicle. AI can flag such claims for an investigator, who can then assess the differences. AI can also limit false red flags, reducing the cases an insurance company sends to outside investigative agencies at extra cost. The result? Lower fraud expenditure, fewer fraudulent claims, and a shorter claims lifecycle, leading to a better bottom line.
Pick the right partner to succeed
No matter where you are in your AI journey, make sure an able partner rides shotgun. Enlist one that delivers not only the necessary technology, but also the people, processes, and operational excellence.
Take stock of your legacy systems first
Many insurance companies today manage claims across disparate legacy systems. Some of those systems can’t process digital data at all. Others may be partway through a multi-year modernization. In contemplating AI upgrades, a company should have a clear vision of how to mesh the new technology with what’s already there, as well as how to integrate it with upgrades currently underway and on the horizon.
Solve for the entire claims lifecycle
Enlist a provider that delivers solutions across the entire claims lifecycle, as well as designs processes tailored to run those solutions at your specific company and navigate any challenges on the road ahead.
Tap insurance domain expertise
The most successful digital solutions take a big-picture approach, looking beyond the purely technological aspects. Ideally, your AI provider bakes design thinking into everything it does, drawing on expertise across diverse disciplines. Equally important, your technology partner should understand the nuances of the insurance business.
Revving toward rapid results
While any stage of AI adoption may seem daunting, it’s all highly doable. Why wouldn’t you want to achieve tangible efficiencies and savings by dramatically speeding up the handling time per claim, lowering your dependency on manual processes, driving down operational costs, increasing the bottom line, and boosting customer satisfaction — all within a matter of months? The choice should be easy. Accelerate your AI adoption today.
Sutherland meets you wherever you are in your digital journey. We’d love to talk.
1 Sutherland case study of a multi-line insurance provider
2 Sutherland case study of international property & casualty specialty and reinsurance underwriter
Reduce Risk. Gain Advantage. Improve Retention.
Vik is a seasoned Financial Services, Business Transformation and Digital disruption Executive. He is a trusted C-Suite Partner and advisor to boards on measurably enhancing enterprise value.
