AI: Detecting Fraud and Improving Claims Handling

The implementation of artificial intelligence (AI) in claims handling may not only help revolutionize the way claims are handled, but also may play a large role in detecting and preventing fraud. Use of chatbots and algorithms can reduce costs, streamline claims, and detect fraud that may otherwise go unnoticed.

The Great Resignation has left many carriers and employers without the experienced workforce to provide frictionless customer service, adequate claims handling, and fraud prevention. Claims adjusters are often overwhelmed by assigned case loads and frequently grow weary of the tedious aspects of paperwork and customer service. The routine, and oftentimes repetitive, inquiries from claimants can dominate an adjuster’s time, limiting their ability to focus on necessary to high value, complex issues in a matter.

Chatbots can be implemented to improve customer service and eliminate the need for adjusters to address the common inquires of claimants. They are significantly faster at analyzing data as compared to their human counterparts and are available 24/7 to answer questions. This expedited analysis connects claimants with needed assistance more efficiently, and with fewer errors, leading to a better customer service experience. Chatbots can create documents and further assist claimants with completion of documentation and uploading the information to the claims system without human intervention. Claimants may use these automated systems to make general inquiries into claims status, medical authorization status, or update their profile or demographic information.

Alleviating the need for adjusters to handle common, repetitive inquiries from claimants allows them to handle the more complex aspects of claims. This reduces the adjuster’s workload and allows for more time and thought to be put into more critical decision-making issues. Automating the claims handling process can lead to significant reduction in operational costs while enhancing the claimant’s experience.

Additionally, chatbots can coordinate services, handle payments and billing processes, and sort voluminous materials, making these actions more streamlined. AI billing processes can automate payments and assist in inquiries regarding payments from claimants or medical providers. This will further alleviate the manual steps needed to establish simple payments.

Machine learning tools can be implemented for use in claims processing as well. These tools can quickly review file data to forecast a timeline for treatment, as well as the potential associated costs. Machine learning tools may be able to review medical records and a claimant’s full medical history in a short period of time to determine if a course of treatment is necessary. These tools may identify any potential unnecessary services, which could lead to less spending on claims, shorten the length of claims, and return workers into the workforce faster.

Machine learning tools can also help medical providers and claims handlers track a claimant’s progress in reaching important milestones in the healing process. AI tools can analyze data to detect obstacles to recovery before unnecessary medical services are provided and paid for by the carrier. This also flags claims to direct medical providers to restructure treatment regimens when necessary to speed up recovery. This will reduce the time and medical costs on each file.

Identifying Fraud Indicators

While AI can reduce overhead on the claims handling side, it can also be an effective tool to reduce costs associated with fraudulent claims. Undetected fraud causes undue costs for carriers. Insurance companies have heavily relied upon manual investigations to identify and prevent fraud. However, many cases of fraud can go undetected as the data requiring analysis can be voluminous and disorganized. AI can gather and organize vast amounts of data quickly and pinpoint unusual patterns that may signify fraud. 

AI can detect correlations and patterns that may go unnoticed by the human eye. It can sort, review, and analyze high volumes of data in an a substantially shorter amount of time than is humanly possible. Additionally, AI can review data around the clock from various sources and flag suspicious behavior for further analysis and investigation by a claims handler. Machine learning systems may understand speech, conduct research related to those speech patterns, analyze any generated data, and interpret documents. Chatbots can be utilized to transcribe voice data when workers talk to insurance adjusters about their claims. Voice data allows for more information to be gathered in lieu of forms with limited space. Chatbots can also transcribe conversations, giving detailed transcripts that can be useful in identifying fraud indicators, such as long pauses.

Medical Provider Fraud

In addition to combating claimant fraud, AI can be used to prevent medical provider fraud and can gather and highlight errors in billing to prevent overbilling, upcoding or duplication of services. One of the most critical issues with preventing provider fraud is the fragmentation of the systems. Claims are spread around countless carriers with each carrier supporting its own network of medical providers. AI tools may access multiple pools of data distributed amongst the carriers to assess patterns in provider behavior and billing that may alert to fraud.

AI can also quickly access volumes of billing data from the national provider identifier system to alert handlers to multiple bills from different named providers, thereby signifying duplicate billing. AI tools can track referrals from providers to other entities to identify repeated patterns that may signify relationships between multiple providers, and such patterns may indicate increasing treatment costs.

With the advancement of AI tools and their application to the insurance industry, costs associated with claims can be significantly reduced. Better tools for streamlining the claims handling and customer service processes will reduce overhead and lead to a better customer experience. Reduction in fraudulent claims will decrease costs and implementation of enhanced fraud monitoring may reduce the overall number of fraudulent claims. Altogether, AI can create a more cohesive, streamlined claims process. We are just beginning to see the positive impact AI can have in the industry and as technology advances, the benefits will only continue to grow.