Fraud is a significant concern for group and employee benefits insurers. In Canada alone, workplace benefits fraud is costing insurers and employers hundreds of millions of dollars every year, according to the Canadian Life and Health Insurance Association.
Advances in technology are increasing the frequency of fraudulent activity in insurance. A study by Deloitte says remote work, increased digitalization and weakened controls are the top three reasons for the recent uptick.
While today's digital environment allows new fraudulent behaviors to evolve, it's also making identifying and stopping fraudulent activity easier than ever before.
1. Real-Time Monitoring With AI
Manual detection of group insurance fraud is next to impossible because of its high costs, and the sheer volume of claims is too high for any group insurer to handle.
As a result, McKinsey predicts that AI-driven technology will be a prevailing method for spotting fraud by 2030. This is because AI and predictive analytic systems can spot copious amounts of fraudulent activity in real time significantly better than humans.
AI can monitor customer interactions, track behavior and language and leverage machine learning algorithms to detect suspicious activity early and minimize potential losses.
Let's say a plan member tries to file a fraudulent health insurance claim through an AI chatbot or systems. However, the AI's algorithms analyze the user's claims history and find that they frequently submit an unusual amount of claims.
AI could detect this suspicious activity and other inconsistencies in real time, probe the customer for additional proof and alert the appropriate manager.
Fraud prevention in insurance is critical to maintaining customer trust in security practices. Integrating AI into security infrastructure is a great way to reduce the probability of such incidents, resulting in significant savings for providers.
See also: Data Breaches' Impact on Consumers
2. Machine Vision and OCR Image Assessments
Identity theft is the root of the group insurance industry’s fraud issues. Fraudsters who compromise a plan member's identity can use their information to make fraudulent claims. This harms the policyholder, the insurer and the providers.
Machine vision refers to the AI-powered analysis of images from sources such as smartphones or satellites. Insurers integrating machine vision-powered technology into their core claims systems or self-service portals can spot identity theft with greater proficiency.
For example, by making the user upload a live “selfie” and ID, the machine vision system can determine if the photo and ID provided are legitimate and ensure the person listed on the ID or group benefits card is the same person submitting a claim.
Insurers must also have accurate data for claims processing, as incorrect information and data can facilitate fraud. Optical character recognition (OCR)-enabled claims processing software can help improve claims processing data accuracy without human intervention.
For instance, plan members can use their phone to take a picture of the receipt from their dentist, eye doctor, etc., and send it to their insurer. Then, OCR systems can structure data from the image of the receipt, confirming if the transaction is legitimate and if the plan member is entitled to coverage.
3. Industry-Wide Data Sharing on Fraud
As organized fraud groups become more sophisticated, the insurance industry has been increasingly willing to share data and insights to stay ahead of fraudsters and develop more effective countermeasures.
Industry-wide data analysis can be facilitated through data-sharing platforms or industry associations that promote information exchange on fraud trends, techniques and prevention strategies.
For example, in 2022, the Canada Life and Health Association (CLHIA) launched an industrywide initiative to pool anonymized claims data and use advanced artificial intelligence tools to analyze and enhance the detection and investigation of employee benefits fraud. By identifying patterns across millions of records, the program improved the effectiveness of benefits fraud investigations across the industry.
Fraudsters often target organizations within the same industry. Therefore, analyzing industrywide data can help identify fraudulent activities that may go unnoticed within a single organization.
For example, predictive modeling uses analytics, machine learning and large amounts of data to build digital models that gauge the likelihood of whether new applications and claims have the potential to be fraudulent. Insurers that train their predictive models with the plethora of shared data and patterns about fraudulent activity can scale and improve the accuracy of their models.
See also: How Technology Is Changing Fraud Detection
4. Blockchain Security
Blockchain's potential for securing transactions from fraudsters and providing trustworthy information has made it an effective and popular method for eliminating many vulnerabilities.
In fact, blockchain deployments can save banks and insurance companies $27 billion annually by 2030, with much of the saving opportunities stemming from fraud reduction.
Blockchain is a type of database that can create immutable and dependable records and validate transactions. It does this through distributed transactions that are shared among a decentralized network of computers. The records shared among these systems are encrypted and can't be erased.
For example, suppose a business buys a healthcare-focused employee benefits insurance package through a blockchain smart contract. In that case, the blockchain smart contract will create immutable data based on the client's records that can accept or refute any insurance claims made by the company.
So, suppose a policyholder makes a fraudulent claim or the carrier no longer agrees to provide coverage for a previously agreed-upon condition. In that case, a blockchain-based smart contract can dissolve and immediately pay the premium back to the plan member or client.
With blockchain, no record can be changed without changing all other records within the same block, meaning there's only a single version of the truth. As a result, fraudsters can't manipulate information to their advantage. This helps build trust between parties, facilitate transactions and maintain accurate claims information and data.
Protecting Tomorrow's Group Insurance Industry
The group benefits insurance industry will never fully eliminate fraud. However, using cutting-edge fraud-prevention technology and industry resources to fight fraud can help make headway against the operational goals of increased efficiency, reduced losses and cost savings for insurers and policyholders.
Fraudulent threats are constantly evolving – insurers and their partners need to use the latest fraud-prevention technologies to monitor new threats and work together to prevent the risks associated with group and employee benefits fraud.
