Artificial intelligence and fraud detection software in insurance

Even medium-sized insurance agencies operate hundreds of thousands of dollars in their regular shop floor activities, whereas the money flow of behemoths in the sector reaches millions. Naturally, such considerable sums attract various unscrupulous people and downright swindlers who want to capitalize on the inadequacies of protective systems insurance organizations utilize. AI-powered fraud detection solutions for insurance are second-to-none instruments that can boost companies’ anti-fraud mechanisms and forestall potential financial and reputational losses resulting from fraud.  

But before we zoom in on the application scenarios and benefits of artificial intelligence in insurance fraud detection, it is necessary to understand the nature of the most significant fraud-related issues in the industry. 

Challenges of insurers concerning fraud

Modern insurance organizations make fraud detection and prevention a cornerstone of their security policies. However, in the US alone, the consequences of fraud cost them over $308 billion every year. How come?  

Evidently, scammers become ever more sophisticated in trying to scam insurers. The traditional range of tricks they employ with this goal (overstating the value of stolen items, false injury, unnecessary treatment, wrongful billing, staged accidents, duplicate claims, misinterpretation, and non-disclosure, etc.) grows radically due to innovations and ground-breaking technology achievements exploited by them. The “latest fraud trends” where artificial intelligence plays a pivotal role include: 

• Voice cloning. Fraudsters access a person’s audio and video posts on social media to obtain a sample of their voice. Then, they forge its clone and use it to answer phone calls from insurance agents who want to talk to a customer about the document or email they “sent.” 
• Deepfake photos and videos. AI technology helps fabricate fake videos or pictures by manipulating existing photos or video footage. Utilizing these synthetic media, criminals can create false accounts on social networks or even fake video calls via Zoom or Skype. They act in the name of actual banking experts and offer false loans or advertise cryptocurrencies. 
• Medical evidence. AI-fueled image generators are trained on a vast pool of radiology data to create CT scans or X-rays, which are then submitted to insurance agencies as medical evidence. 
• Business documentation. Criminals with limited language skills use ChatGPT and various AI bots to target victims in other countries via grammatically flawless and thus convincing messages in phishing attempts and email scams. 

Obviously, combating AI-driven hoaxes is possible only with weapons of the same level. Let’s have a look at the technological advancements and AI fraud detection solutions insurance organizations can use to expose and prevent scams. 

AI for insurance fraud detection: Use cases scrutinized

As a high-profile IT vendor specializing in insurance solutions, DICEUS considers the following know-how pivotal for fighting fraud with the help of artificial intelligence in insurance sector.  

• Machine learning. ML algorithms are highly instrumental as a core of AI automation tools that reveal fraud patterns across historical data. Being trained on such data sets, machine learning mechanisms can recognize potential threats in the datasets fed into AI insurance fraud detection software for negative sentiment indicators in their reviews or social media posts. 
• Predictive analytics. Thanks to this kind of artificial intelligence fraud detection, insurance companies can predict future fraud trends, pinpoint high-risk policyholders, and initiate proactive measures (adjust premiums, refuse coverage, etc.) aimed at scam prevention. 
• Natural language processing. NLP mechanisms can help in fraud pattern identification in the spheres dependent on text analysis. They expose vocabulary and grammar irregularities in claims customers file or look for negative sentiment indicators in their reviews or social media posts. 
• AI-powered engines. These excel at biometric authorization techniques (voice recognition, face or fingerprint scan) that are increasingly ousting passwords, OTPs, or other old-school security practices and enable AI fraud detection insurance solutions to prevent identity theft.  

All these cutting-edge technologies relying on artificial intelligence in insurance software can yield maximum effect if the anti-fraud product has proper functionalities to carry out its mission.  

Must-have features of AI-powered fraud detection solutions for insurance

While creating first-rate insurance fraud detection and prevention software, DICEUS prioritizes the following AI-fueled capabilities. 

• Anomaly detection. Companies worldwide employ This primary mechanism in their fraud detection routine. Insurance companies can leverage this functionality to set up autoencoders and deep learning-based techniques to expose suspicious activities related to filing a claim, flag claims that deviate from the normal pattern (like those submitted too soon after the accident or those filled out quicker than a human can do), alert to claims with unusually high payouts, and more. 
• Past data analysis. Graph neural networks (GNNs), long short-term memory (LSTM) networks, and similar instruments leveraging AI in insurance fraud detection are employed to sift through historic fraudulent claim attempts, reveal patterns in them (like repeated doctor’s name or phone number), pinpoint sequences of events that cause suspicion, and serve as insights for fraud monitoring policies a company adopts. 
• Image analysis. This tool has a wide scope of applications for insurance fraud detection – from recording camera data that validates a person’s image authenticity to revealing various AI-created scams (for instance, doctored videos and photos). 
• Risk profiling and assessment. Such a module is responsible for classifying data patterns according to the type of risk they are related to and generating a threat index for each claim where the pattern is spotted.  
• Integration with third-party data sources. Insurers can have a comprehensive view of their customer only if they draw upon external data sources (EHR, social media, etc.) that can complete the picture where the client is a centerpiece. 

As you see, developing a high-quality anti-fraud product is a no-nonsense task that should be entrusted only to an IT vendor competent in AI implementation with multiple completed projects in the insurance realm under its belt. DICEUS ticks all these boxes. We can deliver a top-notch custom AI-powered insurance fraud solution of any size and complexity that will augment your scam detection and prevention power and minimize fraud-related losses your organization suffers from. 

Drawing a bottom line

Artificial intelligence in insurance industry is making its triumphant advance into various shop floor aspects of this domain – from claim management and billing to insurance analytics and customer support. However, cybercriminals also exploit this technology to fool insurance agencies out of their money. Combating such attempts can be effective only if AI becomes the core of the digital transformation strategy in the field and the centerpiece of anti-fraud insurance software.  

NLP, ML, predictive analytics, and AI-fueled engines are highly instrumental in anomaly detection, image analysis, past data scrutiny, risk assessment, and more. The efficient implementation of insurance fraud detection and prevention solutions can be achieved by partnering with a seasoned IT vendor having in-depth expertise in the niche.  

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