Fraudulent insurance claims can often cost companies millions of dollars. Insurance-based frauds are rife and mostly happen in healthcare, automotive and property sectors. Insurance companies are always locked in an arms race and must continue leveraging technological advancements to identify and reduce fraudulent claims. The FBI determined that insurance fraud (healthcare insurance excluded) costs the US economy alone over 40 billion USD annually! Healthcare sector insurance frauds are even more ubiquitous.
When it comes to tackling sophisticated insurance frauds, individual transaction monitoring methodologies had become outdated decades ago. Financial services companies have been adopting technologies like Artificial Intelligence, Machine Learning, Data Analytics, Deep Learning, Blockchain, etc. like a fish takes to water.
But executing complex algorithms over vast datasets as necessitated by these advanced technologies requires humongous amounts of computational power. That is where GPUs can save the day. This article will weave out ways where GPU servers can improve insurance fraud detection.
What is Insurance Fraud?
By definition, insurance fraud is an illegal act involving the purposeful submission of inaccurate information by policyholders. By doing so, the policyholder seeks to trick the insurance company with false details about the purported damage for financial gains.
Insurance fraud can be of two types – (a) the first is where the issuer commits the fraud, for instance, a counterfeit issuer sells policies from non-existent companies, and (b) the second one is where the buyer undertakes fraudulent actions for monetary gains. This involves submission of exaggerated claims or multiple claims for the same incident, submission of false medical history, fake death or kidnapping, exaggerated vehicle damage, self-infliction of injuries, etc.
The magnitude of insurance fraud is growing at an alarming rate. In a survey conducted by Friss Insurance AI in 2022, insurance personnel reported suspecting that 20% of all claims might be fraudulent. Another report noted that digital insurance fraud incidents worldwide increased 54.3% between 2019 and 2021.
A report by the UK’s ABI reveals that an insurance scam was detected every five minutes in the UK in 2020 – 300 scams per day! Unbelievable!
Naturally, insurance companies need to act proactively and deploy technologies to detect and eliminate frauds in real-time and reduce the financial outgo caused by fraudulent claims.
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Insurance Fraud Detection – Why and How?
Insurance fraud detection is a set of practices that insurers enforce to distinguish between genuine and fraudulent claims. Such detection mechanisms rely on various techniques to identify and prevent fraud emanating from illicit policyholders, exaggerated claims and professional fraudsters.
Insurance compliance personnel discover and detect insurance frauds by analyzing, researching, comparing, and evaluating claims and documents. Today, all insurance companies also employ advanced technologies like AI, ML/ DL, and Blockchain solutions to detect and prevent fraudulent insurance claims.
According to an Allied Market Research report, the global insurance fraud detection market was valued at USD 3.3 billion in 2021 and is expected to soar exponentially to USD 28.1 billion by 2031. It is but natural that as fraud cases exacerbate and more advanced modus operandi come to limelight, fraud detection technologies will also witness a concomitant massive leap in mass adoption.
GPU Servers for Insurance Fraud Detection – Technology Showcase
Here is a list of technologies that are resource intensive and can be accelerated by parallel computations facilitated by GPU servers –
1. Discovering patterns with Advanced Analytics:
Insurance companies have started leveraging advanced analytics driven by large datasets to determine similarities between previous fraudulent actions and new ones. In the datasets, insurers classify each case as either fraud or non-fraud. Based on the parametric values, advanced algorithms can identify and analyze fraudulent claims. Also, the analytic software can generate easy-to-comprehend visual information and graphs indicating in real-time which insurance category is more acutely affected by fraud.
All these information-heavy analytics and simultaneous real-time visualization require massive computation. Companies can opt for Cloud GPU servers from top-notch Cloud Service providers like Ace Cloud Hosting. Ace Cloud Hosting offers dedicated high-end NVIDIAs GPUs (A2, A30, and A100) for advanced computing for AI/ ML, HPC and accelerated analytics.
2. Detecting Frauds with Predictive AI solutions:
Insurance companies are using AI/ ML to decipher patterns from existing datasets that humans cannot normally comprehend. AI/ ML algorithms scan enormous volume of data in the blink of an eye and predict the extent to which a policyholder is falsifying/ misrepresenting. Running ML models to analyze claims data and uncover irregularities highlighting potential fraud requires massive computation powerhouses.
Therefore, companies prefer using GPU servers with sophisticated Tensor cores for parallel processing and high scalability based on dynamic computational demand. Ace GPU servers are Cloud GPUs which facilitate advanced computing and can also execute situational analysis and human interaction for better fraud analysis and detection.
3. Computer Vision can Assess the Cost of Loss:
Computer vision is another powerful technology that can deduce meanings from visual input. A subset of AI, it ingests input through cameras and derives information from videos and images. Insurance companies have started utilizing this technology to assess the cost of the damage incurred in a mishap. The computer vision algorithm evaluates photos/ videos taken by any camera/ or given as input, and determines the repair or replacement cost.
It uses predetermined datasets (in image or video form) along with pre-defined calculative algorithms based on which it assesses the cost of loss. Insurance companies have to come to rely on computer vision technology, instead of human-assisted assessment, because it can precisely gauge damage without bias or prejudice.
But utilizing such unstructured data for analyzing an accident, repair, or damage cost requires colossal computational resources. Naturally insurance companies and their compliance/ fraud detection teams can get in touch with their IT teams to deploy GPU resources for seamless processing of compute-intensive tasks.
4. Blockchain can Prevent Double Dipping:
Double dipping is fraudulent technique policyholders use to file a claim multiple times with different companies. It can have a severe negative impact, stretching into several million dollars across insurers. Insurance companies have trouble detecting double dipping, thus necessitating the incorporation of advanced technology to remediate the situation.
Blockchain technology can help prevent double dipping. Blockchain is a decentralized ledger that stores transaction data records in real-time while also handling security and privacy concerns. Storing records in blockchain’s distributed ledger introduces visibility across insurers and prevents duplicate transactions for the same claim from getting approval. Blockchain-supported real-time storage, management and validation of data against double dipping can be easily handled using robust GPU-accelerated server resources.
5. Identifying Frauds Using AI-powered Chatbots:
Natural Language Processing (NLP) is a sub-branch of AI that uses linguistics and enables machines to understand human languages and expressions. NLP-driven customer assistant chatbots can accelerate insurance claim processing as well as assist in detecting false claims. AI-powered chatbots use NLP-based pattern-recognition algorithms to segregate fraudulent and non-fraudulent insurance claims. If the AI system determines any unusual or odd claims, it can set a flag against that policyholder for human intervention/ supervision/ further investigation.
Insurance companies can, thus, utilize AI chatbots to filter out fraudulent claims through chats without human involvement in the preliminary investigation. Using GPUs for AI bots running such dynamic NLP algorithms can empower insurance companies to provide highly innovative and cutting-edge customer service to policyholders without unnecessary time backlogs.
GPUs and AI for Insurance Fraud Detection – The Perfect Match
As discussed above, GPUs can deliver unmatched benefits to insurance companies and their fraud-detection/ compliance teams. Running sophisticated, data-heavy AI/ ML algorithms using GPU servers streamlines the entire fraud detection process. It can also enhance customer satisfaction through the dedicated use of AI chatbots and blockchain-based interactive solutions. Some other benefits that insurance companies will appreciate after employing GPU servers in fraud detection are –
GPU can help process complex semi-structured and unstructured datasets because it can operate 100x faster than legacy CPUs. GPU servers come with vast memory and processing bandwidth, as well as high bandwidth GPU-to-GPU communication links. These features can easily streamline complex AI and Analytics systems.
Advanced GPUs, such as those offered by Ace Cloud Hosting, come equipped with performance-optimized CUDA and Tensor cores to perform image recognition, complex image processing, and Exascale computing for ML/ DL tasks. These GPUs can also be dynamically partitioned into several GPU instances for accelerated computing performance.
Again, GPUs rely on the concept of highly parallel processing wherein all the cores dedicatedly perform one single task across numerous datasets, thereby achieving very high efficiency and hence, reducing the overall processing time.
GPU servers introduce the concept of multi-level optimization as an essential criterion for faster image processing, thus reducing latency manifolds and increasing the scale of image processing and recognition.
Scalability is the most significant benefit of Cloud GPU servers. Integrating multiple GPUs manually in on-premise deployment throws up numerous challenges. But insurance companies can opt for Cloud GPU servers that can dynamically scale as per computational requirements, thus reducing the need for highly skilled IT manpower for setting up and operating the GPU resources.
Insurance frauds are an alarming threat for financial and insurance companies. Organizations must be proactive in reinforcing fraud detection systems, employing everything from standard manual investigations to highly heuristic AI-driven methodologies. Modern technologies like ML, data analytics, predictive analytics, pattern-based NLP, computer-led behavioral investigation, etc., have come to play an influential role.
Throughout these advanced technology systems, GPU-accelerated analytics remains the common strand that has proven time and again to be the most optimal solution for undertaking complex calculations and executing highly multi-variable algorithms.
Allow us to demonstrate how our advanced range of Nvidia GPUs can elevate your insurance fraud detection strategies. Book a session with our consultant now.