As insurance fraud, we refer to false insurance claims that are intended to create benefits from an insurance process. However, while simple fraud can be identified as loss of a valuable and insurable item, an insured’s creativity is not limited by human nature. Planned accidents, for example a motorist braking suddenly and then being hit from behind, are very complex to be detected as fraud.
With the exception of the fact that today we are completely surrounded by digitization and technological advances that offer the possibility to enable signal processing in complex insurance processes, insurance agents are confronted with fraudulent claims that can be detected based on the following techniques:
• Analyze claim history
• Hiring private detectives or a special investigative agency
• Detecting suspicious billing
• Evaluating credit history
• Internet check, for example social media
• Help from the general public
Cross-checks to detect patternsStatistical methods such as computer data, clustering and classification of the user profile are also known in fraud detection. However, the classic methods do not detect fraud specific to this technological era, as the novelties in technology offer additional opportunities to commit fraud. Cybercrime opens new doors to take advantage of these insurance processes as well.
From a customer perspective, fraud detection methods should not be time consuming so that genuine claims can be handled carefully and within a reasonable timeframe. The process of processing the claims is a very emotional one and so it is important that if an insured, for example, has lost a very valuable property, and thus suffers financial loss, he should not be put under the extra psychological pressure and stress by waiting for his or her promised reimbursement from the insurance company.
Industry 4.0 is accelerating technological evolution and removing at least some of the barriers that existed in the early days of computing due to limitations of memory, bandwidth, etc. Improvements in hardware and software infrastructures enable the development of self-study systems, the so-called artificial intelligence-based platforms. While IBM does this through machine-learning platform IBM Watson, the other technology giants such as Google and Facebook are also on the front line to provide solutions to complex problems such as claims processing and fraud detection.
Artificial intelligence and machines can process large amounts of data in a short period of time. While machine learning techniques can be trained to understand the characteristics of fraud, artificial intelligence can identify the pattern in the data and thus help identify fraudulent claims. We believe these new technology milestones are the game changer for claims management. Fraudulent cases can be recognized in the early process of claims handling and thus save a lot of costs from the insurance perspective. We are currently developing technologies to leverage data exploration and pattern recognition using machine learning techniques and neural networks to detect fraud in our claims management system. However, our focus is on improving the claims handling process so that the pressure on our customers who have suffered a real loss is reduced. The advantage of technology is that we can fully focus on each of our customers and make them feel safe in the digital process of processing their claim.