Fraud, detected and undetected, is a key area of concern for anyone embracing the digital lifestyle.
According to a recently published article covering the global insurance industry, insurance fraud costs American consumers at least $80 billion each year. It also estimates that workers’ compensation insurance fraud alone costs insurers and employers $30 billion annually.
Insurance fraud is an ongoing problem that has shown no signs of slowing down. It is sometimes misinterpreted as a victimless crime. Consumers, in turn, suffer higher premiums and slower claims processing as a result of these crimes, in addition to significant monetary and reputational losses to insurance companies.
The ongoing Covid-19 pandemic is expected to increase insurance fraud cases as reports already suggest an increase in Covid-19-related fraud. A study published by State of Insurance Fraud Technology found that AI has become an increasingly important tool for fraud detection, as conmen are leveraging online and social media data for such fraudulent activities. The good news is that India’s insurance industry has been able to curb fraudulent activities by digitizing fraud investigation.
In one survey, 68% of respondents said their organizations are using digital solutions for investigations, while 19% said they were in various stages of planning to go digital.
Machine learning, predictive analytics, data mining methods are increasingly used for fraud detection, as timely detection is essential, given that there is a deterrent for fraudsters. Here are ways technology can help detect fraud in its early stages.
Blockchain
A database network referred to as Blockchain, records transaction data in real time. What this technology also does is highlight concerns around security, privacy and control. This technology has also been hailed as an ideal solution to combat insurance fraud. Blockchain’s ledger maintains a permanent record of transactions that are automatically synchronized without the use of a centralizing third party. It is a process where each block is linked to a previous block and all have time/date stamps. If a hacker tries to change the information in one of the copies of the blockchain, the other versions will reject it as contradictory. Blockchain is also used to prevent identity fraud in insurance practices.
Anomaly detection
Anomaly detection is one of the main trends in cybersecurity practices, with multiple use cases such as fraud prevention. In the case of insurance fraud, machine learning (ML) models help identify what a normal claim looks like to establish a baseline. Once that baseline is established, they can identify anomalies and notify insurers. During claims processes, anomaly detection helps in screening legitimate customer claims. This creates a model of how a typical claim appears, which it applies to larger datasets. It can also be used by insurers to detect suspicious behavior among users on their network.
Predictive analytics
Above MarketWatchThe Global Predictive Analytics market size will reach USD 34.1 billion by 2027. Valued at approximately USD 6.9 billion in 2019, it is projected to grow at a healthy growth rate of more than 22.17% during the forecast period 2020-2027.
Like anomaly detection, predictive analytics involves training artificial intelligence or machine learning algorithms using historical data so that they can ultimately predict future incidents. Predictive analytics helps maintain a level of reactivity rather than proactivity.
Accelerating request processing with chatbots
Reporting the damage or theft to any insurance company generally initiates claims processing. Traditionally, it was done through intermediaries. However, with technological advancements, policyholders can now use chatbots on the insurance company’s website/mobile app to file a first notice of loss (FNOL). Chatbots would direct them to take photos and videos of the damage, potentially reducing the time for fraudsters to alter data. These natural language processing (NLP)-driven customer assistants speed up the processing of requests, without requiring human intervention.
The writer is VP – Insurance Practice, Fulcrum Digital Inc.