Fraud has been one of the historical problems associated with insurance, however, never since the invention of policies and current insurance systems has it been so viable to detect and in many cases stop it before it happens.
But this being the case, why it is not implemented in a massive way to share this scourge, here we will explain some of the challenges of implementing new technology that reduces and mitigate insurance fraud.
- Commercial and underwriting, fraud begin from the moment of sale, exactly when the business is going to enter the insurance carrier. In the digital age, there are many ways to detect the potential fraudulent business but it is clear that the difficulty exists when generating the amount of data possible to do so, by digital means, and that is influenced by the percentage of traditional business (emails and so) without structure data making not viable systems that can detect the possible threat. The new digital brokers (insurtechs) play a key part in creating the data necessary for analysis and implementations by providing structure in the management of information that will reach the insurer (or a third party) for analysis.
- Information systems, within this same point, a collaboration between industry peers is essential, the creation of losses (claims) databases with information that allows the identification of fraudulent patterns that are repeated around different insurers and that have had passed under the radar due to the lack of data concatenation is essential. Taking into account that insurers are apprehensive of your information, there are new technologies such as blockchain that allow data to be kept anonymous and allow the adoption of these systems and avoid potential fraud.
- Claims, it is the real moment where the fraud is carried out and materializes with the payment of a sum of money for a loss. This is where the greatest effort is currently seen and applications such as algorithms for the identification of claim patterns are seen, anti-money laundering systems, verifications, etc… However, a lot of frauds evade these controls and are paid because the evidence of the crime will only be seen later due to a lack of early alert systems.
- Forensic analysis, this is where you find those cases that caused the fraud itself but after having made the payment and booked the loss. It is still a fundamental part but it must reveal elements necessary to implement in the previous stages to avoid similar claims that can be avoided since it was entering the insurance company.
There are many war fronts to work on to prevent fraud in the insurance industry, but this cannot be seen as individual company efforts.
It must be attacked with a unified approach from brokers, agents, insurance and reinsurance companies; sharing information (so that data privacy is guaranteed), implementing analysis systems in stages of a sale, in the digitization of data (information entering through portals, web services, APIs or with automated systems for scanning pdf and files for traditional ), past fraud patterns in the purchase stage, in subscription information and claims.
This will allow that in the future fraud detection and prevention can be improved with volumes of data that enter algorithms that learn and avoid future cases of claims.
Inmediate is an insurtech startup from Singapore that is using the latest technology such as Artificial intelligence, Distributed Ledger, and NLP, making insurance processing and underwriting fast, cheap, and flexible. That gives for better processes, lower costs, improved time to market, and new revenue opportunities.