The key to reducing false positives in fraud detection systems
For the uninitiated, if we go back a few years the term ‘false positive’ was mainly a medical phrase that indicated that a patient had been diagnosed with a condition that upon further reflection, turned out to be benign.
Fast forward to today’s financial services industry and the term is now closely associated with the industry’s attempts to combat fraud. In this context a false positive is deemed as a suspicious transaction, loan application, or insurance claim, for example, which turns out to be innocent upon investigation.
"Taking the time to map the flow of data, and how any data matching or rule based decision system fits within an organisations processes, can often yield reductions in false positives that might have otherwise required much more sophisticated, and expensive methods to remedy."
When it comes to combating fraud one of the most challenging things to get right, regardless of which business sector you’re working in, is understanding how to minimise the amount of these false positives being generated.
In many respects, because of the huge growth in transaction volumes across all areas of financial services, precipitated by the advent of the Internet, most investigation teams place huge importance on reducing the amount of false positives their fraud defence systems are generating.
Many companies have complicated legacy systems to help them try and address fraud. Many just aren’t up to the job of coping with the exponential growth that has occurred in transaction volumes, and the volumes of data that they are being expected to deal with.
Additionally investigation capacity is a very finite, and specialist resource. Many companies deploying fraud detection systems become rapidly overwhelmed with investigations for these teams if they haven’t calibrated their solutions correctly – or configured their metrics in the most appropriate way for the business sector they are in. This results in a multitude of false positives that all require some kind of assessment.
Obviously fraud assessment or investigation requires resource, and takes time, which all adds significant cost to the business – and risks creating a drag on competitiveness while potential new business is held up in the approvals process.
This fact doesn’t help banks, insurers or financial providers who are under increasing pressure to increase profitability. Perpetually low interest rates, additional regulatory compliance burdens and increasing competition from new ‘fintech’ start-ups have all eroded their margins. As such these companies need solutions that improve their bottom line by reducing the cost of risks – not adding to costs or reducing competitiveness.