For fraud systems tasked with keeping up with today’s online criminals, the goalposts are forever moving. Fraud attacks constantly appear in new and unexpected spots. The number of reported fraud cases in the financial sector nearly doubled in the last year, with businesses struggling to keep up with ever-shifting vectors of attack.
From new modes of mobile fraud to skyrocketing rates of identity fraud, the fraudsters are preying on every weak point with increasingly incisive methods. They’re upping their efforts – and so should everyone else.
Traditional Solutions Are Off The Pace
The problem is this, most existing tools are not up to the task of competing with increasingly sophisticated fraudsters. ISMG reported that only 34% of C-level leaders have high confidence in their organisation’s ability to detect and prevent fraud.
Not only that, they are unable to achieve the right balance between security and customer service that modern consumers demand. Companies end up losing customers due to the friction caused when transactions are falsely deemed to be fraudulent because of outdated tools that can’t tell the difference.
Machine Learning Alone is Not the Answer
In response, machine learning tools are being recruited en masse. But while they are very effective as detection tools, on their own they do not do enough to investigate potential fraud cases. Identifying potential cases is only half the process. Identified cases are passed to back-office teams who investigate multiple systems and make human judgements on the level of risk.
Data-Up or Human-Down?
Machine learning is data-up, but to make a nuanced judgement on how best to resolve a fraud case, the human-down element is necessary too. The only way to scale this effectively is to build a tool based on human expertise, which can resolve cases based on your company’s best practice. This is where an automated decisioning tool comes in.
Automated Decision-Making Can Help You Outsmart the Fraudsters
With a company’s best fraud experts at the centre of its configuration, an automated decisioning tool, can model the complex understanding of an experienced fraud professional, and can apply that to thousands of cases.
This human-anchored process has unique benefits that go beyond the capabilities of data-up fraud solutions. Imagine being able to apply a consistent, best practice, human approach to each and every transaction without the need to detect and flag.
Fraud detection is more subtle and adaptable as a result, which means there is less friction for the customer and less risk for the business. In the end, everybody wins – everybody except the fraudsters, that is.