Financial services professionals once considered effective fraud prevention as simple as requiring a customer to present the teller a driver’s license or entering an ATM PIN. If only things could work so simply today. The advent of online and digital banking changed all of that by creating touchpoints unfathomable even a decade ago.
As financial institutions continue to leverage multiple channels, preventing fraud attacks has become as complicated as it is critical. The use of phones, computers, tablets, smart watches and other connected devices provides consumers with the convenience they expect. That must serve as an eye opener: Because customer behavior isn’t siloed, fraud solutions can’t be either.
Instead, a concerted effort must take root to enact effective measures that holistically mitigate risk against cross-channel fraud, meanwhile avoiding unnecessary false positives that can drive customers away.
Analytics meets adaptive fraud prevention
A study by the Ponemon Institute and Accenture reveals that the financial services industry, including credit unions and banks, saw 125 security breaches in 2017 with an average annualized cost of $18.28 million: higher than any other sector. Further, the Identity Theft Resource Center reported that in 2017-2018, "the number of consumer records exposed containing sensitive personally identifiably information jumped 126 percent." What’s more, 1.68 billion non-sensitive records were compromised last year.
Banks can't get into the habit of creating individual fraud prevention strategies for each channel because that can leave gaps that increase exposure. The focus must remain on all channels as banks adapt to a customer’s unique behaviors and differentiate those from criminals’ chameleon-like attacks.
Unlike rules-based systems that rely on pattern-matching against known fraud types, adaptive behavioral analytics ingests a variety of data from all channels to develop granular behavioral profiles. Utilizing this, institutions can adopt a clear lens across the customer journey into risk at all of the critical customer touchpoints.
This moves beyond the labor-intensive practice of stacking rules to create a dynamic fraud prevention mechanism. This way, even slight deviations are detected that would normally slip through the cracks of other fraud prevention systems. Regardless of the scenario, the difference lies in the seemingly innocuous (but incredibly important), versus countless clues that indicate whether fraud actually occurs. This leads to determining in real time whether the transaction should proceed.
Combined with machine learning, adaptive behavioral analytics allow banks to pinpoint when, where and how customers interact with an account and make purchases. In addition, data scientists with a deep understanding of the fraud use case and underlying behavior can build targeted features and robust models that move beyond self-learning algorithms to truly adaptive behavioral profiles.
The importance of real-time decisioning and anomaly detection can’t be emphasized enough, given the undeniable convenience and security customers demand from their banks. A recent survey found that 77 percent of U.S. consumers checked their bank account for suspicious activity at least once a week; 59 percent wanted their bank to notify them of suspected fraud immediately; and 36 percent have cancelled a credit or debit card within the past 12 months because of security concerns.
Lost customers equate to lost revenue and while customers expect security, they don’t want a genuine transaction declined because their bank incorrectly suspected fraudulent activity. Over the long term, any inability to discern actual fraud from genuine customer behavior could cost a bank millions of dollars in unrealized assets and income.
Putting it all together: Protect your customers
As customers demand secure, convenient account access through various channels, so too will cyber criminals fight to leverage those channels to perpetrate fraud any way they can. The only deciding factor between which party wins boils down to the foresight banks show to enact a premier fraud prevention strategy. The differentiating value of adaptive behavioral analytics makes this possible—and in terms of halting a fraud, should make criminals afraid.
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PJ Rohall is a fraud subject matter expert at Featurespace.