Why Enterprise Fraud Management Must Include Deposit Focus
Enterprise fraud management (EFM) is the real-time screening of transaction activity across users, accounts, processes and channels, to identify and prevent internal and external fraud in an organization. (Source)
Effective lenders spend considerable time, effort, and resources on enterprise fraud management to make loan fraud more difficult to perpetrate. For example, they shore up processes and train staff. They use a multi-tool approach, such as improved validation tools and predictive AI models.
And it’s working. Today’s enterprise fraud management successfully outwits massive fraudulent schemes and saves lenders billions of dollars.
But fraudsters continually invent new methods to cheat financial institutions. So it’s important to stay vigilant for all trending risks across all channels of opportunity, including deposits.
Add Deposit Focus to Your Enterprise Fraud Management
Consumers have access to an ever-growing number of channels (many with online mobile access) to move their money in real-time. Increasingly large wires, ACH payments and consumer-to-consumer transfers are becoming standard practices. All this convenience provides a fertile environment for fraudsters to exploit deposit accounts.
How? Fraudsters love fast money movement. The faster the money movement capabilities, the faster the fraudster can achieve his goal. And the less likely detection and recovery methods will be effective. Think of it this way:
Fast Money + Fast Fraud
Why Deposits Need Greater Risk Controls
All financial institutions (FIs) have some form of “Know Your Customer” (KYC) program in place to identify and evaluate customers at the time of onboarding. However, the temptation may be to apply less fraud control rigor as customers deposit money, versus borrowing it. As new deposit fraud trends continue (e.g. fraudulently deposited PPP loans or unemployment checks) and money moves more quickly in and out of deposit accounts, banks must reassess the strength of current of their KYC and fraud vetting at account opening.
Mule accounts and suspicious money movement may not have the traditional loss risk to banks that loan products and other types of fraud do. But as these risks increase, so does the need to stabilize the system, protect customers, and protect reputational risk exposure.
If a high risk/fraudulent deposit account is opened, fraud and anti-money laundering teams must chase any suspicious activity. They will need to determine whether to hold funds, close accounts, perform linked analysis, file a SAR filed, etc. As mule activity and fraudulent/suspicious activity increases on deposit accounts, the workload for these teams can increase dramatically.
Deposit Onboarding: Improve Fraud Controls at the Front Door
While many risk manager, auditors, and regulators incorporate enterprise fraud management strategies at some level, gaps remain. The concept of expanding existing controls and process for better coverage is an easy concept to get behind. But it is often an expensive and difficult structure to fully operationalize where silos exist across products.
A strategy some banks now use to combat deposit fraud is to leverage existing loan fraud prevention processes, tools, and training already in use, and apply them across the enterprise.
In other words, the same tools that validate loan applicants’ incomes, employers, identities, and overall risk can vet out high-risk deposit accounts. And they can accomplish this before the activity occurs, while complimenting the existing KYC processes. For instance, verifying employers and other identity markers is a standard control for loan products and a leading indicator for risk, but not for customers opening a deposit account. The door is wide open. If you wouldn’t knowingly book a deposit account where you knew the customer was providing a fictitious employer, wouldn’t it be helpful to apply that control at the front door?
Closing large gaps like this can not only help the entire system, but also can drive down expenses, and potentially downstream losses.
Point Predictive enables lenders to fund more loans with confidence with its unique combination of Artificial and Natural Intelligence [Ai+Ni] and proprietary data repository leveraging millions of industry data points.
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