Fraud comes in many forms and can be perpetrated both by individuals as well as sophisticated organizations against individuals, businesses, lenders, and banks. Fraud in lending, while a small percentage of overall loan volume, can add up to a significant amount given the large size of the transactions.

According to National Mortgage News, successful fraud attempts are on the rise.  In 2020, on average 55% of mortgage fraud attempts resulted in fraud loss compared to 36% in 2019. For digital mortgage lenders, 53% of fraud attempts resulted in losses in 2020, compared to 22% in 2019. And according to the report, every $1 of fraud perpetrated on lenders cost them $3.56 in 2020, which is up nearly 8% from $3.30 last year.

Fraud in small business lending has also seen an increase given the proliferation of small business relief loans necessitated by the COVID-19 pandemic.  According to LexisNexis, SMB loan fraud increased 8.3% over the last 24 months and saw a 28.6% year-over-year increase as a percentage of annual revenues.

Some of the more common types of fraud in lending include the following:

• Identity theft - using a stolen identity or a fabricated identity to apply for a loan
• Income - falsifying one's earnings by altering existing or creating fake documents such as pay stubs, W2s, tax returns, or business bank account statements
• Employment - falsifying employment status by using a fee-based online service to confirm one's employment or recruiting an accomplice to verify employment
• Debt obligations - failing to disclose existing liabilities including credit card, loan, alimony, and other monthly payment obligations
• Assets - falsifying or tampering with bank statements or investment accounts

To help mitigate risk and minimize fraud, lenders can take extra precautions to identify potentially fraudulent applications.

Implement Strict KYC and KYB Processes

Although financial institutions have created efficiencies by automating many of the processes that historically required human labor, there are certain steps in the loan application process, especially around KYC (Know Your Customer) and KYB (Know Your Business). This link, Know Your Customer and Know Your Business provides helpful information for both from Wikipedia, process which machines cannot replace. For example, in verifying an applicant’s identity or employment status, an underwriter may want to take an extra step to verify the identity and employment history of the applicant by reviewing the applicant’s Facebook or LinkedIn accounts to look for inconsistencies. Social media is becoming an increasingly useful tool to enhance existing verification processes during the application process.

Data Aggregation Tools

To supplement KYC and KYB procedures, lenders can utilize bank data aggregation tools such as Plaid and Yodlee that, once the customer inputs their bank credentials, gives the lender direct access to the customer’s bank account to verify balances and transactions as well as credit card and brokerage account data. Getting direct access to an applicant’s bank account data will decrease the risk of bank statement tampering, but the adoption rate is low as many customers don’t feel comfortable providing their login credentials.

AI and Fraud Detection Software

Implementing fraud detection tools that utilize artificial intelligence and machine learning algorithms can help businesses mitigate fraud by quickly detecting what a human cannot. Machine learning algorithms are getting increasingly sophisticated and are able to look for patterns and inconsistencies in hundreds of thousands of transactions within seconds. For example, a document fraud detection tool can review bank statements against a database of thousands of statements from the same bank and detect the subtlest of inconsistencies such as font type and size, column headers, spacing, formatting, and countless other data points. Likewise, fraud detection software can review and reconcile debits, credits, and balances, and flag inconsistencies in seconds -- faster and more accurately than a human.

Tools like MoneyThumb’s patent-pending Thumbprint™ fraud detection feature can help financial underwriters automatically detect and flag altered or fabricated credit card and bank statements, helping them underwrite and approve loans more confidently. Thumbprint searches through its database of millions of documents and within seconds gives a confidence score that helps lenders determine whether or not to approve the loan. Learn more about Thumbprint or sign up for a live demo.

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