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With mortgage fraud on the rise, it’s more important than ever before for mortgage companies, independent mortgage bankers, credit unions, and all lenders to prevent fraud at the earliest stages of the mortgage process. So, how can you minimize risk and protect yourself, your borrowers, and your organization? Continue reading to find out how other lenders are dealing with potentially fraudulent activity every day.
Marc De Diego Ferrer
Marc De Diego Ferrer is a registered real estate agent, tax advisor, and founder of MCA Assessors.
Table of Contents
Request an Endorser
This risk minimization technique may be applied, especially when an applicant has no credit history or convincing financial statements. Banks request an endorser who is willing to sign, saying that they would take responsibility for loan repayment if the applicant fails to repay it on time. This measure minimizes the risk of loaning money to applicants with bad credit histories or committing fraud. Endorsers should preferably be family members with the ability to repay loans.
ID Verification, Facial Recognition, and Other Data Analysis
There are various ways for lenders to avoid lending money to fraudulent customers. Top of all is ID verification, facial recognition, and guarantees from the two or three other people who know the borrower. Bank account and family background verification must be done before lending someone money.
The other main thing which must be kept in mind is that one should always keep the transactions written somewhere in the form of deeds or stamps, etc. The lender can also check the bank statements of the borrower to analyze their monthly income and calculate the amount which they can pay back or not.
Utilize Machine Learning to Analyze Borrower Data
One of the best ways to minimize lending fraud is through lending software that utilizes machine learning and fraud analytics to score each new online application for fraud risk. These systems will usually be able to access a wide range of internal and publicly available data, ranging from physical addresses to social media data to email accounts, phone numbers, and more, to identify any hidden patterns that may point to fraudulent information or activity.
For instance, these systems can identify patterns in fraudulent phone numbers that can allow lenders to automatically flag these numbers in future applications for manual review. This way, instead of making your best guesses on new applications, your system can do the work of keeping a detailed record of all known scam factors and notify you of anything suspicious in advance.
Raise Interest Rates and Require Substantial Collateral
To reduce its credit risk, lenders can raise interest rates on loans, and require substantial collateral, as well as impose debt covenants allowing them to call the loan at any time if the covenants are violated, and to require the borrower to pay it off before it can spend the money.
A user can take a picture of an ID and a selfie in real-time to verify their identity with an automated ID verification solution for online applications. The technology is used to verify that a selfie is not a snapshot of a photograph but a real photo taken by the individual. Afterward, facial recognition technology confirms that the selfie matches the ID.
There is also the option of making a video call. When loan officers call an applicant for information, they verify their identity by asking a few questions about their appearance compared to their ID photo.
