A thief who steals your identity can use it to obtain loans for properties, vehicles, and companies. Here’s how to stop loan fraud from happening to you.
Jory MacKay has been writing and editing for print and online publications for more than ten years. She has won several awards. He is passionate about assisting people in recognizing and avoiding fraud, and he holds a bachelor’s degree in journalism from the University of Victoria.
Alina Benny is an expert for Aura on fraud, identity theft, and internet security. She has almost ten years of experience in content research and graduated with a bachelor’s degree in electronics engineering from the Cochin University of Science and Technology. Twitter: @heyabenny.
What Is Loan Fraud?
Any dishonest behavior intended to obtain a financial advantage during the loan process is referred to as loan fraud.
There are numerous varieties of loan fraud, including loan scams, mortgage fraud, payday fraud, and ATO in online lending. Each of them will result in a financial loss for someone, while the counterparty will make money and vanish.
This kind of scam is becoming more common in the US; CoreLogic estimates that 1 in 164 mortgage applications are suspicious. However, the online environment is far riskier, with startups trying to draw clients with simple and quick processes.
It’s important to remember that depending on the type of lending fraud, the roles of the criminal and victim may vary.
Sometimes, the entity providing the loan (the creditor) engages in dishonest behavior. In other situations, the party acting in bad faith is the individual or entity that is receiving the loan (the debtor).
How Does Lending Fraud Work?
All lending fraud is built on deception. Someone is going to pretend to be someone they are not at some point during the money lending process.
Usually, the debtor is the one who will give misleading information. They will make use of fake or stolen identification that blends the details of real people with made-up material. After their loan is authorized, they will vanish without paying it back. The same applies to business loans.
More cunning borrowers who commit fraud will diligently repay their debts to improve their credit history. After that, they’ll take out a sizable loan and vanish.
What Are the Types of Loan Fraud?
Let’s examine the forms of lending fraud that are becoming more common.
Financial firms have to be on the lookout for different kinds of lending fraud because the fraud landscape is constantly changing. Let’s look at some common types of loan fraud.
One type of first-party fraud is mortgage fraud, in which the borrower fabricates information or misrepresents their financial situation in order to get a mortgage. There are various types of mortgage fraud:
· Occupancy fraud refers to the practice of a borrower buying an investment property with the goal of renting it out while falsely claiming to be the owner or to use it as a second residence. As a result, they might be able to get their mortgage interest rate lowered.
· Income fraud refers to lying about one’s income in order to get a bigger mortgage.
Mortgage fraud also includes withholding information, such as by not disclosing liabilities.
Payday loans are high-interest, short-term loans offered by businesses whose operations depend on minimizing friction. Payday loan fraud occurs when dishonest people use the low friction to get loans and then vanish into thin air with their money that they shouldn’t have.
First-Party Fraud (or Personal Loan Fraud)
In this case, the applicant will knowingly fabricate information or overstate their financial situation in order to be approved for credit that they might not otherwise be eligible for. Because of these unlawful efforts, the majority of digital lenders mistake first-party fraud for a credit loss.
It will be challenging to compare the amount you actually lose to fraud versus credit risk because first-party loan fraud is on the rise.
Unfortunately, loan companies won’t have it easier anytime soon. Personal loan fraud increased by 2040% in the first half of 2020–21 alone, up 2063% from the previous year, according to Experian.
When someone provides their personal information to another person so they can commit fraud, it’s known as second-party fraud. The accomplice can be a family member or friend.
Occasionally, the individual whose information is being used may not even be aware of the loan program.
Second-party loan fraud is difficult to identify since there are frequently no outward signs of illegality. After all, the information provided is legitimate. Below, you’ll see how to stop this increasingly common kind of attack.
Third-party loan fraud, also referred to as identity theft, occurs when someone obtains credit with no intention of paying it back by using a false identity or the identity of another person without that person’s consent.
Synthetic identities, in which the con artist fabricates a new identity by faking and pilfering information, are the primary means of supporting this. Following that, they borrow modest sums of money and really pay off the debt in order to validate this new identity and boost its credit score.
This enables them to subsequently take out large loans and disappear without a trace.
Third-party loan fraud can also happen offline, wholly or partially. For example, scammers have been known to apply for loans using stolen SIM cards.
Third-party fraud is an especially common problem with digital lending due to the seamless, entirely online onboarding process. When done on a large scale, it can result in enormous losses. According to McKinsey, artificial identities are the reason behind 10% to 15% of annual losses experienced by lenders.
When a borrower applies for multiple loans quickly without intending to repay them, this is known as loan stacking.
Because credit inquiries and new accounts can take up to 30 days to appear on a credit profile, lenders occasionally are unable to determine who has applied for several loans in a short period of time until it is too late.
Since this loophole can be very profitable, fraudsters take advantage of it.
These fraud risks have the potential to bankrupt your lending businesses, particularly microlenders, startups, and fintech innovators.
You need a strong, perceptive fraud detection and prevention solution to hold scammers accountable. Stop loan fraud without compromising.
Use alternative, real-time data to more effectively combat loan fraud and create more accurate customer profiles.
How Dangerous Is Loan Fraud?
Loan fraud presents a danger to individuals and businesses. People whose personal information is taken and utilized by scammers may suffer severe emotional distress and have their credit severely damaged. A person’s life can be significantly impacted by a bad credit score in a variety of ways, from making it difficult for them to get a mortgage to destroying their chances of starting their own business.
Loan fraud can cause financial and reputational harm to lending companies. Lenders incur costs from non-repaid loans as well as from the time needed to look into fraudulent loans, report losses, communicate with regulators, and other issues.
Industry insiders have repeatedly cautioned that simple identity verification is insufficient today. We require an identity proofing system that is difficult, if not impossible, to hack for these and other reasons.
As noted in Javelin’s Study on Digital Lending Fraud:
Examining an individual’s online presence, or their digital footprint, to gain insight into their identity is known as “digital footprinting.” It stems from the understanding that email addresses and phone numbers are the new digital passport.
Each of these has a wealth of publicly available data associated with it that we can utilize to learn more about the client. Most importantly, you wouldn’t fabricate or falsify a digital footprint, in contrast to the usual personal information provided in loan applications.
More specifically, a determined scammer could theoretically set this up to some degree. However, this approach would not be sustainable because it requires time and effort to register a new email address with each service, and some of SEON’s methodology produces time-stamped results that are nearly impossible to fake.
Due to the scale and real-time delivery of digital footprinting, credit scoring checks are now feasible even in underbanked markets. For instance, in order to weed out fraudsters by evaluating the applicants’ digital presence, FairMoney, a neobank that serves Nigeria—a nation with a sizable unbanked population—overlaid SEON’s digital and social lookup with device fingerprinting.
This is a method for obtaining alternate information about your candidates in real-time so that you can decide more wisely. Let’s examine the three methods SEON uses for digital footprint analysis to apprehend scammers.
On to digital footprinting with email analysis. This module assists you in verifying the authenticity of an email address by searching 50 online platforms and social media sites for profiles related to the email address through deep social media profiling and domain verification. It also discloses any publicly available user photos, whether the email address has been included in blacklists or data breaches, and more.
You have two options for integrating the Email API into your risk tech stack: the SEON Dashboard or API calls for manual email lookups.
[SEON examines if the address has been used on 50 online and social media sites, including Booking, Twitter, and Facebook. com, Airbnb, and other websites, and extracts data to calculate a risk score]
You can also check multiple email addresses at once:
You should be more worried about the second user in light of these risk scores.
This module verifies, among other things, that the phone number submitted is legitimate, that it is used for messaging, and that it is associated with social media and messaging accounts.
[It’s safe to assume that this user’s phone number is real because their risk score is zero]
This module allows you to determine the customer’s location, the source of their connection to your website, and whether or not they are using Tor, a proxy, or a VPN to mask their identity:
[It’s safe to assume that this user doesn’t use a proxy and that they genuinely reside in London]
When you put the pieces together, you’ll see that the data points these modules reveal are not only indicators of applicant affordability but also a potent predictor of fraud risk.
An Asian microlending company served as an example of this.
By utilizing the email and phone modules to investigate their users, SEON assisted them in determining that 275 percent of defaulting customers did not have a social media presence. As a result, they started to exercise greater caution whenever they came across loan candidates who fit this description.
Overall, digital footprinting will help you:
- learn more about borrowers based on their online presence
- build more precise risk profiles based on single data points
- enable dynamic, lightweight profiling without sacrificing security
- potentially save on your KYC costs by pre-screening applicants
More Sources of Intel on a Loan Applicant
Extending beyond the digital footprint analysis we previously discussed, which enables us to generate an almost uncrackable profile of your client, SEON’s anti-fraud solution leverages information about an individual’s device, location, and behavior.
This analyzes data on the borrowers’ devices that were used to access your lending and is a component of SEON’s Fraud API. It lets you:
- flag suspicious devices like emulators and VPNs
- link users who may be involved in fraudulent activities if they are sharing devices.
- observe users’ actions over time and keep an eye out for instances when they seem suspicious overall.
In the interim, the system can also highlight default and custom fields and modify their risk scores for applicants, letting you know which aspects you’ve found crucial. In fact, if you decide to use the whitebox machine learning risk rules, SEON can take care of this for you.
Furthermore, advanced banking fraud detection software will take the user’s actions into account in relation to time. As an elementary illustration, the presence of several distinct applications on the same device in a single day may indicate a fraudulent scheme.
Compliance & Regulatory Concerns
It is crucial for lending businesses to maintain good relations with legislators, particularly if they are involved in the startup and fintech industries. Don’t overlook compliance when looking for a fraud prevention strategy that works for you. Always find out if using a product will put your business at risk for non-compliance.
At SEON, we comply with GDPR and SCA regulations and have obtained ISO 27001 certification. Reduce Risk with SEON.
Join forces with SEON to use advanced APIs, real-time data, and machine learning to lower risk and fraud rates in your company.
Online Loan Fraud Trends in 2023 and Beyond
According to Allied Market Research, the value of the global digital lending market is expected to increase from $12 6 billion in 2022 to $71. 8 billion by 2032. Due in large part to the digital revolution and changes in small- and medium-sized business (SMB) lending practices during the COVID-19 pandemic, the market has already experienced tremendous growth.
The loan fraud landscape has changed along with the online lending industry. Some of the latest trends to watch include:
Synthetic ID Fraud Keeps Growing
The Federal Reserve reports that fake ID fraud is the form of fraud that is expanding the fastest in the US, costing billions of dollars every year. Due to the US’s heavy reliance on static personally identifiable information, like social security numbers, this trend is especially problematic.
Government-Backed Business Loan Fraud Will Continue
After the flood of government emergency loans brought on by COVID-19, business loan fraud became an increasingly serious issue. This is a persistent risk due to the ongoing economic problems in many countries.
Digital Customer Onboarding Must Evolve
There is no shortage of contemporary methods available to fraudsters to evade KYC checks, including deepfakes, massive data breaches, and biometrics hacking. Digital customer onboarding needs to change to take into consideration the fact that fraudsters will continue to adopt new techniques and technologies.
SEON’s Prevention Against Loan Fraud Risks
Apart from effective underwriting procedures, the risk of loan fraud can be reduced by accurately constructing a profile of each applicant based on their device configuration and the personal data they provide, such as their IP address, email address, and phone number.
Beyond identity verification tools and data from device fingerprinting, SEON combines this intelligence with potent real-time digital footprint analysis from 50 online sources and social media.
Through thoughtfully created modules, social lookup and device fingerprinting both assist you in improving the KYC information of borrowers. Let’s take a closer look.
Sources
- Link GDS: How Banks
- Credit Connect: Bank account and loan fraud soars in pandemic
- Banking Exchange: Lenders’ Risk Mitigation Is Critical in the Face of COVID-19 and Synthetic Identity Fraud
- BusinessWire: To Combat Fraud, the Federal Reserve Has Released a Synthetic Identity Fraud Mitigation Toolkit.
- Experian: In the first half of 2021, bank account fraud in the UK skyrockets.
- CoreLogic: Mortgage Fraud Trends Report
- PR Newswire: A CAGR of roughly 11% is anticipated for the digital lending market. 9% during the forecast period (2020 – 2025).
- Financial Times: To avoid state Covid loans, small businesses in the UK are considering declaring bankruptcy.
Malicious loan applicants are identified by means of both automated data-drive risk assessment and manual examination by qualified risk specialists. When a loan application is submitted online, software detects any obvious data outliers, such as differences between the applicant’s apparent address and IP geolocation. A human loan risk assessment team then reviews the data and decides whether to approve the loan, usually after following up with a call or request for more information.
In the United States, loan fraud carries a maximum 30-year prison sentence and fines of up to $1 million, depending on the type, jurisdiction, and extent of the fraud.
Speak with a fraud fighter.
Co-founder and chief operating officer of SEON is Bence Jendruszák. Under his direction, the business was granted the largest Series A in Hungarian history in 2021. Bence has a strong interest in cybersecurity and how it relates to corporate success. (When he’s not making dubious coffee for his colleagues, you can find him hosting webinars with prominent figures in the industry on subjects like machine learning, identity verification, and iGaming fraud.)
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FAQ
What are the examples of loan fraud?
In the SAR filing sampling, typical fraudulent activities linked to this category include identity theft, fraudulent flipping, appraisal fraud, and five straw buyers. Reports of identity theft were often made in connection with suspected mortgage loan fraud.
What is considered personal loan fraud?
requesting payment in full before providing services or allowing you to review the documentation requesting payment using a prepaid card, cash, cryptocurrency, or any other untraceable means Calls or texts from purported government agencies asserting that you owe money Loan offers that are made over the phone.
What type of crime is loan fraud?
Loan fraud is seen as a form of identity theft since it necessitates the theft and use of personal data. Leasing or loan fraud ranked as the fourth most prevalent identity theft category in 2020 [*]. There are several ways for scammers to obtain your personal information.
Read More :
https://www.aura.com/learn/loan-fraud