Frictionless lending: the Secret to Thriving in a Competitive Market

In the fast-paced world of personal finance, consumers are attracted to lenders who allow faster and more frictionless access to credit. In response, the landscape has shifted to include extending loans without pulling credit–sometimes to those with low credit scores who would not have been deemed creditworthy previously. This is made possible by online personal loan providers, “buy now pay later” lenders, cash advance apps, and payday alternative loans, all of which have gained tremendous popularity in recent years. 

Many lenders in the alternative lending space have also increased their focus on financial inclusion to provide credit to consumers marginalized due to factors such as low income, geographic location, or lack of proper documentation.

Borrowers with low credit scores or those worried about the effect of a credit pull are drawn to these lenders. With the highly competitive nature of online lending and multiple options for consumers, lending companies are now fighting more fiercely than before to win borrower business–often at the expense of exposing themselves to greater fraud and risk. 

The Threat of Fraud Makes Frictionless Lending Difficult

While consumers are demanding a more frictionless lending experience, the threat of fraud makes this a difficult proposition for lenders.  There is a dizzying array of fraud risks that lenders have to manage with each and every loan they approve. This includes identity theft, synthetic identity, income misrepresentation, employment fraud, and loan stacking.

Identity theft and synthetic identity are increasing as criminals shift their focus from defrauding pandemic-related government loan programs back to the private sector.  Point Predictive analysis determined that 78% of the synthetic identities identified by auto lenders in 2022 were associated with likely-fraudulent Payroll Protection Program (PPP) loans in 2021. 

Cybercriminals are also targeting loyalty/incentive programs and retirement accounts, leading to more account fraud losses in general. As identity thefts and data breaches increase across the board, the need for identity verification continues to grow. Fraudsters can now bypass common verifications by easily switching online profiles, devices, IDs and IP addresses. Even physical state IDs and paystubs are easy to obtain online. 

Risk Is Increasing As Lenders Expand Their Footprint

As lenders expand services to a larger population, including thin-file and credit marginalized consumers, they assume greater risks–because the insights from traditional data sources, such as credit bureaus and large data providers, are limited or non-existent. To make good lending decisions and manage risks, these companies will increasingly need to rely on alternative sources of data. 

Another consideration to keep in mind is that even if an applicant can present a credit score, these scores don’t account for the baseline information required for lenders to make a sound lending decision: verification of the consumer’s identity, employment, and income—all of which can help safeguard the lender against fraud. 

How to Safeguard Against Fraud in Today’s Risk-Riddled Environment

Lenders need to perform strong identity verification using techniques such as one-time passcodes to known mobile devices to ensure the customer is who they claim to be. They also need to verify consumer employment quickly and efficiently without incurring huge fees and ensure income validation from a trusted third-party source. 

Given the instant gratification of present-day processes, borrowers demand that these verifications happen quicker– and lenders prefer them to be more cost effective. Hard pressed to find such solutions, lenders often resort to shortcuts to enable such a frictionless, cost effective experience. But with Point Predictive, that’s no longer necessary. 

Point Predictive: the Future of Safer, More Cost-Effective Lending

Point Predictive provides insightful, actionable data flags, fraud alerts and data elements from its proprietary data repository about consumers, including over 23 billion data points and personally identifiable information (PII), covering more than 65 million US adults who have accessed credit in any form over time. 

By validating information against this database—which also provides a machine learning model-generated score for fraud risk—lenders can verify if the consumer has engaged in fraud or displays other telling signs that may signal higher chances of early default. It also provides flags related to employment and income and allows the use of strong identity verification.

Lenders can access Point Predictive’s IncomePass™ solution to validate income-related information quickly and easily. 

IncomePass helps you to: 

  • Improve conversion rates by 50%
  • Remove friction by bypassing paystub requirements for low-risk applicants
  • Make more confident lending decisions with greater speed and accuracy
  • Decrease loss and risks from income misrepresentation and paystub fabrication
  • Determine which borrowers need to provide additional proof of income and which ones can proceed directly into origination 

For lenders that are expanding their consumer base or want to decrease early payment defaults due to fraud, Point Predictive solutions are a must-have addition to existing data sources. In many cases, it may even replace other sources of data. To learn more about our solutions and which ones are right for you, book a free consultation with our solution experts. 

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