In an era of increasing loan volumes, auto finance lenders face numerous challenges, from lengthy approval cycles to the need for efficient credit evaluation. Outdated manual workflows and staffing shortages further exacerbate these issues. However, the solution lies in automating the motor finance lending process. By leveraging automation, lenders can reduce risk and cost while providing customers with faster approval cycles.
Vehicle lending fraud is a rising issue
So let's talk about compliance and risk. As the cost of living crisis continues to soar throughout the UK and beyond, the harbingers of financial products are increasingly under attack from fraudsters who seek to take advantage of the holes in manual application review processes to secure financial products that they cannot afford or have no intention of paying back.
Within the motor finance sector, false application fraud has emerged as a significant concern. In the UK, CIFAS, the fraud prevention service, reported a 16% increase in false application fraud cases in 2022 compared to the year before. This fraud involves individuals altering or providing false bank statements or wage slips to inflate their income, aiming to appear more creditworthy.
Identity fraud is another pressing issue affecting car and automotive lenders. CIFAS reported a significant 43% rise in identity fraud cases in the same reporting period, compared to the previous year. Fraudsters exploit various techniques, including identity document verification, and current and previous address fraud, to secure vehicles on finance. These fraudulent activities impose long-term challenges for lenders and necessitate robust identity verification processes.
Homeppl’s Fraud Finder technology can see precisely where edits on submitted bank statements and ID documents have taken place. For example, in the below video, an applicant provided a fake address on their bank statement. Unbeknownst to the document editor, we can see and display every single document edit to uncover the document’s original form:
Fraud Finder has recently been updated to run these similar fraud tests on IDs and passports:
Ensuring that auto finance lenders are exposed to as minimal fraud as possible.
Park manual. Drive automatic
Putting cheesy automotive puns aside, automation in the car loan approval process is essential in 2023. Manual underwriting reviews are subject to human error. Auto lenders today grapple with evaluating creditworthiness due to pandemic-related loan forbearance programs, furlough payments and varying employment spikes and shortages have made sustainable credit checks more complex, muddied even further by a surge in refinancing. Moreover, staff shortages and the requirements to cut costs have strained lenders, necessitating a more streamlined approach. Automation in motor finance lending offers a competitive advantage by reducing the manual toll on operations teams by fishing out fraudulent applications and assessing affordability instantly.
With the click of a button, an applicant’s recent financial behaviour can be analysed and supported in a quicker, more reliable underwriting decision.
In this example, Fraud Finder combines three bank statements provided by an applicant to show our lender key analytics surrounding: opening balance, credit balance, overdraft usage and spending patterns throughout the month:
Digitally evaluating essential documents such as payslips, bank statements, and ID documents paves the way for enhanced efficiency. AI-powered document automation extracts pertinent information from electronic documents, cross-references data, and validates its accuracy.
Additionally, automation systems like Fraud Finder can instantly identify and verify an applicant's net income, even when diverse employment profiles are spread across multiple documents, providing lenders with a clear picture of an applicant's cash flow.
Automating the vehicle financing process leads to a shorter processing time per application. How long does it take for your underwriters to manually review a bank statement, authenticate an applicant’s employment status and salary and calculate their affordability? It’s an extremely difficult process to scale especially when each added document review presents the opportunity for human error.
With AI and Machine Learning algorithms, car financing automation systems like Fraud Finder can assess a range of international documents from 000s of banks simply because the system always learns as it validates, reducing friction and bottlenecks presented by strange-looking documents that manual underwriters haven’t seen before. Homeppl has assessed close to a million financial documents and is well-equipped to authenticate statements from around the world.
And what does this mean for your customers? The end users benefit tremendously from the shift in gear that automating the lending process provides. Streamline the approval process, reduce paperwork, and deliver faster decisions.
Streamlined approval process:
Gone are the days of lengthy approval cycles and cumbersome paperwork. With automation, borrowers can experience a streamlined approval process that saves time and effort. Digital document capture and management eliminate the need for physical paperwork, reducing the administrative burden on both borrowers and lenders. The elimination of manual data entry and verification allows for a faster and more accurate assessment of loan applications, expediting the decision-making process.
Reduced paperwork
Automation eliminates the reliance on stacks of paperwork traditionally associated with motor finance lending. Borrowers no longer need to navigate through piles of documents, making the process more convenient and user-friendly.
Faster decisions
With automation, borrowers can expect faster decisions on their loan applications. Automation systems extract relevant information from digital documents, validate its accuracy, and perform cross-referencing to verify employment and address details.
Fostering financial inclusion in auto finance
Automation in motor finance lending not only streamlines processes and improves efficiency but also has the potential to foster financial inclusion. By reducing bias and enhancing fairness in credit evaluations, automation can open doors for individuals with a limited credit history or unconventional employment profiles, providing them with access to financing opportunities.
Reducing bias in credit evaluations
Traditional lending processes often rely on subjective assessments and manual decision-making, which can introduce biases that disproportionately affect certain individuals or communities. Automation mitigates these biases by implementing standardised evaluation criteria and data-driven algorithms.
By leveraging advanced technologies such as machine learning, automation systems can analyse vast amounts of data, including alternative data sources, to assess creditworthiness objectively. This shift towards data-driven decision-making minimises human biases and ensures that credit evaluations are based on accurate and relevant information.
Enhancing fairness and access
Automation levels the playing field by considering a broader range of factors beyond traditional credit metrics. It can incorporate alternative data sources such as utility payments, rental history, or educational background to assess an individual's financial capabilities more comprehensively.
This approach benefits individuals with limited credit history or unconventional employment profiles, who may have previously struggled to access financing due to rigid lending criteria. Many of the standard credit referencing agencies in the UK struggle to assess the creditworthiness of applicants who have thin or no UK credit files. These profiles typically include individuals who have been historically marginalised, such as immigrants, low-income earners, international applicants, or those with limited access to traditional banking services.
Automation can break down barriers by leveraging fraud and risk technology to assess creditworthiness based on a comprehensive understanding of financial behaviours and capabilities. By incorporating alternative data, lenders can extend financing options to these underserved communities, enabling them to purchase vehicles and improve their economic mobility.
In a nutshell
By embracing intelligent automation solutions, lenders can streamline their operations, mitigate risks, deliver an improved lending experience for both customers and underwriters as well as promote financial inclusion whilst doing so.
With the right automation tools, lenders can adapt to changing market dynamics, enhance efficiency, and make more informed lending decisions. As the industry continues to evolve, embracing automation will be crucial in shaping the future of motor finance lending.
What to read next:
A guide to lending fraud detection
How people commit document fraud
How we identify fake bank statements and payslips in seconds
The top ways mortgage lenders verify bank statements
Most fraudulent bank statements of 2023
What to listen to:
Podcast: Technology, innovative credit assessment and creating financial inclusion
