In the world of small business lending, every decision has a price, especially when it comes to denying loan applications. In today’s unpredictable market, it’s not just about granting loans but also understanding the hidden costs tied to declined applications.
According to the 2023 Report on Employer Firms: Findings from the 2022 Small Business Credit Survey by the Federal Reserve Banks, as pandemic-specific funding programs have wound down, there’s been a surge in businesses applying for traditional loans, lines of credit and merchant cash advances. But while approval rates have increased year-over-year, they still haven’t rebounded to pre-pandemic levels, suggesting a higher volume of declined applications.
How much do these declined applications cost small business lenders? Every rejected application is more than just a missed lending opportunity. It’s also an expenditure of time, effort and resources. In short, the longer a lender evaluates an unqualified applicant, the less time they dedicate to quality applications.
Addressing this inefficiency is crucial to ensure that your lending company’s resources are strategically allocated, maximizing both profitability and customer satisfaction.
The high cost of miscalculating an applicant’s financial health
Understanding an applicant’s financial health provides a key insight into their ability to repay a loan and make informed decisions; small business lenders need a full picture of an applicant’s financial situation.
While traditional credit reports give a snapshot of applicant creditworthiness, they can only provide a partial perspective. Small business owners, especially those in the early days of ownership, may not have an extensive credit history. This makes it challenging for traditional credit checks to show their financial situation accurately.
Detailed bank data provides a deeper view of businesses’ cash flow than credit data alone. Cash flow lending analysis enables lenders to get a detailed picture of an applicant’s financial health by illuminating insights including their income, expenses, debt-to-income ratio and more.
Cash flow analytics not only enable lenders to discern cash flow seasonality but also evaluate unconventional income sources, assess debt capacity and identify recurring transactions. This holistic approach to risk analysis enables more accurate predictions of default risks, ultimately boosting returns and expanding credit accessibility.
The power of document automation in small business lending
In a landscape where declined applications not only lead to missed opportunities but also cost time and money, streamlining and automating processes is key.
Instead of manually sifting through stacks of paper applications or disparate digital files, lenders equipped with automation tools can instantaneously retrieve, organize and assess necessary documents. These tools can also automatically study how money flows in and out, sort different types of transactions, pinpoint various income sources and much more.
While traditional methods often overlook key details, document automation tools help lenders recognize the seasonal patterns of cash flow, evaluate income sources that aren’t typical, and measure how much debt can be handled.
In such a fast-changing industry, developing accurate credit models is crucial to anticipating risks and optimizing returns in such a fast-changing industry. Document automation technology like Ocrolus enables small business lenders to easily aggregate data from multiple sources and create cash-flow-based models that precisely predict the risk of default.
How to leverage AI and machine learning for advanced financial insights
AI and ML have revolutionized the lending landscape, helping lenders uncover hidden financial relationships that might otherwise go unnoticed.
By sifting through mountains of data and discerning patterns and connections that could escape the human eye, these tools give small business lenders a deeper understanding of potential risks and offer a holistic view of an applicant’s financial health.
By analyzing historical data, these tools can also predict an applicant’s future financial behaviors, particularly in response to shifting economic climates. This foresight equips lenders with invaluable insight to tailor loan terms that align with the borrower’s unique circumstances.
At the same time, by automating repetitive tasks and calibrating risk assessments in real time, ML and AI help expedite small business lending decisions. This helps ensure lenders remain in step with their strategic objectives and make informed lending decisions while maintaining operational costs.
Efficiently and accurately identifying unqualified borrowers
Effective risk management demands a thorough understanding of a borrower’s financial landscape. Document automation technology like Ocrolus offers an efficient and intensive examination of a business’s financial behavior, revealing more than just credit scores.
While AI systems allow financial teams to quickly and accurately review and identify information, more is needed to speed up decision-making. It also means mistakes from manual reviews are less likely. Letting technology handle document processing means lenders can be sure they’re making choices based on solid and dependable info.
Lenders can better gauge the associated risks and sidestep potentially unsuitable candidates by highlighting intricate financial patterns, diverse transaction types, and distinct revenue sources. These tools significantly speed up the loan application review process without sacrificing accuracy, helping small business lenders make more informed decisions to mitigate losses while optimizing resources.
In the ever-evolving world of small business lending, accurately assessing and managing risk is a cornerstone of success. By harnessing the power of cutting-edge tools and technologies, lenders can fine-tune their decision-making processes to seize opportunities and avoid potential risks.
As the lending landscape continues to shift, those equipped with precise risk management strategies will not only survive but thrive, setting new standards for time and cost efficiency.
Book a demo to learn how Ocrolus can help small business lenders reduce the cost of declined applications.
- With AI-powered document automation and cash flow analysis, small business lenders can reduce costs by identifying unsuitable applications early in the process.
- Addressing inefficiency in loan qualification helps ensure lenders’ resources are strategically allocated, maximizing both profitability and customer satisfaction.
- Automating repetitive tasks and risk assessments can expedite and improve small business lending decisions.