How AI and Technology are Revolutionizing SME Lending | Faster Loan Approvals

How Technology Can Revolutionize SME Lending

Small and medium-sized enterprises (SMEs) form the backbone of the UK economy. According to the Federation of Small Businesses, there are around 6 million SMEs in the UK, contributing to 52% of the private sector’s total turnover. These businesses employ 16.3 million people across Britain, making up 61% of the total employment. Despite their critical role, SMEs face significant challenges when accessing finance, which has only intensified with recent economic conditions.

Challenges Facing SME Lending in the UK

A survey conducted by the British Business Bank reveals a notable increase in the use of finance by businesses in 2023, largely due to cash flow pressures. While cash flow remains under strain, credit cards and overdraft finance have seen greater use. Interestingly, gross bank lending to SMEs in 2023 was down, but still ranked as the third-highest on record, while gross repayments were the second-highest after 2022.

However, despite this availability of finance, SMEs are suffering the most. In several recent surveys, numerous problems have been identified in the lending process for SMEs in the UK:

• 1. Gross bank lending to SMEs declined by 9%, with banks becoming increasingly cautious about businesses' ability to repay loans.
• 2. Over the past decade, traditional banks have exited many parts of the lending market, allowing non-bank lenders to step in and serve SMEs. This has resulted in more options but also a fragmented landscape.
• 3. Regional disparities persist, with entrepreneurs in some regions facing greater challenges in accessing finance.
• 4. SMEs are increasingly looking at multiple finance providers, as reliance on a single lender decreases.
• 5. More than 25% of SMEs accepted finance even when the amount offered was lower than what they had requested.
• 6. The economic downturn has led to a rise in small business closures.

Role of Open Banking and Non-Consented journeys

Open Banking has emerged as a revolutionary concept among lenders to access customers information via secured APIs with their consent. But this journey is not smooth for customers as they are reluctant to share their personal information. This becomes a challenge especially for the lenders which must disburse cash in a timely manner as it can be a make-or-break situation for the SMEs.

Traditional document collection remains popular despite open banking and many times borrowers upload documents such as VAT, Bank Statements for proving their financial stability.

Lenders must find a way to balance the benefits of both journeys. It is here that the role of AI-enabled technology for document processing or Document AI becomes important.

The Role of AI-enabled technology in Addressing These Challenges

While non-bank lenders have provided some relief, traditional banks remain a critical player in the SME lending space. However, to truly address the gaps in the market and support SMEs, lending practices need to evolve—and this is where technology can play a transformative role.

One of the most promising technological advancements for SME lending is the use Document AI. Document AI can benefit the lenders in the following ways:

• • Document extraction and classification: One of the most time-consuming tasks in lending is manual document processing. AI-powered tools can extract data from loan applications, tax documents, and other critical paperwork automatically. This reduces the error rate and speeds up the approval process especially in the cases of manual uploads regarding non-consented journeys.
• • Underwriting automation: AI algorithms can automate underwriting processes, ensuring loans are evaluated more efficiently while maintaining compliance with regulatory standards. This automation significantly improves the turnaround time for loan approvals, making it easier for SMEs to access the financing they need.
• • Fraud detection: AI-driven predictive models can detect suspicious patterns in financial transactions, helping to prevent fraud in real-time
• • Risk modelling: AI can evaluate a company's creditworthiness more efficiently than traditional methods by analysing vast amounts of financial data, identifying patterns, and predicting future risks.
• • Data management: With the growing volume of financial data, AI enables organizations to process and analyse information at unprecedented speeds, ensuring that critical insights are extracted quickly.

Conclusion

As the economic landscape continues to evolve, SMEs in the UK will need greater access to financing to thrive. While the current lending environment presents several challenges, the integration of AI and other advanced technologies can make SME lending more efficient, accessible, and equitable. AI will transform the process of lending in SMEs by reducing the time to access funds for SMEs, help improve speed and efficiency for the lender. Digilytics offers AI-enabled solution for document processing through its product RevEL which improves the turnaround time for SME lender to approve funds. As economy and open banking bring new challenges, lenders that embrace AI-led innovations will not only help SMEs but will also position themselves to compete in an increasingly digital financial landscape.

Author: Akshat Dev, Partnership Development Strategy at Digilytics AI

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