THE AI REVOLUTION IN THE GLOBAL BUSINESS LENDING LANDSCAPE: TRANSCENDING CONSUMER-BASED DIGITAL LENDING TO TRANSFORMING SME AND CORPORATE BORROWER CREDIT ASSESSMENT AND UNDERWRITING, March 2025

Written by Admir Imami, Chairman at Zvilo

In the past decade, lending has evolved, with digital platforms simplifying processes, particularly for individual borrowers. However, the real revolution lies not in process digitalisation, but in how AI can transform the way business lenders assess and underwrite loans for SMEs and corporations.

After a period of unprecedented growth, the global market is expected to increase from $7.5 billion at the end of 2024 to $65.5 billion by 2033 (a robust CAGR of 27.20%). This surge can be attributed to the rapid adoption of digital solutions to streamline processes and enhance customer experience. AI has been a massive proponent of boosting predictions; due to just how much it exponentially improves each of these factors.

For business lenders, AI enhances not just speed but also the ability to pull from multiple data sets to assess risk, trends, and creditworthiness, all of which are vital for business lenders and SME and corporate borrowers alike. This unlocks new lending opportunities for businesses that might have been overlooked in the past.

In leveraging this power to navigate the range of contemporary business lending complexities, AI can enable more efficient operations and faster, more accurate decision-making in support of the working capital needs of its international clients.

Consumer vs. Business Lending: Access and Efficiency Are Not Enough

From mortgages and car loans to personal loans, modern digital lending platforms have made consumer borrowing easier to access and more efficient by eliminating endless paperwork required to collect static data points, multiple in-person meetings, and automating much of the application process. Recent AI innovations have also improved consumer borrowing through features and tools like customer service-focused chatbots, fraud detection tools, and personalised loan offers based on a consumer’s preferences or past behaviour. But there is more to AI than just process.

AI’s transformative power in the business lender-to-borrower realm is less about process digitalisation and more about enabling more accurate risk analysis, which is central to credit underwriting decision-making.

The Challenges of Business Lending: Complex, Shifting Data Points, Decision Making, Assessing and Mitigating Risk

Business loans require a broader range of information, and the data points themselves are simultaneously dynamic, distinct, and interconnected. While financial statements, tax filings, cash flow projections, and information on industry trends are all essential pieces of the puzzle, SME and corporate financial health can fluctuate due to management decisions, external market conditions, environmental, political or pandemic-related disruptions, and new regulatory frameworks, among other factors. Many borrowers find themselves excluded from traditional lending channels or are forced to pay higher interest rates and pledge more collateral due to perceived risks.

Resilience and real-time access to working capital are central to this, with clients needing greater working capital support to drive successful and sustainable growth. Having the support needed from digital lending platforms that can leverage extended technologies to boost navigation in today’s operating environment is therefore key.

AI-Powered Lending: A Game-Changer for Business Lenders and Borrowers

1. Dynamic Risk Assessment

AI can evaluate complex, shifting data points by continuously monitoring changes in a business’s financial health, market conditions, geopolitical shifts, international logistics, and a host of other factors that could influence creditworthiness. AI can track cash flow patterns, profitability trends, and even macroeconomic indicators that might signal potential risks or opportunities.

2. Real Time Decision Making

AI can process data in real time, supporting quicker, more informed decisions. Whether it’s a change in a business’s cash flow or a new development in the market, AI systems can quickly adapt to these shifts, recalculating risk levels and making underwriting decisions more agile and responsive to lender responsibilities and borrowers’ working capital needs.

3. Improved Risk Profiling

One of AI’s biggest strengths is its ability to spot patterns in data that might be overlooked by human analysts. By identifying these patterns, AI models can create more accurate risk profiles for borrowers who may not have a long track record of credit history but show promise through other dynamic factors. AI can evaluate risk more holistically, factoring in a range of data to predict future business performance.

4. Beyond Traditional Metrics

AI also opens the door for analysing non-traditional data points—something especially useful for SMEs. For example, assessing the strength of a business’s social media presence, customer reviews, or those of its competition, as well as other non-financial indicators, can help lenders look beyond financial statements. This provides a better sense of the business’s performance within its community of clients or consumers, and its ability to weather associated challenges, given its clients’ commitment to the product or service it offers. 

The Future of AI in Lending, Digital or Otherwise

As the business lending landscape continues to evolve, the role of AI in assessing business creditworthiness will only grow. By empowering lenders to analyse data in new and innovative ways, AI is not only improving the accuracy of loan decisions but also expanding access to capital for underserved businesses across both developed and emerging markets, unlocking new lending opportunities to businesses that might have been overlooked in the past.

Of course, as AI becomes more integrated into lending processes, there are important regulatory and ethical considerations to keep in mind. It’s crucial to ensure fairness and transparency in AI models to prevent bias and foster trust in these new systems. The industry must establish robust standards for responsible AI use, balancing the benefits of innovation with the need for accountability.

Paving the way for the future of lending

AI is undeniably adding a new dimension to the business lending landscape—digital or otherwise. While consumer lending has already reaped the benefits of digitization, it’s AI-powered underwriting for SMEs and corporations that is truly paving the way for the future of business lending. By leveraging AI to assess complex, dynamic data points, lenders can offer more precise, real-time credit assessments, reducing risk and expanding access to capital. As AI continues to advance, we can expect these improvements to accelerate, making it easier for businesses of all sizes to secure the financing they need to grow and succeed.

Here at Zvilo, harnessing the power of AI is already front and centre in how we currently operate and plan to do business. Invoz, Zvilo’s proprietary digital platform, is already leveraging AI in critical tasks like invoice reconciliation and review for maximum scale while simultaneously supporting rigorous and efficient risk and fraud management. Zvilo’s proprietary platform, Invoz, will further leverage AI as we seek to scale credit underwriting capabilities by strengthening our internal, continuously calibrated credit rating system, aptly named Z-score.