Helping banks better serve SME customers to support growth

Small and medium-sized enterprises (SMEs) are key to a more sustainable and inclusive world. Data from the World Economic Forum (WEF) shows that SMEs and their supply chains contribute up to 90% of global business. Yet SMEs find it more difficult to secure lending than large organizations, and many rely on alternative sources, such as personal savings or loans from family and friends to set up businesses.

So how can traditional banks better serve SME customers, particularly at a time when many are facing turbulent market conditions, including high interest rates, market volatility and the rising cost of borrowing?

Scale of the problem

SMEs continue to face significant challenges due also to the complex regulatory environment. This includes responding to the rise of sustainable finance and navigating socio-political instability, which may affect the international credit risk landscape. In addition, the flow of credit to SMEs has been impacted by changes in general monetary policy and fiscal stimulus from central banks across key geographies.

According to estimates from the International Finance Corporation (IFC), cited by the World Economic Forum (WEF), 65 million firms, or 40% of formal micro, small and medium enterprises (MSMEs) in developing countries, have an unmet financing need of $5.2 trillion every year.

Addressing these challenges requires financial institutions to leverage new and adaptable tools and technology to serve SME lending needs much more efficiently. Potential benefits include increased access to data-driven insights, quicker identification of new financing opportunities, improved credit pricing discipline, and faster, more efficient loan processing.

AI integration and innovation

The use of AI in the banking industry is progressing rapidly and is being leveraged across various use cases including customer experience, operational efficiencies, and productivity improvements. How can banks start to use AI to enhance risk and credit management in SME lending?

One of the main challenges is that the data used to assess the creditworthiness of individual SMEs is often unstructured and varies significantly from one business to another. AI can quicken the process of reviewing prospective lenders’ documents and other sources, which can be time-consuming due to the extensive information required to make loans available without risking late payments or defaults. This information can include both structured and unstructured data, such as bank statements, reports, tax returns and invoices.

Another valuable application for banks is using AI for portfolio and risk management. For instance, a bank can diversify SME loans across different sectors based on the outlook for those sectors, thereby spreading risk profiles and avoiding over-reliance on a particular industry or segment.

There are still concerns about whether the outcomes of large language models (LLMs) used by GenAI can be trusted; however, banks can implement strong governance frameworks to ensure that AI outcomes are explainable and free from bias.

Advancements in AI technology facilitate the monetization of previously underutilized data. This enables firms to offer data-driven insights across the credit issuance landscape, enhancing aspects such as pricing and capital allocation, and improving the setting of provisions. Additionally, AI supports a more automated underwriting process while maintaining a ‘human-in-the-loop’ approach, thereby providing a unique and differentiated customer experience.

Simplified servicing

From a technology perspective, there is an opportunity to modernize underlying platforms to enhance efficiencies and reduce redundancy and loss. By making lending and loan servicing processes more efficient, banks can not only reduce operational costs but also create a platform that supports a more integrated ecosystem.

Banks have recognized that their SME customers want more joined up, end-to-end business services, but perceive these as too difficult or expensive to provide. By collaborating with other providers,  banks can increase the ‘stickiness’ of SME customers. This collaboration allows banks to ingest more data about their customers to support credit decisions and build a larger platform that makes credit more accessible.

In some markets, such as India, banks are rapidly developing ‘super apps’ that SMEs increasingly expect to use. Meanwhile, financial institutions in other regions are taking advantage of the current high-interest rate environment to replace siloed legacy systems and invest in AI-infused technology, anticipating a potential loss of income when interest rates eventually fall.

Historically, the SME lending market has been slow to innovate, relying on manual processes that are inefficient and error-prone, especially when servicing high volumes of smaller loans. Adopting a ‘Simplified Servicing’ approach, which automates previously manual tasks, aims to speed up processing times, improve accuracy, reduce risk and enhance transparency by breaking down silos in the lending process. As a result, this approach can unlock more routes to finance for SMEs, providing them with the banking services they need to succeed.

Opportunities in a changing landscape

The evolution of the SME and Corporate bilateral lending industry presents both challenges and opportunities for financial institutions. These changes create avenues for establishing new partnerships and innovative ways to manage credit risk, potentially leading to increased revenues across a more diversified credit portfolio.

At a time when banks face increased competition in the SME lending space from new market entrants – including firms in the private credit, fintech and insurance sectors – they need to shift their focus from merely delivering transactions to building deeper relationships with SMEs. This approach should be geared towards the overall success of the business.

SMEs are increasingly looking for banks to take on the role of trusted advisors, providing a wider range of services such as business expansion planning, legal, accounting, and audit services. In regions like India, SMEs are turning to fintechs and niche private players for these services. However, traditional banks can leverage their expertise in servicing and packaging deals, as well as risk management, to help organizations in the private credit market. This can be achieved by establishing partnerships and new business models for warehouse financing and loan servicing.

The implementation of AI-infused digital lending platforms will be one of the most significant initiatives, enabling banks to focus on customer acquisition and retention, rather than just productivity gains. These platforms can streamline processes, provide data-driven insights, and enhance the overall customer experience.

In conclusion, the prevailing political and economic climate will continue to impact the pace and scrutiny of financial regulation and the pressures on both bank and non-bank balance sheets. While these market forces are beyond the control of banks and their SME customers, what will make a difference is how banks respond to current and emerging challenges. By harnessing the power of technology, interoperability and modernisation such as AI, banks can build new models and lending policies that support the growth and sustainability of SMEs moving forward.

To listen to a recent webinar on this topic, including Finastra, IBM and Celent, click here.

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