1 Introduction: The challenges banks face when lending to small and medium-sized enterprises (SMEs)

Small and medium-sized enterprises (SMEs) are the backbone of the economy and account for the largest share of jobs and GDP in many countries. Despite this enormous importance, SMEs around the world often face difficulties when it comes to accessing finance, especially bank loans. The reasons for this are manifold and reflect both the specific characteristics of SMEs and the challenges faced by banks. Credit assessment is the central process that banks go through to evaluate the risk of a loan default before providing capital to a company. While large companies with comprehensive financial reports, longer histories and audited balance sheets are easier to analyze, assessing the creditworthiness of small and medium-sized enterprises (SMEs) poses a particular challenge.

1.1 Poorer information situation

One of the biggest hurdles for banks when lending to SMEs is the often poorer information situation. In contrast to large companies, which can often provide comprehensive financial reports and balance sheets, banks often have less detailed or unaudited financial information from SMEs. This makes it difficult for banks to assess the actual risk of a loan default. In addition, smaller and newly founded companies in particular often do not have a long financial history that would enable a more reliable credit assessment.

For banks, this means taking a higher risk, which often leads to stricter lending conditions or higher interest rates for SMEs. In some cases, banks refuse loans altogether if the uncertainty seems too high.

1.2 Higher transaction costs

Processing and checking a loan application incurs costs for banks, regardless of the size of the loan. In the case of SME loans, these costs are often disproportionately high in relation to the loan amount. Checking creditworthiness, analyzing business figures and documenting collateral are labour-intensive, especially for smaller companies that cannot provide standardized financial reports or audits.

As the loan volumes for SMEs are generally smaller than for large companies, banks have lower margins to cover these costs. It is therefore often less attractive for banks to grant smaller loans to SMEs, as the administrative costs are high in relation to the size of the loan.

1.3 Regulatory requirements

Banks are subject to strict regulatory requirements relating to risk assessment and capital reserves for loans. After the financial crisis of 2008, the supervisory authorities tightened the requirements for banks even further. These regulations mean that banks have to hold higher capital reserves when lending to higher-risk customers such as SMEs. This reduces the profitability of such loans and makes banks more cautious, especially if the risk of loan default is considered high.

1.4 Economic uncertainty and market conditions

Economic uncertainty in certain sectors or regions can also be an obstacle. SMEs are often more affected by economic fluctuations than larger companies. In difficult economic times, such as during a recession or geopolitical uncertainty, SMEs are more susceptible to liquidity shortages, falling demand or rising operating costs.

Banks therefore see a higher risk of default, particularly in uncertain times or for companies operating in sectors that are highly susceptible to fluctuations. This often leads to a further reduction in lending to SMEs in such phases, although this is precisely when there is often a greater need for financing.

2 Common approaches to assessing the creditworthiness of SMEs and their problems

To overcome these challenges, banks have developed various approaches and methods to assess the creditworthiness of SMEs. These approaches can be divided into traditional methods and alternative, innovative approaches.

2.1 Financial ratio analysis

The financial ratio analysis is a classic credit assessment tool. Banks analyze a range of key figures, such as the equity ratio, the ratio of debt to equity, profitability or a company's liquidity ratios. These ratios provide an indication of the financial health and stability of the company. A key problem with this approach is the backward-looking nature of the information. The key figures are often calculated on the basis of the most recent annual financial statements, which relate to a period of 12 previous months. It is often difficult or even impossible to draw conclusions about future risk from these key figures alone. Another problem with the analysis of financial ratios is the selection of ratios, which in some cases allow no or only indirect conclusions to be drawn about the default risk. The information provided by these ratios often overlaps, which means that certain criteria are weighted too heavily and the creditworthiness assessment is additionally distorted.

2.2 Credit history

Another traditional approach is to analyze the credit history. Banks check whether the company or its owners have already taken out loans and whether these have been serviced on time. For existing companies, this can be a reliable indicator of future payment behavior. However, SMEs without an extensive credit history, such as start-ups, are often at a disadvantage here as they do not have a solid credit history. However, this approach does not reflect the future risk of a company, but at best only that of the owner or the past risk of the company and is therefore inadequate for the comprehensive assessment of the creditworthiness of SME.

2.3 Scoring models

Banks are increasingly relying on automated scoring models that analyze a variety of data points to calculate a credit risk. These models are based on historical data and often use algorithms to weight different risk factors and combine them into a score. These systems are particularly useful for quickly assessing a large number of applications, such as smaller loans. Scoring models are based on statistical models that allow statements to be made about the history of an extensive SME portfolio, but are not very flexible in practice and cannot take into account the specific risks of individual companies. Companies that have similar risk factors to other companies that have been insolvent in the past have little chance of obtaining a loan, even if their individual risk profile would be better.

2.4 Alternative data sources

In recent years, banks and FinTechs have increasingly turned to alternative data sources to assess the creditworthiness of SMEs. These include, for example, transaction data, tax reports, social networks, supplier data and information from e-commerce platforms. These alternative data sources make it possible to gain a more comprehensive picture of the company, especially if traditional financial reports are missing or insufficient. But it is not sufficiently adequate to comprehensively and fairly assess the creditworthiness of SME.

3 RIXOR: Innovative credit assessment from PROSYD

3.1 Individual, automated and high-quality credit assessment of SMEs

PROSYD has developed a fundamentally new and innovative approach to enable banks to assess the creditworthiness of SMEs more reliably and efficiently. The PROSYD credit scoring model comprises two risk assessments:

· Short-term default risk

· Long-term default risk

The credit risk assessment model is able to calculate with a small number of financial figures, which is usual for SMEs. Thanks to the innovative and AI-supported model, the credit scoring is reliably estimated despite a small amount of data. Inconsistencies and accounting errors can also be detected automatically. The unique feature of the PROSYD model is that it estimates the future risk. In addition, the risk is assessed on a company-specific basis. This means that each SME has a fair and individual access to credits. The credit assessment can be calculated fully automatically and can therefore help to keep transaction costs low for banks. With the PROSYD standard model, banks can assess SME credits with a high quality and low transaction costs. In case a bank needs more specic risk assessments, PROSYD offers more advanced and individual risk models, including business plans, macro-economic models and supply chain.

3.2 Credit Portfolio: Identification and early detection of risks

The PROSYD SME credit solution also includes the identification of concentration risks. The AI-supported model estimates how macroeconomic factors affect a company's default risk. By actively monitoring macroeconomic data, PROSYD's software is able to identify at an early stage which companies may run into difficulties. This enables a bank to better balance its risks in advance in the event of a economic crisis. The company-specific creditworthiness analyses also allow a fast and reliable assessment of whether and how a company can be restructured in a critical situation.

4 Conclusion

Assessing the creditworthiness of SMEs is a complex challenge for banks due to the special characteristics of this group of companies. Traditional approaches such as financial ratio analysis and collateral checks often reach their limits, especially for young or small companies without a solid financial history or sufficient collateral. Modern approaches such as scoring models and the use of alternative data sources offer new opportunities to better assess the credit risk of SMEs, but in turn reveal new problems. Banks are particularly reluctant to lend to SMEs due to the often inadequate credit checks, which – as a broad phenomenon – causes also problems in economic growth. PROSYD-RIXOR offers banks a new and innovative solution to these challenges. A forward-looking, company-specific and automatable risk assessment means that risks can be better assessed with lower transaction costs.

PROSYD's SME portfolio risk software gives banks unprecedented opportunities for risk management – making banks more resilient to an economic crisis.