After a turbulent few years of the Covid-19 pandemic, followed by high inflation worldwide, SMEs are desperately in need of finance. But access remains a challenge. The global funding gap is estimated to be $5.2 trillion a year, according to data from the World Bank. This is where data-driven lending can help – an approach taken by an increasing number of alternative lenders. We believe traditional banks could also benefit from a data-driven approach by leveraging leading technology platforms such as those by SAP Fioneer to expand their existing financing offers.

The hurdles SMEs face in getting the funding they need from banks

The lack of funding is partly due to the traditional approach taken by lenders, often focusing on collateral-based lending. The limitation of this approach is that it excludes potential customers who have high creditworthiness and a strong business but do not have sufficient collateral for a loan.

The issue is compounded by current methods of credit assessment, which are centred around traditional financial documents, such as balance sheets. These documents provide a backward-looking view of a company’s performance or, at best, an indication of the current situation. In addition to that, standard policies, such as the common “we only lend to SMEs that have had an account with us for months or years”, prevent SMEs from getting the funding they need.

However, when it comes to managing credit risk, lenders could significantly improve their success by relying on alternative data instead of these arbitrary, often outdated, “one-size-fits-all” rules.

The limitations of collateral-based lending

Collateral-based lending is where a borrower offers up assets as security against a loan. It gives the lender reassurance that if the borrower defaults on the loan, they have an assets to seize to potentially recoup their money.

But there are a number of challenges that SMEs face when obtaining finance via this approach.

  1. Lack of assets to offer as collateral. Because the value of the asset determines the size of the loan, it leaves an SME with little funding options if they do not have tangible assets (or the right assets, often property) to offer.
  2. A time-consuming process. It will likely take months for the loan to be approved, as the lender will need to value the asset and prove its worth. For example, a commercial mortgage, where banks lend against the value of a building or premises, can take months to arrange.
  3. Intense search for suitable lenders. With collateral-based lending, many SMEs, despite having strong credit and viable business propositions, find it difficult to secure loans. This forces them to spend significant time and effort in search of banks willing to offer funding.
  4. Increased complexity and costs. A collateral-based approach comes with enormous running costs for banks, as their operations need to handle collateral across asset classes and regions. This ultimately increases costs for SMEs, leading to higher interest rates and fees.

Supporting SMEs in their growth journey is a win-win situation for all. SMEs fuel economies by fostering employment, driving innovation, and boosting economic growth through enhanced productivity. By adopting alternative lending approaches, banks not only facilitate SMEs’ access to finance but also augment their own revenue streams. In essence, when SMEs thrive, economies prosper, and banks reap financial benefits.

The rise of data-driven lending

Data-driven lending arises as a formidable response to the limitations of collateral-based lending. This approach hinges on the thorough analysis of key business metrics around  revenue and equity, cost and debt, and growth to assess a borrower’s creditworthiness. Banks adopting such lending strategies set specific eligibility criteria – e.g., industry, revenue, profit margins, and other pertinent ratios, including debt to equity, which are integral to their lending decision. They ultimately base their credit decision on a deep understanding of a business and an industry, instead of relying on an asset they can seize in case a lender defaults.

Banks often already have access to such data points and might also consider external data, e.g., credit scores or industry-specific data, e.g., customer satisfaction ratings for e-commerce businesses. The evaluation of these various data points provides a comprehensive assessment of an applicant’s potential to repay the loan timely and according to the lender’s terms.

Conclusion

Data-driven lending has many benefits for banks and SMEs. Lenders have a wider pool of potential borrowers to loan money to, as a tangible asset may not necessarily be required for collateral. They are also likely to get a more complete profile of an applicant through analyzing better data (i.e., “traditional” data they already have and additional and alternative data) to determine a borrower’s creditworthiness.

SMEs with limited assets have a higher chance of obtaining a loan as a stronger focus on data helps them in proving that they have the ability to repay a loan. This way, it becomes easier for a lot of SMEs to grow and expand to new markets or employ more people, ultimately driving economic growth.

Alternative lenders are more likely to take this data-driven approach, but traditional banks are increasingly embracing the power of data as they see significant revenue opportunities. For example, ING in Germany teamed up with Amazon to offer loans to Amazon sellers, who by and large are SME businesses, by analyzing business data available to Amazon to underwrite loan amounts of up to €750,000. And traditional banks have a clear advantage over alternative lenders when it comes to reputation. SME customers are likely to trust them more when it comes to sharing data if they can see a clear benefit to them. For example, sharing their recent transactional data may help them appear more favourable to borrowers, resulting in a higher loan or a lower interest rate.

Start your data-driven journey with the right partner at your side

To better serve SMEs and secure their own long-term success, banks must adopt data-driven lending strategies. At SAP Fioneer, we help banks provide better access to funding and more tailored finance offers for their SME prospects and customers.

Find out more here about how traditional banks can learn from alternative lenders to win more SME customers.

 

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