Alternate data in SMB lending risk management & monitoring

Traditionally, financiers relied on data derived from conventional sources such as annual company reports or quarterly credit bureau reviews to make business decisions. But as market volatility and competition increase, lenders now need ways to gauge a borrower’s business health more instantaneously. This is where alternate data comes into the picture. Far from being just an industry buzzword, alternate data gives financiers faster and more complete counterparty insights. Importantly, the value of such non-traditional information in SMB lending risk management and monitoring can be found on both sides of the aisle. On the one hand, it gives financiers the ability to unlock newer market segments and on the other, it gives businesses better access to crucial financing.


A computer screen with a trend graph that is derived using alternate data
Alternate data gives financiers faster and more complete counterparty insights

The need for better SMB lending


SMBs are the backbone of the economy. In the US, they account for about 44% of the national GDP and create thousands of jobs annually. Globally, it represents over 90% of the corporate population and accounts for 55% of the GDP. Despite being such an integral part of society, however, SMBs face multiple growth challenges, chief among which is limited access to credit. As of December 2021, SMB business loan approval rates sat at 14% for big banks and 20% for small banks. Alternative and institutional lenders performed better with an approval rate of around 25%. This unfortunately means that a vast majority of businesses are unsuccessful in securing the financing needed to stay afloat and grow – a funding gap that amounts to over $5 trillion globally. This is not just bad news for SMBs alone, but for financiers who miss out on growth opportunities too. It also spells trouble for the broader economy as stagnation in business growth, directly and indirectly, stifles economic expansion.


Key constraints in SMB lending


In lending circles, SMBs are considered ‘thin-file’ applicants – they do not have the requisite credit information needed for financiers to assess creditworthiness in the traditional sense. Most traditional-based banks have a mile-long, set-in-stone lending checklist. These require applicants to have healthy personal and business credit scores, sufficient amounts of collateral, and robust balance sheets that go back several years – all of which can be hard for an evolving small business to procure. Such rigid criteria can often set the bar too high for an SMB to clear. What’s more, they are designed to mostly reward those with an established track record and not those in the nascent stages of business building.


The Solution – Alternate data


Alternate data is information that is essentially nonfinancial in nature. Despite its nonfinancial status, however, such data can have a definitive bearing on an entity’s finances and can therefore be used to assess its present and future creditworthiness. Some examples of alternate data include:

  • Public news feed data

  • Social sentiment data

  • Customer review data

  • Credit and debit transactions

  • Web traffic analytics

As most of the global economy can be found online today, data of this kind is now widespread and readily available. What’s more, most businesses today leave behind a digital footprint that can be analyzed for risk insights. This is particularly advantageous for ‘thin-file’ entities. By leveraging this all-pervasive data, financiers can easily augment and sometimes sidestep traditional benchmarks of creditworthiness. In addition, using such real-time data in conjunction with advanced analytics makes the credit underwriting and monitoring process more up-to-date and efficient.


4 advantages of using alternate data in SMB lending risk management & monitoring


1. A more comprehensive evaluation of business health


Traditional financial metrics do not provide a complete picture of business health. For example, a company’s P&L statement can tell you that profits are down for the quarter, but it cannot tell you why that is so. Alternate data helps bridge this information gap by assessing non-quantitative metrics such as brand sentiment and customer loyalty. Such non-quantitative performance indicators are crucial value drivers of business health. Assessing them provides much-needed context and allows financiers to read between the lines.


It also gives lenders crucial risk insights that could otherwise have been missed by perusing only financial statements. A prime example of this is Greensill, a supply chain financing company, that despite having great financials went bankrupt in March 2021 due to a loss in reputation. So, by using alternate data, financiers can perform both quantitative and qualitative risk assessments, giving them gap-free risk analysis and a more holistic picture of their borrower’s business health.


2. Better risk prediction


Risk prediction can be a double-edged sword. Getting it right leads to timely risk reduction and bigger profit margins. Getting it wrong, however, could result in colossal losses. Accuracy in risk prediction is therefore of paramount importance. Unfortunately, such accuracy is tricky to achieve with traditional methodologies that primarily use only historical financial data to predict risk. That’s because, as the name itself suggests, historical data comes from the past. It is a lagging indicator that informs you of past business performance. And, as the pandemic amply proved, just because a company did well in the past does not necessarily mean that it will continue to do so in the future.


For risk predictions to be more accurate, financiers must include leading indicators of business health such as is found in alternate data. Several studies have shown that using nonfinancial and alternate information in risk prediction models significantly improves their accuracy. This includes a study by FICO that demonstrated how combining traditional and alternate data made for more powerful and reliable risk modeling than depending on only one or the other.


3. Improved decision-making, monitoring, and fraud detection


One of the key attributes of alternate data is that it is, for the most part, created externally. Other than PR pushes, businesses have very little control over what is written or said about them in the digital world. Conversely, as seen recently with companies such as Wirecard, Hin Leong, and Luckin Coffee, financial reports can be manipulated by fraudulent-minded individuals. By the time someone gets suspicious and takes a closer look at the numbers, it is often too little too late in terms of de-risking.


Analyzing alternate digital data helps financiers stay in the know and improves their ability to monitor changes in counterparty business health. Crucially, it equips financiers with early warning signs of business distress. For example, Hin Leong filed for bankruptcy in April 2020 after investigations into the company revealed longstanding fraud. The TRaiCE platform's proprietary Early Warning System detected signs of business distress several months before any of this happened. The graph below shows the company's sentiment score dropping steadily 6 months prior to the bankruptcy, alerting users early and giving them ample time to reduce exposure.

A sentiment trend graph from TRaiCE that showed Hin Leong's sentiment score dropping months before its bankruptcy
TRaiCE detected signs of business distress with Hin Leong several months before it went bankrupt

4. Expand revenue and market share


SMBs represent an enormous opportunity for lenders who are looking to grow their revenue and expand their market share. As we touched on earlier, alternate data provides lenders with pertinent and granular information on businesses, even on those with little to no credit history. These extra insights can help lenders assess a borrower’s capacity and intent to repay even without traditional barometers of creditworthiness. This in turn can lead to higher approval rates in a market segment that is traditionally overlooked. In addition, with real-time information at their fingertips, financiers can craft more personalized services and products that meet the current needs and repayment capacity of their customers.



Conclusion


SMB financing and alternate data go together like pieces of a puzzle. While in times past, getting financing was a struggle for smaller businesses, the ubiquity of alternate data today has ensured that this no longer need be the case. It adds tremendous value to borrowers and lenders alike by paving the way for financial inclusion and augmenting the decision-making process with real-time intelligence. By leveraging it, lenders get more thorough and complete risk management and monitoring process.


Want to know more about how to access and extract actionable insights from alternate data? Get in touch with us or simply schedule a demo today and we will be happy to walk you through it all.


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