Not every financial theory and statistical model continues to remain relevant half a century after it was presented, but the Altman Z Score can claim that feat. Built back in 1968 by Edward I Altman, then a professor at New York University the model is still being used across the world.
It helps predict the possibility of a business going bankrupt. And that perhaps explains why Altman is considered an authority in bankruptcy prediction.
What was initially developed for large manufacturing companies has slowly evolved over the years for companies across sectors, across the globe, and eventually into a Z score for small, privately owned businesses.
To put the SME Z Score into commercial use, Altman co-founded Wiserfunding with his colleague Gabriele Sabato. The aim of the company is to standardise accounting and evaluate principles for small businesses across the globe. As a part of its endeavours, Wiserfunding, which already operates in 65 countries, has entered India.
The startup has set up an office in Mumbai and plans to hire 25 employees in the first year and keep doubling the count over the coming years. In its launch press release, the company spoke about investing around $5 million in the country and working with several banks and non-banking finance companies (NBFCs) to implement their SME Z score.
Moneycontrol caught up with Professor Altman, who is currently the Max L Heine Professor of Finance, Emeritus, at the Stern School of Business, NYU; Sabato, who is the CEO of Wiserfunding; and Avantika Goel, who heads its India business. The trio explained their vision in evaluating small businesses and where India stands with respect to the global SME financing opportunity in a post-COVID world.
Edited excerptsQ: Why do you think the Z score continues to remain relevant even today?
I am extremely surprised that something that we built 50 years ago is popular even today. I think the secret to its longevity is three factors: first, it is a simple analytical tool involving five commonly found financial measures which helped distinguish between healthy and unhealthy companies. Second, it continues to be quite accurate, ranging between 80 to 90 percent accuracy for large companies. And third, it is free. Anyone can use it, test it, and if they do not like it, throw it out.Q: Why did you think about developing a Z score separately for SMEs?
The original model was mainly for manufacturing companies. Then, I realised there are many companies which are not publicly traded and there is a need to build models for private companies as well. We built a second-generation model in 1995 for emerging markets.
Fast forward to 2015 and the Italian stock exchange reached out to me to build a model for small companies issuing mini bonds. These are lesser known businesses, and investors were looking for some transparent accurate models to evaluate them. I reached out to my colleague Gabriele Sabato to help me build this model. He was with the Royal Bank of Scotland then and used his free time in the evenings and over weekends to help me in this project.
The stock exchange liked the model very much and is using it even till this date.Q: Is that how you decided to start a company and commercialise the model?
After the success in Italy, we decided to incorporate this company, Wiserfunding, in 2016 and started this as a business. Now, in addition to the original model, we have come up with two additional modules to the final scoring system for SMEs. One uses artificial intelligence, primarily social media data, combining that with corporate governance data. Second, we get in macro data, data about the country, GDP, data about the sector. We realised all the modules combined added a lot of value.Q: How familiar are you with India and our financial systems?
I must say I am very well acquainted with the Indian ecosystem. I have a colleague who served as the deputy governor with the Reserve Bank of India (Viral Acharya), with whom I have regular conversations. I have been travelling to India since 1989. It was in 2018 during a lecture tour here that the chief risk officer with one of the largest banks in the country approached me with the SME funding problem bankers were facing here. That was the time there were a lot of bankruptcies even among large corporates, across sectors. While we had no idea about COVID-19 then, we knew that there was risk building up in the SME space. We were encouraged then to build a model for SMEs in India. We have started testing our generic model here and I can say with confidence the model works with a very high degree of accuracy here.
Q: COVID19-induced lockdowns have affected cash flows of many small companies. How do you think this will affect SMEs’ ability to attract funding?
Altman: Going into COVID-19, the world, including India, was heavily leveraged, particularly the corporate sector. So, anyway a lot of bankruptcies were expected, going into a downward cycle. Now, as countries reopen, we have seen in the US, sectors like leisure, oil and gas, telecom and restaurants have been hit very hard. Then, will small businesses in risky sectors get shut out from formal financing? We think that under such circumstances our models can actually help SMEs get credit. While financials are important, we need to stress on other data points to evaluate how these companies will be able to repay. If the stress test shows viability then we can say that even after COVID-19 these companies will pay off.Q: So how do you evaluate small businesses?
There are two ways through which these companies can be looked at. One is the idiosyncratic risk for a single company; how are their financials and how prepared are they to face the next economic crisis. The second is a systemic risk that looks at the macro-economic context within which the company operates. Since Dr Altman was predicting a downturn we designed our models in a way that could include these two elements. The pandemic has given us a competitive advantage in the market.
Altman: The banker can collect data around the expected cash flow, profitability and other financial metrics of the businesses, input those into our model and get a result which predicts the possibility of success for the business. Regulators stress-test the banks; we are stress-testing companies on behalf of the banks. Our Z score model not only evaluates the company but also gives a bond rating equivalent and also shows the probability of default, up to as much as 10 years. This helps bankers get that confidence when they are looking to lend to these companies.Q: How is India doing in terms of technology innovations and where do you see scope for improvement?
On the technology front, the country is doing really great. I think in terms of payment systems, the country is a pioneer and as a result you have the ability to tap data even at company levels and individual levels. I think one problem in India is that regulations, relatively speaking, continue to be heavily bureaucratic.Q: Which are the business segments you’re targeting in India?
In India, we are looking at small and medium businesses, not micro businesses. We don’t focus too much on startups, because we need a financial history since it helps us get the high accuracy ratio. We have separate models for construction, manufacturing, retail and other industries.Q: Which lines of business can use your model: supply chain financing or term loans?
If I look at the client base in Europe, we have a lot of non-bank lenders where they are doing all sorts of lending, be it secured or unsecured lending, property lending and even credit cards. Non-bank lenders are more interesting to us since they are more tech enabled. But interestingly, in India, we have seen higher conversion among banks.Q: While lenders are trying to make their process more data driven, industry insiders say that the availability of structured data is a big problem. How do you wish to address that?
This is not a problem only in India; it is a problem globally. Even in Europe and the US, we have faced this problem while trying to automate our models. In India also, we are trying to automate most of our models. We are partnering with banks and NBFCs and trying to use the huge amount of data that they are sitting on to simplify, automate and test our assessment models for Indian SMEs. We are looking to tie up with accounting software companies so we can directly source data from them. But I think overall there is a lot of movement in India with regards to digitisation of data, which will help businesses like ours.Q: Recently, another UK-based company, ClearScore, exited the India market. How do you wish to make money here?Goel:
We are a software as a solution business working with lenders. We are a revenue-generating company and are in advanced talks to deploy our solution with a large bank and that deal will get announced soon. We are already generating some revenue here and our cost structure in India is also very low. We plan to invest in setting up technology teams in the country as well. Our business is run by academics so the goal is slightly different; we are a profit making body but also looking to create a change in the ecosystem.