It's one thing for financial sector regulators to promote prudence by flagging signs of excessive speculation in any area of the securities market; it's quite another to label a class of shares as inherently risky.
It's one thing for financial sector regulators to promote prudence by flagging signs of excessive speculation in any area of the securities market; it's quite another to label a class of shares as inherently risky.
A class of shares includes various individual companies, some of which might become the next Infosys, Kotak Mahindra Bank, or ITC. It would be grossly unfair to lump these potentially successful companies with failures like the next Satyam Computer or Dewan Housing Finance. It's crucial to distinguish the viable from the non-viable, separating the good from the bad and the ugly.
Analysts at mutual funds, brokerages, and rating agencies are engaged in the task of sifting through the universe of companies to identify the diamonds in the rough, mixed with less promising entities. Despite their efforts, this screening process often falls short, whether due to insufficient effort, lack of data, or unreliable data. As a result, potential success stories are overlooked, and unmerited achievements are prematurely celebrated, only to fail later.
What could analysts do to get a more realistic grasp of the actual financial health of companies, short of acquiring clones of Charlie Munger, if not of Warren Buffet, who could reputedly smell out good companies to invest in?
To improve their analysis, analysts need access to relevant and reliable data on a company's finances, customer base, sourcing base, and the risks and growth prospects associated with these elements.
Before China's infamous tech crackdown, Ant Financial's success model, as it prepared for what was expected to be the world's largest initial public offering, had served as a case study. Positioned alongside China's largest marketplace, Alibaba, Ant Financial was able to observe business-to-business (B2B) and business-to-customer (B2C) transactions, assessing each company's customer and sourcing bases, sales, procurement sizes, and financial health. It developed algorithms to process this data into credit scores, which it then used to lend to these companies. What started off as a way to finance, and thereby promote sales on Alibaba, grew into a giant non-banking finance company.
How can Indian analysts access the kind of data Ant harvested from Alibaba? Through account aggregators.
India is one of the few countries in the world to have a ready framework for collecting financial activity data across various domains—tax, savings, investments, credit, online purchases, payments—through the India Stack's consent layer, which utilizes Aadhaar-based APIs (application programming interfaces).
With the permission of the data subject, all such information can be procured from different agencies, identified, in this context, as financial information providers, and thereafter, collated and presented to financial information users.
This data, representing cash flows in different contexts, complete with data on GST paid and GST credit availed of, can provide an analyst with a picture of the health of an enterprise far more current and far more reliable than an annual report for the preceding year.
All that needs to be done is for companies that want to get listed to give their consent to their compiled financial information to be provided to financial analysts, who would, in turn, need to be recognized as financial information users.
Account aggregators, licensed to compile and provide financial data, play a crucial role in ensuring the integrity of this data exchange. Sharing data with them does raise privacy concerns, but this transparency is part of going public. In exchange for access to public investment, companies must disclose their financial data, including real-time significant developments, to the public and regulators.
India has 60 million-odd enterprises, of which some 11 million are registered for GST, but fewer than 7,000 are listed, assuming minimal overlap between the National Stock Exchange and the BSE. Clearly, millions more companies could benefit from public capital, as could investors seeking profitable investment opportunities.
However, access to formal finance is a prerequisite for generating reliable financial data, implying that small companies must have credit relationships with non-banking finance companies, if not banks.
Financial inclusion, it would appear, matters not just to the small companies who get access to formal finance, but also to savers seeking avenues for profitable deployment of their savings.