Better use of data could help small caps and their investors flourish

livemint.com:

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