Capital market regulator Securities and Exchange Board of India (Sebi) made it clear on Wednesday that companies should not interfere with the ratings methodologies and due diligence processes of rating agencies and that these methodologies were sacrosanct and need to be recorded in the prescribed manner.
The comment comes a day after the rating agencies met Sebi to discuss the issue of companies suing the agencies. It was not unusual for companies to slap legal notices on rating agencies for downgrading or assigning negative rating which, in turn, led to litigation that ate into the fees of the agencies.
“It is the bounden duty of rating agencies to inform investors about the change in the status of a company or an instrument that they have rated. So our aim will not only be to help the industry but also to ensure investors' interest is being taken care of. In the context from the feedback we received yesterday from our discussions with the rating agencies, we will be soon taking up the issues,” said Sebi chairman UK Sinha on the sidelines of the third India Securitisation Summit 2012 organised by National Institute of Securities Markets.
Sinha stated that if the companies are raising money from the general public — whether retail or institutions — they should be willing to follow the rules of the game rather than being upset if the rating is downgraded.
Sinha said he expected such companies to act maturely and not rush in dragging rating agencies to court. “I am also sure all the courts in the country are aware that if Sebi is regulating a particular industry or if a particular instrument is being looked at, they will let the due process prevail rather than come in the way,” added Sinha.
Concerning the Nifty flash trade incident on October 5, Sinha said Sebi was investigating the matter and examining the issue from all dimensions: “Sebi is trying to look at what measures are required to further improve the system and how to prevent further recurrence of such incidences.”
Sinha said the market regulator was working on measures to mitigate algo-based risks. “We