MUMBAI: Even as the banks try to identify and tackle their stressed loans after the push from the Reserve Bank of India (RBI) the big four – EY, PwC, Deloitte and KPMG – are introducing algorithm based products to identify bad loans and accounts.
Industry trackers say that many banks would now have to first identify the stressed loans and then try and clean up their balance sheets. The stressed loans in the public sectors’ balance sheets would be anywhere around 10 per cent to 12 per cent as of today say industry trackers. Now as per the RBI’s direction the banks have to identify the NPAs by 31 March 2017.
However, not many banks are able to identify which of the loans are stressed or can get stressed in the coming years. Enter the consultancies who are now trying to create a business model out of helping the banks do exactly that.
“With the stringent deadline looming it is difficult for them to identify the level of inconsistencies in NPA identification process and also the extent of clean up required at their end to meet the deadline set by RBI, without automated assistance,” said Vikram Babbar, executive director, fraud investigation & dispute services, EY.
EY has recently introduced a tool — NPAccurate — that can assist banks with the NPA. These algo-based tools tend to identify and analyse the NPA scenario. Like in this case the tool could, classify non-performing assets along with appropriate provisioning that the bank has to make for it.
The mechanism being put in place by the consultancies encompasses a broader gamut of loans when compared with the early warning signals (EWS) introduced by the RBI some time ago. Under the EWS system, if a bank finds one or more of these signals then the account has to be treated as a ‘red flag account’ (RFA).
Industry trackers say that currently many banks are facing a lot of difficulties in going through their accounts. The number of loans that a public sector banks would have on their books could range from anywhere around 1,00,00 up to 10,00,000. Industry trackers say that in volume terms the NPA problem could be around Rs 4 lakh crore. However insiders say that if a thorough examination is done, the number could increase substantially.
“The key here is to not only to scrutinise a humongous set of data, but do so with a host of critical parameters in place,” said Babbar.