Regulator for housing finance firms NHB has asked housing finance companies with asset size of over Rs 1,000 crore to adopt an early warning signals (EWS) framework to check financial frauds and also to prevent accounts from turning into non-performing assets.
National Housing Bank (NHB), in a recent circular, said analysis of the frauds reported by the housing finance companies (HFCs) has revealed that the reasons behind accounts being identified as fraud accounts are seller impersonation, submission of fake income/ employment documents, submission of fake title deeds, a collusion of the builder and borrower.
It has also been observed that such deficiencies are identified only when the borrower stops paying the EMIs after the disbursement of the loans, NHB said.
"It has been therefore decided that an Early Warning Signals (EWS) Framework should be adopted by the HFCs so that an alert is triggered before the account turns into non-performing asset (NPA) or declared as a fraud account," it said.
NHB circular further said that tracking of the EWS must be integrated with the credit monitoring process in the systems of the HFCs so that it becomes a continuous activity.
Through the EWS framework, HFCs will be encouraged to take into account fraud risks in their risk management practices.
NHB has asked the housing finance companies to place the circular before their boards for information and to devise an implementation strategy.
"The mechanism needs to be put in place by April 1, 2024," it said.
The NHB has provided an indicative list of EWS for individual borrowers (retail). This includes 'disbursement of loan done without meeting all pre-disbursement conditions', 'occupation of the borrower has changed', 'adverse developments in the sector in which the borrower is employed', and 'company is unable to contact the borrower during credit monitoring'.
The regulator has also suggested an indicative list of EWS for corporate and project loans.
(Only the headline and picture of this report may have been reworked by the Business Standard staff; the rest of the content is auto-generated from a syndicated feed.)
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