Markets regulator SEBI is considering extending the use of an expected loss-based rating framework for municipal bonds, aiming to provide a more comprehensive risk assessment.
The proposal, outlined in a consultation paper, suggests that credit rating agencies may use this framework alongside the existing standardised rating scale.
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Currently, expected loss-based ratings are used primarily for infrastructure-related instruments, offering an additional measure of credit risk beyond traditional ratings. SEBI noted that since urban local bodies and municipalities primarily issue bonds to fund infrastructure projects, adopting this framework could improve transparency for investors.
The expected loss-based rating system combines the probability of default with the potential loss if a default occurs. SEBI believes this approach, when used alongside standardised ratings or probability of default assessments, can give investors a clearer picture of recovery prospects in case of financial distress.
“Including expected loss ratings along with the standardised rating scale and probability of default ratings can enhance the assessment of municipal bonds. This is particularly relevant as municipalities raise funds for infrastructure development," SEBI stated in the paper.
If implemented, the move could lead to a more refined credit risk evaluation for municipal bonds, similar to the methodology applied in infrastructure financing. SEBI has invited public comments on the proposal until April 18.
Separately, SEBI is also reviewing norms related to the disclosure of technical glitches by brokerage firms, according to three sources who spoke to NDTV Profit. The regulator is exploring ways to simplify these disclosure requirements, people familiar with the matter said.
A technical glitch refers to any malfunction in a stockbroker's systems, whether related to hardware, software, networks, processes, or electronic services. Such disruptions can arise from multiple factors, including cyberattacks, inadequate infrastructure, or deviations from normal operations.
(With PTI inputs)
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