Week ending 2nd May 2026

# 1 Markets

1.1 Indian equities rebounded early in the week, with Nifty 50 reclaiming 24,000 and BSE Sensex gaining 600+ points, aided by easing U.S.–Iran tensions. India VIX cooled with DII support offsetting FII selling. However, sentiment turned on Apr 30 as crude spiked to ~$120 and INR hit record lows, dragging indices ~1% lower (Sensex 76,913; Nifty 23,998) despite a sharp intraday recovery.

 

1.2 It may be interesting to note that despite corrections, India’s elevated market cap-to-GDP (~138%) looks less like a classic bubble and more like a structural re-rating driven by formalisation, deeper financialisation, and stronger corporate profitability—unlike the leverage-fueled 2007 peak. That said, with “easy” valuation gains largely behind us, future returns will hinge on earnings delivery, while near-term risks persist from potential earnings downgrades and energy-linked macro pressures.

 

1.3 The three broad U.S. indices finished last week with a split performance, as tech-heavy momentum once again outpaced the broader industrial market: Nasdaq an outperforms with 1.1% increase, closely followed by S&P500 at 0.9%. Late-week rotation into defensives lifted the Dow Jones Industrial Average as investors turned cautious.

1.4 Indian bond yields surged to a multi-week high last week, with the 10-year benchmark breaching the 7% psychological mark to close at 7.01% on Thursday. This hardening was driven by a perfect storm of $120+ crude oil prices, a record-low Rupee, and hawkish signals from the U.S. Federal Reserve, which overshadowed stable domestic policy rates.

1.5 U.S. Treasury yields surged to their highest levels of 2026 last week, with the 10-year yield breaching 4.40%. Fed last week held rates but signaled sticky inflation and deep policy divisions, casting doubt on the timing and certainty of future rate cuts.

 

# 2 RBI/Banking

2.1 RBI issued revised Master Directions on Provisioning norms on April 27, 2026.

The Core Change: Incurred Loss → Expected Credit Loss

Until now, banks followed the incurred loss approach, recognizing bad loans only when a default actually happened. Under the new ECL approach, a lender must look into the future to estimate what losses an asset is likely to incur and build buffers accordingly — before a default even occurs. The framework introduces a three-stage classification system that links provisioning directly to deterioration in credit risk:

 

• Stage 1: Assets with no significant increase in credit risk → 12-month ECL provisioning
• Stage 2: Significant increase in credit risk → lifetime ECL provisioning
• Stage 3: Credit-impaired assets → lifetime ECL provisioning

A rebuttable presumption applies that credit risk has increased significantly when contractual payments are more than 30 days past due.  The existing 90-day NPA rule is retained alongside this — so the ECL staging layer is additive to current NPA norms, not a replacement.

 

How ECL is Computed

Banks are required to estimate expected credit loss as a probability-weighted average of credit losses under different scenarios, incorporating forward-looking information including borrower-specific factors and macroeconomic variables. The three key parameters are Probability of Default (PD), Loss Given Default (LGD), and Exposure at Default (EAD). Banks must also adopt the Effective Interest Rate (EIR) method for income recognition, with loans outstanding as on March 31, 2027, required to transition to EIR by March 31, 2030.  The revised framework builds provisioning buffers while bringing transparency besides aligning global alignment.

 

Impact on Indian Banks

• Shift to ECL may shave up to ~120 bps off CET-1 ratios, but impact can be amortized over 4 years.
• Strong capital buffers (~14% CET-1) and provisioning cushions should absorb the transition without weakening credit profiles (per CRISIL Ratings).
• Incremental provisioning hit largely driven by Stage II assets, though low system share (~2–2.2%) limits overall impact.
• Expanded scope (incl. off-balance sheet exposures and undrawn limits) will lift total provisions.
• ECL implies a structural uptick in credit costs, especially for Stage III and early delinquency assets.
• Profitability remains supportive (RoA ~1.25–1.3%), but banks must protect NIMs and control opex.
• Large private sector banks are likely to be better placed as the transition impact would be lower, given provision buffers of 2–4% of net worth.

This is a structural upgrade for Indian banking — moving from a reactive, backward-looking provisioning system to a proactive, model-driven one. While it will create short-term pressure on profitability (especially for PSU and mid-tier banks), the 4-year capital transition relief and strong current capital buffers make the shift manageable.

 

2.2 As per CRIF-Highmark report released last week,

• New to Credit [NTC] borrower base grew to 4.4 crore (FY26) from 3.6 crore (FY22), ~5.1% CAGR, reinforcing its role in credit expansion
• However, contribution to loan originations fell to 17.8% (from 23.5%), reflecting more selective/risk-calibrated lending
• Strong rural/semi-urban traction: >50% originations beyond top 100 cities
• Women’s participation rising; share up from 33% → 41%, signalling deeper financial inclusion
• NBFCs dominate (>60%) NTC lending; banks remain relatively cautious
• Entry products led by small-ticket loans: consumer durables (32%), followed by gold and two-wheelers
• Young borrowers (26–35) drive most originations; younger cohorts dominate personal & two-wheeler loans

 

• Credit behaviour improving: ~67% migrate to low/very-low risk within a year

Despite tighter underwriting, the NTC segment remains a structural driver of inclusive, geographically diversified credit growth with improving borrower quality.

2.3 Why Indian Banks are nervous on Anthropic’s “Mythos”?

Anthropic recently unveiled Claude Mythos, its most advanced AI model yet. It was designed for defensive cybersecurity — meaning its original purpose was to help find and fix security weaknesses in software before hackers do. Think of it like hiring the world’s best locksmith to check if your house locks are weak — so you can fix them before a burglar finds out.

So, what’s the problem?

The problem is what this AI found and how fast it found it.

Anthropic’s own team claims Mythos can find and exploit zero-day vulnerabilities (previously unknown security holes) in real-world software. Their red team reportedly found vulnerabilities in every major operating system and web browser, with over 99% of those flaws not yet patched (fixed).  Even more alarming: engineers with no formal security training were able to use Mythos to generate complete, working exploits — code that could allow a bad actor to run malicious commands on a remote computer — simply by asking it.

In plain language: a non-technical person could potentially use this AI to hack systems they have no business accessing.

Why are Indian banks specifically worried? Banks are worried because:

• Their IT systems run on the same software (operating systems, web browsers, servers) that Mythos has already found holes in.
• Bankers are worried about the model’s ability to find many bugs quickly and the difficulty of fixing them in real time. Imagine someone finding 100 holes in your wall faster than you can patch them.

Has it already been misused?

Yes — and this made things worse. Hackers reportedly gained access to Mythos through a third-party vendor, even though Anthropic had restricted it to a small group of vetted companies. So fear is no longer just theoretical — the tool has already leaked outside controlled hands.

Anthropic built a super-smart AI to find security holes in software — but it works so fast and so well that if it falls into wrong hands, banks and other critical systems could be hacked before anyone has time to fix the vulnerabilities. Indian banks are essentially racing to patch their systems before someone uses Mythos-like capabilities against them.

2.4 RBI last week issued final directions on Basel III capital charges for credit risk, effective April 1, 2027. Key takeaways:

• The limit for applying a 150% risk weight on unrated exposures to corporates and NBFCs has been increased to Rs 500 crore (up from the initially proposed Rs 200 crore).

 

• The RBI has removed the requirement for higher risk weights on exposures that moved from “rated” to “unrated” status.
• The proposed Standardised Credit Risk Assessment [SCRA] -based grading for unrated bank exposures has been scrapped.

 

• • Unrated exposures now carry a flat risk weight of 100% for long-term and 50% for short-term exposures.
  • Indian branches of foreign banks can now use the parent bank’s external credit ratings to determine risk weights.

 

• The “Regulatory Retail” category now includes all small businesses (including non-MSMEs) with a turnover of up to Rs 500 crore.

 

• • The maximum exposure per counterparty to qualify as “retail” has been raised to Rs 10 crore (up from Rs 7.5 crore). fund-based & non-fund exposures qualify; 75% risk weight if criteria met
  • individuals/small businesses (≤ ₹500 crore turnover), standard retail products, ₹10 crore cap per borrower, diversified pool (≤0.2% per borrower)
  • Home, term, education loans, and small business credit
• Most personal loans, revolving card balances, capital market, derivatives, real estate-linked loans kept out → higher capital requirements
  • unsecured personal loans & revolving cards at 125%; other non-qualifying retail exposures at ~100%
  • Housing loans: LTV-based framework with lower 20–40% risk weights for individuals
  • Higher risk for concentration: multiple home loans and real estate exposures penalised 100% (residential), 150% (commercial)

Overall, RBI norms sharpen risk-sensitive capital allocation—rewarding disciplined retail credit while tightening buffers on riskier segments.Top of Form

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# 3 SEBI

3.1 SEBI introduces a fast-track PPM mechanism for AIFs to accelerate scheme launches and capital deployment. Key features:

• • AIFs (excluding large value funds for accredited investors) can launch schemes and circulate PPMs 30 days after filing, unless SEBI raises objections.
  • Removes pre-launch approval bottleneck—replaces detailed upfront review with post-filing observation window.
  • Responsibility shifts to merchant bankers and AIF managers for due diligence, disclosures, and compliance.

 

• First-time fund managers can launch only after registration or 30 days from filing (whichever is later).

 

• • Any SEBI observations within 30 days must be addressed before launch.
  • AIFs must achieve first close within 12 months of becoming eligible to launch.
• Filing a PPM does not imply SEBI approval; regulators disclaim responsibility for disclosures and manager performance.

A pragmatic shift by SEBI that speeds up AIF launches while clearly pushing accountability onto managers and Merchant bankers.

 

3.2 SEBI’s PaRRVA: Putting Performance Claims Under the Microscope

SEBI has operationalised PaRRVA (Past Risk and Return Verification Agency), ending the era of unaudited performance claims by investment advisers, research analysts, and algo-trading service providers. Full operations begin May 4, 2026.

 

• Market intermediaries have long advertised returns and win rates backed by nothing more than their own word. PaRRVA mandates independent verification before any such claim can be used in client communication or advertising.
• Intermediaries register with PaRRVA, submit performance data, and receive verification against actual market records. Only authenticated data can then be publicly cited. CARE Ratings serves as the verification agency; NSE acts as the data centre, bringing established credibility and infrastructure to the process.

Investors can now distinguish verified track records from marketing claims. Intermediaries with strong performance gain a credible stamp; those relying on inflated numbers face new accountability. Few countries have a similar framework this broad, covering all categories of financial service providers — making this a potentially significant regulatory benchmark globally.

 

PaRRVA doesn’t just raise the bar for transparency — it removes the option of not clearing it

# 4 Economy

4.1 As per data released last Tuesday,

• IIP rose 4.1% YoY in March (5-month low), down from 5.1% in Feb; FY26 industrial growth edged up to 4.1% (vs 4% FY25), indicating broadly stable momentum.

• • Weaknesses in electricity and manufacturing, alongside higher input costs and supply disruptions linked to West Asia tensions caused slowdown.
• Sector performance:
  • Manufacturing: Growth slowed to 4.3% (from 5.9%);
  • Mining: Improved to 5.5% (from 3.1%)
  • Electricity: Slowed sharply to 0.8% (from 2.3%)

 

• Use-based trends (mixed demand):
  • Capital goods (+14.6%), infrastructure (+6.7%), intermediate goods (+3.3%)
  • Consumer durables (+5.3%), primary goods (+2.2%), consumer non-durables (+1.1%) → signals soft mass demand

 

• Investment-linked sectors are driving growth, while consumption remains uneven.

Industrial growth is holding up better than feared but slowing momentum and weak consumption signal rising vulnerability amid global uncertainties.

4.2 Summary of the key observations and conclusions in RBI Bulletin “State of Economy”

• Global economic activity hit an 11-month low in March as momentum weakened across manufacturing and services.

• While domestic activity showed overall resilience, select indicators like port cargo, air passenger traffic, and core industry production showed signs of slowing.
• Demand remained strong in rural areas, and automobile sales grew, supported by post-GST momentum and increased EV adoption.

• The trade deficit narrowed to a nine-month low in March due to an expansion in exports and a contraction in imports.
• Foreign Portfolio Investment (FPI) was volatile with net outflows in March and April, though Net Foreign Direct Investment (FDI) turned positive in February.
• Favorable summer sowing for pulses and oilseeds was noted, but possible El Niño conditions pose a downside risk for the upcoming south-west monsoon.
• The all-India unemployment rate declined slightly to 3.1% in 2025 from 3.2% in 2024. However, March 2026 saw a temporary increase in unemployment across both rural and urban areas.

The Indian economy remains resilient with improving trade balances, yet faces significant headwinds from multi-year high energy prices (US$ 118.4/barrel) and geopolitical-driven supply chain disruptions

# 5 PE/VC

5.1 As per Venture Intelligence report released last week,

• PE-VC investments in April 26 fell 32% YoY to $1.9B ($2.8bn); deal count dropped 124 → 87
  • Primary drag: Delayed IPOs (esp. large tech) and weaker pre-IPO funding amid global uncertainty and valuation concerns
  • Investments down ~60% vs March 2026 (120 deals $4.7bn vs 87 deals @ $1.9bn) which was boosted by mega deals
• YTD 2026 – No of deals were 435 at $ 12 bn.
• Stage-wise trend:
  • Early-stage: Funding rose ($166M → $253M) despite fewer deals (53 → 40)
  • Growth-stage: Deals fell (44 → 26); funding largely flat (~$520M)
  • Late-stage: Funding declined sharply ($653M → $376M)
• Average deal size declined overall, though early-stage cheque sizes increased

IPO delays and valuation caution are shifting PE-VC momentum away from late-stage toward selective early-stage bets.