Standardised Approach for Credit Risk: Risk Weights and RWA (CAIIB Risk Management)

Every bank computing its capital adequacy ratio must first decide how it measures credit risk on its loan book, and for most Indian banks that starting point is the standardised approach for credit risk. Unlike the internal ratings-based approach, which lets a handful of sophisticated banks build their own probability-of-default models, the standardised approach for credit risk assigns risk weights using external credit ratings and regulator-prescribed buckets. For CAIIB Risk Management candidates this is one of the most heavily tested topics because it sits at the intersection of Basel III, RBI's capital adequacy framework, and everyday balance-sheet arithmetic. This article walks through risk weights by exposure class, unrated exposures, credit conversion factors, and a worked risk-weighted assets example.

🏦 What Is the Standardised Approach for Credit Risk?

The standardised approach for credit risk (SA-CR) is the method Basel III prescribes for converting a bank's on- and off-balance-sheet credit exposures into risk-weighted assets (RWA) using fixed, regulator-published risk weights rather than the bank's own internal models. Each exposure is first classified into an exposure class — sovereign, bank, corporate, regulatory retail, residential mortgage, or "other assets" — and then multiplied by a risk weight that depends on the borrower's external credit rating or on the exposure category itself.

In India, the Reserve Bank of India mandates SA-CR for the overwhelming majority of banks; only a small number of large, systemically important banks have pursued supervisory approval to move to the internal ratings-based route, and even they must still hold capital against an SA-CR-based output floor. Because SA-CR sits inside a bank's broader risk management framework, candidates should treat it as the default capital-computation engine every bank runs, with the more advanced approaches as the exception rather than the rule.

📊 Risk Weights by Exposure Class: Sovereigns, Banks and Corporates

Sovereign exposures — claims on the Government of India and the RBI in domestic currency — generally attract a 0% risk weight, reflecting the assumption of negligible domestic default risk. Claims on foreign sovereigns and foreign central banks are risk-weighted according to their external rating, following the same rating-to-risk-weight mapping tables that RBI's Basel III capital regulations prescribe.

Claims on banks are weighted with reference to the external rating of the bank itself, or in some formulations the sovereign of incorporation, and typically range from 20% for the strongest-rated banks up to 150% for the weakest. Corporate exposures follow a similar ladder: an AAA to AA- rated corporate usually attracts 20%, A+ to A- attracts 50%, BBB+ to BB- attracts 100%, and anything rated below BB-, or in default, attracts 150%. Only ratings from RBI-recognised External Credit Assessment Institutions (ECAIs) — CRISIL, ICRA, CARE, India Ratings and Acuité among the domestic agencies — can be used for this mapping, and banks must apply the rating consistently to both the funded and the unfunded portions of an exposure.

💡 Exam Tip: Learn the rating bands (AAA/AA, A, BBB/BB, below BB, unrated) cold — SA-CR questions in CAIIB Risk Management routinely test the exact risk weight attached to each band rather than the underlying rationale.

🏠 Unrated Exposures, Retail and Residential Mortgage Buckets

An unrated corporate exposure does not get a favourable risk weight by default — it is generally assigned 100%, the same as a mid-investment-grade rated borrower, so "unrated" should never be read as "low risk" in an exam answer. Claims on unrated banks are treated similarly through a base risk weight rather than being assumed AAA.

Exposures that qualify as regulatory retail — loans to individuals or small businesses that meet RBI's granularity, product, and per-obligor exposure-ceiling conditions — get a flat 75% risk weight regardless of the borrower's rating, which is usually lower than the unrated-corporate weight and rewards diversification across many small borrowers. Residential mortgage loans secured by a first charge on the property, where the loan-to-value ratio is kept within prudential limits, attract a lower risk weight than general corporate exposures — RBI has historically applied a tiered structure that rewards a lower LTV and a smaller loan size with a lower risk weight, while high-LTV housing loans and commercial real estate exposures are weighted closer to, or at, 100%.

📝 Credit Conversion Factors for Off-Balance-Sheet Items

Off-balance-sheet items — guarantees, letters of credit, undrawn commitments and derivative contracts — are not risk-weighted directly. They are first converted into a credit-equivalent amount using a Credit Conversion Factor (CCF), and only that credit-equivalent amount is then multiplied by the counterparty's risk weight. Direct credit substitutes, such as financial guarantees where the bank takes on the credit risk of a third party, carry a high CCF, commonly 100%. Performance-related contingencies like bid bonds and performance guarantees typically attract a lower CCF, around 50%, since the probability of a call is lower. Short-term, self-liquidating trade-related contingencies, such as documentary letters of credit collateralised by the underlying shipment, attract a modest CCF, often 20%.

Commitments are graded by tenor and cancellability: commitments with an original maturity of up to one year generally get a lower CCF than those exceeding one year, while commitments the bank can unconditionally cancel at any time without notice attract a very low CCF. Off-balance-sheet derivative exposures — a forward contract or an interest rate swap or swaption — are not converted with a simple CCF table at all; counterparty credit risk on these is measured separately, typically through a current-exposure-style method, before the resulting exposure is risk-weighted.

⚠️ Common Mistake: Candidates often forget that the CCF is applied first, and the counterparty's risk weight is applied second — the two steps are sequential, not additive, and skipping the CCF step overstates RWA.

⚖️ Standardised Approach vs Internal Ratings-Based Approach

The core difference between SA-CR and the internal ratings-based (IRB) approach is who estimates the risk parameters. Under SA-CR, risk weights come from a regulator-published table keyed to external ratings or exposure category — no bank-specific modelling or RBI approval is required to use it. Under IRB, a bank estimates its own probability of default (and, under the advanced variant, its own loss-given-default and exposure-at-default) using validated internal data, subject to rigorous RBI supervisory approval, ongoing model validation and a capital output floor that benchmarks the IRB result against the SA-CR figure.

SA-CR is simpler to implement, easier to audit, and comparable across banks, but it is less risk-sensitive because two borrowers with very different underlying risk can land in the same rating band. IRB is more granular and can lower capital requirements for genuinely lower-risk books, but it demands years of default and loss data, strong model governance, and continuous supervisory oversight — which is why RBI has kept IRB approval selective in India. For a deeper look at how banks build the internal models behind an IRB-style estimate, see the companion article on credit risk models in banks, and for how the output floor keeps IRB results tethered to the standardised numbers, see capital output floor in Basel III.

🧮 Worked Example: Computing Risk-Weighted Assets

Consider a bank with the following exposures on a single reporting date. An AA- rated corporate loan of Rs 100 crore at a 20% risk weight contributes Rs 20 crore of RWA. An unrated corporate loan of Rs 50 crore at 100% contributes Rs 50 crore. A regulatory retail portfolio of Rs 40 crore at 75% contributes Rs 30 crore. A residential mortgage book of Rs 20 crore, kept within prudential LTV limits and weighted at 35%, contributes Rs 7 crore.

Now add an off-balance-sheet performance guarantee of Rs 10 crore issued on behalf of an unrated corporate client. Applying a 50% CCF gives a credit-equivalent amount of Rs 5 crore; applying the client's 100% risk weight to that credit-equivalent amount gives Rs 5 crore of RWA. Total RWA for this portfolio is Rs 20 crore + Rs 50 crore + Rs 30 crore + Rs 7 crore + Rs 5 crore = Rs 112 crore. Under RBI's Basel III capital regulations, banks must hold total capital plus the capital conservation buffer against this RWA base, so the minimum capital a bank must hold against this specific portfolio scales directly with how each exposure was bucketed — which is exactly why getting the exposure class and CCF right, not just the arithmetic, is what CAIIB examiners test.

📌 Remember: RWA computation is always a two-step multiplication for off-balance-sheet items — exposure × CCF × risk weight — while on-balance-sheet items skip straight to exposure × risk weight.

✅ Conclusion: Master SA-CR Before You Sit the Exam

The standardised approach for credit risk rewards candidates who memorise the rating bands, the retail and mortgage buckets, and the CCF ladder rather than trying to reason them out from first principles under exam pressure. Pair this topic with related chapters on asset liability management to see how RWA feeds into capital planning, and browse more posts on the Risk Management Elective tag hub for the full Basel III series. For official rate and rating benchmarks, always cross-check the latest master circular on the RBI website before an exam attempt. Once you have the buckets down, drill the arithmetic with timed mock questions on iibf.store's CAIIB course — and if you also study Central Banking, the linked article on RBI intervention in the foreign exchange market shows how the same regulator's tools extend well beyond credit risk capital.

🧠 Practice MCQs: Standardised Approach for Credit Risk

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