Risk Management interview preparation

Questions

100

Traced to a firm

37

Firms

12

Updated

September 2026

Asked at

All firmsUBS14MSCI7BLBlackRock5FTFranklin Templeton3Oaktree Capital Management2Scotiabank2Jane Street1Moody's1Neuberger Berman1PIMCO1SSState Street1TSTruist Securities1

Topic

All topicsMarket risk and VaR14Tail risk and stress testing5Greeks and sensitivities5Credit risk11Counterparty risk and CVA6Operational risk5Model risk and validation6Regulatory capital7Liquidity risk and ALM6Statistics and quant foundations7Indian regulation7Risk governance and appetite4Markets and macro9Fit and career8

Level

AnyCoreIntermediateHard

Type

AnyTechnicalCaseBrainteaserMarket viewFit

1. 060Distinguish funding liquidity risk from market liquidity risk.Liquidity risk and ALMCoretechnicalTreasury and ALMBank market risk

   Say this

   Funding liquidity risk is not being able to meet your obligations as they fall due. Market liquidity risk is not being able to sell an asset at anything near its marked price. They're different risks, and the danger is that each one triggers the other.

   Then walk it

   1. Funding liquidity is a balance sheet and cash flow problem: deposits leave, a wholesale line isn't rolled, a margin call lands, and you need cash today. It's binary and it's fatal. You are either able to pay or you are not.
   2. Market liquidity is a price problem: bid-offer, depth, and how far the price moves against you when you try to sell size. It's continuous, and it shows up as a haircut on what your book is really worth.
   3. The spiral is the real answer. You need funding, so you sell assets. Selling into a thin market depresses the price. The lower mark reduces your collateral value and your capital, which makes funding harder, so you sell more. That's the liquidity spiral, and it's what turned 2008 from a credit event into a systemic one.
   4. Measurement differs completely. Funding liquidity: contractual and behavioural cash flow ladders, survival horizon, LCR and NSFR, and a stress test on deposit outflow. Market liquidity: bid-offer spreads, days of average daily volume to exit, and a liquidity-adjusted VaR or an exit-cost haircut.
   5. Worked example: a bond book marked at 100 crore, where the position is ten days of average volume. In a stress you might realise 92, so the honest liquidity-adjusted value is 92, not 100. The mark is not the exit price, and that 8 crore is the market liquidity risk in money.
   6. FRTB codified this by making liquidity horizons vary from 10 to 120 days by risk factor, so illiquid risk now costs more capital. That's the regulatory acknowledgement that a mark is not a price you can get.
   7. The thing to say without prompting: almost every bank failure is ultimately a funding liquidity failure. Solvency problems kill banks slowly and liquidity kills them in a week.

   Where candidates lose it

   Conflating the two, or giving definitions without the interaction. The answer that earns respect explains the spiral in both directions and says that a marked price is not an exit price. And naming that banks fail from liquidity, not capital, frames everything else you say.

   Expect next

   • How would you measure market liquidity risk in a bond book?
   • Which one killed more institutions in 2008?
   • How does FRTB handle illiquidity?
2. 061Explain LCR and NSFR.Liquidity risk and ALMIntermediatetechnicalTreasury and ALMRegulatory reporting

   Say this

   Both are Basel III liquidity ratios with a minimum of 100 percent. LCR is a 30-day survival test: high quality liquid assets over stressed net outflows. NSFR is a one-year structural test: available stable funding over required stable funding. Short-term shock versus long-term funding mismatch.

   Then walk it

   1. LCR numerator, HQLA: Level 1 is cash, central bank reserves and most sovereign debt at no haircut. Level 2A is high-grade covered and corporate bonds at a 15 percent haircut, Level 2B is lower-rated corporates and some equities at 25 to 50 percent, and Level 2 is capped at 40 percent of the total.
   2. LCR denominator: outflows minus capped inflows, with prescribed run-off rates. Stable retail deposits 3 to 5 percent, less stable retail 10, operational wholesale deposits 25, non-operational corporate deposits 40, and financial institution deposits 100. Inflows are capped at 75 percent of outflows, so you can't rely on collecting to pay.
   3. That run-off table is the heart of it, and it encodes a real judgement: insured retail deposits are sticky, and money from other banks disappears entirely. SVB's deposits were overwhelmingly uninsured corporate money, which the table would treat as the fastest-running kind.
   4. NSFR pairs funding stability against asset liquidity over a year. Equity and long-term debt count fully as stable funding, retail deposits at 90 to 95 percent, short wholesale funding at little or nothing. On the asset side, long-dated loans need high stable funding and cash needs none.
   5. So NSFR is a structural constraint on maturity transformation, which is the business banks are in. It limits how much of a long loan book you can fund with three-month wholesale paper.
   6. Indian specifics: RBI implemented LCR from 2015 and NSFR from 2021, both at 100 percent, and has periodically adjusted the treatment of SLR securities within HQLA. The 2024 draft revisions raised run-off assumptions on retail deposits with internet and mobile banking access, which is a direct response to how fast deposits can now move.
   7. The critique to volunteer: both are point-in-time ratios with prescribed assumptions, and they can be window-dressed at reporting dates. And in a real run, the run-off rates have been far higher than the table assumes. SVB lost a quarter of its deposits in a day.

   Where candidates lose it

   Mixing up the horizons or quoting the ratios without any run-off rates. Knowing that financial institution deposits run off at 100 percent and stable retail at 3 to 5 is what shows you've seen the schedule. And the point that real runs are faster than the assumed rates is the part with judgement in it.

   Expect next

   • What counts as HQLA, and what haircuts apply?
   • Why did banks with a 100 percent LCR still fail in 2023?
   • How does NSFR constrain the lending business?
3. 062What is interest rate risk in the banking book, and how do you measure it?Liquidity risk and ALMIntermediatetechnicalTreasury and ALMIndian bank risk and treasury

   Say this

   IRRBB is the risk that rate moves hurt the banking book, and you measure it two ways that often disagree. Economic value of equity is the present value view over the full life of the balance sheet. Net interest income is the earnings view over one to three years.

   Then walk it

   1. EVE: revalue all assets, liabilities and off-balance-sheet items under a rate shock and look at the change in net present value. It's the long-horizon, economic answer, and it's where a big fixed-rate asset book shows up immediately.
   2. NII: project interest income and expense over one to three years under the shock. It's the accounting and earnings answer, and it's the one management actually cares about because it hits reported profit.
   3. They can point in opposite directions, and that's the interesting part. A bank funding long fixed-rate mortgages with short deposits looks fine on NII when rates rise slowly, because deposit rates lag, while EVE is deeply negative from day one. That gap is exactly the SVB configuration.
   4. The Basel standardised framework prescribes six shock scenarios: parallel up and down, steepener, flattener, short rate up and short rate down. Non-parallel scenarios matter because most banks are not exposed to the level so much as to the shape.
   5. Then the behavioural assumptions, which are where all the model risk lives. Non-maturity deposits have no contractual maturity so you assume one. Prepayment on fixed loans. Early withdrawal on term deposits. Pipeline commitments. Move the deposit assumption from a two-year to a five-year effective duration and the answer changes sign.
   6. The supervisory outlier test: if EVE sensitivity exceeds 15 percent of Tier 1 capital under any of the six scenarios, you attract supervisory attention under Pillar 2. That's the number to know.
   7. In India, RBI requires both the traditional gap approach and duration-based EVE reporting, and IRRBB is a core Pillar 2 item in ICAAP. Indian banks carry large SLR portfolios of government bonds, so rate risk in the banking book is structurally significant and the AFS versus HTM classification decision drives how much of it hits reported capital.
   8. How you manage it: reprice the book, use interest rate swaps to shorten effective asset duration, adjust deposit pricing, and set limits on both EVE and NII sensitivity so neither view can be ignored.

   Where candidates lose it

   Giving only one of the two measures. If you say EVE and not NII, or the reverse, you've described half the framework and missed the tension that makes IRRBB interesting. And the behavioural deposit assumption is the single biggest driver of the answer, so name it as the main model risk.

   Expect next

   • EVE and NII disagree. Which do you act on?
   • What is the supervisory outlier test?
   • How would you hedge a negative EVE position?
4. 063How would you build a survival horizon for a bank treasury?Liquidity risk and ALMIntermediatetechnicalTreasury and ALMIndian bank risk and treasury

   Say this

   Build a daily cash flow ladder under stress and find the first day the counterbalancing capacity runs out. That day count is the survival horizon, and the useful output isn't the number itself but which assumption drives it.

   Then walk it

   1. Start with contractual cash flows by day: maturing loans in, maturing deposits and wholesale funding out, coupon and interest flows, and known commitments. That's the easy part and the least informative.
   2. Then layer behavioural assumptions, which is where the answer is actually made. Deposit run-off rates by segment, drawdown on committed undrawn facilities, no rollover of wholesale funding, and rating-trigger-driven collateral calls.
   3. Then the counterbalancing capacity: unencumbered HQLA at stressed haircuts, central bank facilities and what collateral qualifies, committed lines you can genuinely draw, and asset sales with a realistic time-to-cash. Repo is the fast one, whole-loan sales are not.
   4. Then run at least three severities: an idiosyncratic name-specific stress where markets function but nobody will lend to you, a market-wide stress where everyone is short cash, and a combined scenario. The combined one is what regulators require and it's the one that binds.
   5. Read off the first day of negative cumulative net cash. A typical internal appetite is 30 days for a combined stress and 90 days for an idiosyncratic one, plus the regulatory 30-day LCR as a floor.
   6. Then the genuinely valuable step: sensitivity. If the horizon goes from 45 days to 12 when retail run-off moves from 10 to 20 percent, the number is an assumption, not a fact. I'd present the horizon as a range with the binding driver named.
   7. Two things people forget. Intraday and currency granularity: being liquid in rupees and short dollars on day three is a failure even if the aggregate is fine. And encumbrance, because assets already pledged in repo are not available however liquid they look.
   8. And the escalation link: each horizon threshold should map to a contingency funding plan trigger with named actions, or the measurement is an academic exercise.

   Where candidates lose it

   Building a contractual maturity ladder and calling it done. Contractual flows tell you almost nothing, because the risk lives in behaviour. And failing to split by currency is the classic error: an aggregate survival horizon can hide a dollar funding gap that kills you first.

   Expect next

   • What run-off rate would you assume on uninsured corporate deposits?
   • How do you treat central bank facilities in the counterbalancing capacity?
   • How would this differ for a non-bank finance company?
5. 064How would you model a bank's savings deposits, which have no contractual maturity?Liquidity risk and ALMIntermediatesuperdayTreasury and ALMIndian bank risk and treasury

   Say this

   Split the balance into a stable core and a volatile portion, assign a behavioural maturity to the core, and estimate a deposit beta for how much of a policy rate move you pass through. Those two parameters, core share and beta, drive the entire banking book rate risk answer.

   Then walk it

   1. Volume modelling first. Look at the historical balance series per segment, strip out trend and seasonality, and take a low percentile of the remaining distribution as the stable core. Many banks use something like the balance exceeded 95 percent of the time over five years.
   2. Assign a repricing or behavioural maturity to the core. If it has been sticky for a decade, you might treat it as five to seven years of effective duration, capped by supervisory limits. Basel caps the average repricing maturity of core retail non-maturity deposits at five years in its standardised framework, and that cap exists because banks were assuming longer and flattering their rate risk.
   3. Deposit beta: regress the rate you actually paid against the policy rate. Indian savings rates have historically been very sticky, so betas on savings accounts are low, maybe 0.2 to 0.4, while term deposits and bulk deposits run much higher, 0.6 to 0.9. Segment or the average is meaningless.
   4. Betas are asymmetric and non-linear, and that's the point most candidates miss. They're low on the way up until competition bites and then they jump, and they're low on the way down because you can't pay less than zero. Modelling a single symmetric beta understates the squeeze in a rising cycle.
   5. Segmentation matters more than technique: retail versus corporate, insured versus uninsured, digitally active versus branch-only, relationship versus rate-shopping. A digitally active uninsured corporate depositor behaves nothing like a pensioner with a branch passbook.
   6. Then validate the assumptions against a real episode rather than trusting the regression. What actually happened to your balances and your pass-through in the 2022 to 2023 hiking cycle? That's the out-of-time test.
   7. The limitation to volunteer, and it's the important one: these models are all calibrated on a world where moving money was slow. Mobile banking and instant transfers have shortened behavioural maturities in a way the history doesn't contain. SVB lost a quarter of its deposits in a day, which no core-stability model would have produced. So I'd stress the assumption hard rather than trust it.
   8. RBI's 2024 draft LCR revisions add a run-off add-on for internet and mobile banking enabled deposits for exactly this reason, which is a good example of supervisors updating faster than the models.

   Where candidates lose it

   Treating it as purely a statistical problem. The regression is the easy part; the judgement is in segmentation, in the asymmetry of beta, and in recognising that the historical data predates instant digital withdrawal. A candidate who says 'the history no longer applies' and then says what they'd do about it stands out.

   Expect next

   • What deposit beta would you assume for Indian savings accounts?
   • How would you stress the core assumption?
   • Why does Basel cap the assumed maturity at five years?
6. 065A bank funds long-dated fixed-rate securities with uninsured corporate deposits. Walk me through everything that can go wrong.Liquidity risk and ALMHardcase studyTreasury and ALMBank market risk

   Say this

   That's the Silicon Valley Bank structure, and it fails in a specific sequence: rates rise, the asset side loses economic value without showing it in the accounts, depositors leave because they have better options, and selling the assets to pay them crystallises the loss and destroys the capital.

   Then walk it

   1. Step one, the duration mismatch. Long fixed-rate assets and overnight liabilities means economic value of equity falls hard when rates rise, even while net interest income looks fine for a while because deposit rates lag.
   2. Step two, the accounting shield that becomes a trap. Securities classified as held-to-maturity aren't marked through capital, so the loss is invisible in the reported ratios. SVB had roughly $15bn of unrealised HTM losses against about $16bn of equity at the end of 2022. The capital ratio said nothing was wrong.
   3. Step three, the depositor incentive. Uninsured corporate treasurers are rate-sensitive and professional. When T-bills yield 5 percent and your account pays 0.5, they leave for economic reasons before there's any fear. That's a slow outflow that forces asset sales.
   4. Step four, the crystallisation. Selling HTM securities to fund outflows moves the loss from a footnote into the income statement and the capital ratio. Worse, selling any of the portfolio can force reclassification of the whole HTM book under the accounting rules, which is why banks resist it until they can't.
   5. Step five, the run. Once the loss is public, uninsured depositors with a 100 percent loss-given-failure have every incentive to leave first, and they can now do it in an afternoon from a phone with a group chat coordinating them. SVB lost about $42bn in a single day.
   6. Step six, concentration as the accelerant. A depositor base drawn from one industry with shared advisers and shared venture investors is not a diversified funding book. It's one depositor with many accounts.
   7. What the risk function should have done: report EVE alongside NII and escalate the gap, treat unrealised HTM losses as economic capital regardless of accounting, model uninsured deposits with far faster run-off, set a concentration limit on depositor type, and hedge the duration with swaps. The last one is the cheapest and SVB had almost none on.
   8. And the governance point: SVB had no chief risk officer for part of 2022 and its interest rate stress scenarios had reportedly been changed to be less severe. The measurement failure was downstream of a governance failure, which is almost always the case.

   Where candidates lose it

   Describing it as a liquidity problem only, or a rate problem only. It's the interaction, plus an accounting classification that hid the loss, plus a concentrated and professional depositor base. Candidates who name the HTM accounting treatment and the depositor concentration show they've read the post-mortem rather than the headline.

   Expect next

   • Why didn't the capital ratio show the problem?
   • What single hedge would have changed the outcome?
   • How would you set a depositor concentration limit?

Firm tags come from public, anonymous candidate reports on Wall Street Oasis: strong signal, not sworn testimony. Firms are named as the places a question was reported, not as partners of Fin Maverick. Answers are written for this page to show how to think out loud; they are not scripts to recite.