How Citigroup Interviews in 2026: Process, Questions & What They Score

1. 01

   Walk me through a DCF (discounted cash flow) analysis.

   Core valuation: project free cash flows, discount at WACC, add terminal value; expect follow-ups on each input.

2. 02

   Walk me through the three financial statements and how they flow together / how a change in one flows through the others.

   Accounting fluency: how income statement, balance sheet, and cash flow statement link and reconcile.

3. 03

   What does the discount rate (WACC) represent, and how do you calculate it?

   Tests cost-of-capital mechanics: weighting debt and equity costs and where CAPM inputs come from.

4. 04

   What's the difference between unlevered and levered free cash flow (FCFF vs. FCFE)?

   Valuation detail: unlevered versus levered cash flow and which discount rate pairs with each.

5. 05

   How do you value a company using comparable companies analysis and precedent transactions, and when would you prefer each over a DCF?

   Tests relative valuation: picking comparables, applying multiples, and when comps beat a DCF.

6. 06

   What makes a borrower risky? Walk through key credit metrics (leverage/debt-to-EBITDA, interest coverage, cash flow stability, collateral).

   Credit analysis: leverage, coverage, and cash-flow stability metrics that signal borrower risk.

7. 07

   What are the 5 C's of credit, and what types of covenants and debt structures should a lender care about?

   Credit fundamentals: the five C's plus covenant types and seniority in debt structures.

8. 08

   How would a $10 increase in depreciation affect the three financial statements?

   Classic accounting walk-through: trace a depreciation change through all three statements including the tax effect.

Reported problems, listed so you know what to expect. Practice them in your own editor or on the platform you prefer; SupaCV's practice mode coaches how you talk through them.

1. 01

   Core Java fundamentals questions (e.g., differences between similar syntax/constructs, OOP concepts) often via an external Karat interviewer.

   Language fundamentals: Java syntax distinctions and OOP concepts, often run by an external Karat interviewer.

2. 02

   A live debugging exercise (finding and fixing a bug or failing test in provided code), typically ~10 minutes.

   Tests fast fault isolation: read unfamiliar code, reproduce the failure, and fix it within about 10 minutes.

3. 03

   A small implementation/coding question in a language of your choice, typically ~10 minutes.

   Short coding exercise in your language of choice; correctness and clean structure matter more than tricks.

4. 04

   Framework/stack scenario questions covering Spring Boot, React, AWS basics, and common design patterns.

   Applied stack knowledge: Spring Boot, React, AWS basics, and where common design patterns fit.

5. 05

   A timed Codility/HackerRank-style data-structures-and-algorithms assessment (difficulty broadly comparable to LeetCode 'medium'), sometimes including basic SQL or concurrency-reasoning questions.

   Timed DSA assessment near LeetCode medium; may mix in basic SQL or concurrency reasoning.

6. 06

   System design or architecture discussion for more senior engineering candidates (role- and level-dependent; not uniformly reported at junior levels).

   System design for senior engineers: scope, architecture, and trade-off discussion calibrated to level.

Reported problems, listed so you know what to expect. Practice them in your own editor or on the platform you prefer; SupaCV's practice mode coaches how you talk through them.

1. 01

   SQL questions covering joins, aggregations, and window functions.

   SQL proficiency: joins, aggregations, and window functions on realistic tables.

2. 02

   Python data-manipulation and debugging exercises.

   Tests practical Python: cleaning and transforming data plus debugging broken snippets.

3. 03

   Explain how you would validate, monitor, and document a machine-learning model in a regulated banking environment.

   ML governance: validation, monitoring, and documentation expectations in a regulated bank.

4. 04

   Statistics and model-evaluation fundamentals (e.g., bias-variance tradeoff, precision/recall, cross-validation).

   ML evaluation basics: bias-variance, precision versus recall, and cross-validation design.

5. 05

   Applied case questions connecting modeling choices to banking outcomes such as credit risk, fraud detection, or customer lifetime value.

   Applied judgment: connecting model and feature choices to credit risk, fraud, or CLV outcomes.

6. 06

   Walk through an end-to-end modeling project you've worked on, including how you handled data quality or deployment concerns.

   Project deep dive testing real modeling experience: data quality handling, deployment, and your specific decisions.

Reported problems, listed so you know what to expect. Practice them in your own editor or on the platform you prefer; SupaCV's practice mode coaches how you talk through them.

1. 01

   Basic probability puzzles (e.g., expected length of the smallest piece of a randomly broken stick).

   Probability puzzle on order statistics: expected minimum piece of a randomly broken stick.

2. 02

   Mental math and market-sizing/estimation questions under time pressure.

   Tests speed arithmetic and Fermi estimation under time pressure with clearly narrated steps.

3. 03

   Core probability, statistics, linear algebra, and calculus fundamentals relevant to pricing and risk models.

   Screens the math core for pricing and risk work: probability, statistics, linear algebra, and calculus.

4. 04

   Basic option pricing and financial economics concepts (e.g., what drives an option's value, put-call parity intuition).

   Options intuition: the drivers of option value and put-call parity reasoning without heavy math.

5. 05

   Classic brainteasers (e.g., coin-weighing, dice, expected-value puzzles) used to test structured reasoning.

   Structured-reasoning check via classic coin, dice, and expected-value puzzles; narrate your setup.

6. 06

   Questions on stochastic processes / basic stochastic calculus for more quant-specific roles.

   Quant depth check: Brownian motion basics and Ito-style reasoning for pricing models.

Reported problems, listed so you know what to expect. Practice them in your own editor or on the platform you prefer; SupaCV's practice mode coaches how you talk through them.

1. 01

   Tell me about yourself / walk me through your resume.

2. 02

   Why Citi? (interviewers reportedly respond better to candidates who reference Citi's current strategy/turnaround, e.g., its global network, the investment-banking build-out under new banking head Vis Raghavan, and recent M&A/banking fee growth, rather than generic 'prestigious global bank' answers.)

3. 03

   Why investment banking / why this specific business (e.g., why corporate banking over IB, why markets, why this group)?

4. 04

   Tell me about a time you faced a challenging situation at work or school and how you handled it.

5. 05

   Describe a time you had to work with a difficult team member or resolve a conflict.

6. 06

   Tell me about a time you demonstrated leadership or took ownership of a problem.

7. 07

   Describe a time you had to make a decision with incomplete information or under pressure.

8. 08

   What would your team/manager/professor say about you?

1. 01

   Why quantitative trading/analysis at Citi specifically, and what markets or products interest you?