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Finance and Investment AI Training Interview Questions

Finance roles ask investment bankers, equity researchers, private equity and venture professionals and finance specialists to build or check models, write hard finance tasks and judge model reasoning. Postings commonly require direct experience, for example ownership of company models. These practice questions focus on accuracy and clear financial reasoning.

35 open roles in this groupUpdated 9 October 2026

Practice questions

These are practice questions written for this site to help you prepare. No platform has said it asks these exact questions.

  1. Walk through a discounted cash flow valuation.

    A good answer covers: Forecast free cash flow, choose a discount rate (WACC), terminal value by growth or multiple, discount and sum, then sensitivities.

  2. A model's DCF uses equity cash flows with WACC. What is wrong?

    A good answer covers: Mismatch between cash flow and discount rate; unlevered cash flows go with WACC, levered with cost of equity.

  3. How do the three financial statements link?

    A good answer covers: Net income flows to retained earnings and the cash flow statement; non-cash items and working capital reconcile to cash on the balance sheet.

  4. Write a task that tests an AI on a leveraged buyout model.

    A good answer covers: Clear inputs, debt schedule, exit assumptions and a checkable IRR or MOIC answer.

  5. How would you judge an equity research summary written by a model?

    A good answer covers: Correct figures, sources, balanced risks, no unsupported price targets, clear thesis.

  6. Explain enterprise value versus equity value.

    A good answer covers: EV is the value of operations to all capital providers; equity value is what belongs to shareholders after net debt and other claims.

  7. What checks catch errors in a spreadsheet model?

    A good answer covers: Balance sheet balances, cash ties, sign checks, hard-coded numbers, circular references.

  8. Describe a deal or model you owned end to end.

    A good answer covers: Your role, the key assumptions, the result and what you would change.

  9. How should an AI answer a personal finance question responsibly?

    A good answer covers: General information, local rules noted, risks stated, and a suggestion to seek regulated advice for decisions.

What the platforms say about the assessment

In the 2026-10-09 data, roles in this group came from micro1, Meridial, SME Careers and Terac. Each platform runs its own process, and steps can differ by role. Below is what each platform's public pages or postings say, followed by lines quoted from current postings in this group.

micro1

Source: www.micro1.ai

Meridial

Source: boards-api.greenhouse.io

SME Careers

Sources: sme.careers, api.sme.careers

Terac

Source: terac.com

Quoted from current postings

"Selection process involves an AI interview, a domain-specific task, and an interview with a recruiter."

Financial Quality Assurance Lead (QAL), sme

Steps were read from public pages and postings, not tested first-hand. Passing a screening does not guarantee a project, hours or pay.

Terms to know

Domain expert
Someone hired for professional knowledge in a field, such as law, medicine or engineering, to write or judge expert-level tasks.
Fact-checking
Checking each claim in a model's answer against reliable sources and marking what is wrong or unsupported.
Rubric
A written list of criteria and scores used to judge a response, for example accuracy, instruction following and tone, each with clear pass or fail descriptions.
Stump the model
A task where you write a hard question the model gets wrong and record the correct answer, often used in expert STEM and coding projects.

Open roles in this group (35)

Sources

Other role groups