Flagship course

Model Risk Audit Fundamentals

A structured path for examining fintech analytics models — from inventory hygiene to findings that survive second-line review.

Collaborative review of analytics materials

Who it is for

Analytics leads, model owners, and second-line reviewers who must speak coherently about credit, fraud, pricing, or marketing models inside a fintech stack.

You do not need a full MRM title. You do need access to at least one model packet you can discuss in redacted form.

Modules

  1. 01

    Inventory and materiality

    Classify models, tools, and vendor scores. Decide what belongs in scope before debate begins.

  2. 02

    Conceptual soundness under pressure

    Pressure-test purpose statements, population definitions, and excluded segments.

  3. 03

    Data lineage and feature risk

    Trace fields from source systems through transforms; spot silent breaks.

  4. 04

    Performance and stability evidence

    Read discrimination, calibration, and stability plots the way auditors do.

  5. 05

    Overrides and human-in-the-loop

    Document exception patterns that quietly rewrite model outcomes.

  6. 06

    Monitoring design

    Choose triggers that matter; retire vanity metrics that never escalate.

  7. 07

    Challenge memo intensive

    Write findings with severity, evidence, and remediation owners.

  8. 08

    Audit dry run

    Defend your pack in a timed challenge circle with faculty feedback.

Learning outcomes

Instructor

Portrait of instructor Hana Jeong

Hana Jeong

Former validation lead for a Seoul-based digital lender; now advises fintechs on model challenge design. Teaches Modules 1–4 and co-facilitates the audit dry run.

Informational pricing

Desk Seat from ₩1.85M per learner. Studio and Assurance Circle options are listed on the pricing page. No payment is processed on this website.

Reviews from this course

Module 05 on overrides forced our product ops team to admit how often chat approvals bypassed the score. Uncomfortable, useful.

Junho · Seoul

★★★★☆

Strong on documentation. The monitoring week felt rushed if you have immature pipelines — faculty said as much, which I appreciated.

Client in consumer lending

FAQ

Do I need coding experience?

Comfort reading metrics and basic SQL helps. The course is not a machine-learning coding bootcamp.

Can I bring a confidential model pack?

Yes, in redacted form. Faculty will tell you what to strip before sharing in cohort spaces.

What is a real limitation of this course?

We do not certify models as compliant with any regulator. Completing the program improves your preparation quality; it does not replace independent validation, legal advice, or supervisory dialogue.

Are sessions recorded?

Yes, for enrolled learners during the cohort window. Live attendance is still expected for challenge circles.