BI/Fraud Stakeholder Case: Drive an Account Takeover (ATO) Policy Change in 90 Days

You join the Chicago Fraud team as a Decision Scientist. The hiring manager emphasized BI tooling and high‑impact analysis. In your first 90 days, you must influence a policy change that reduces ATO while minimizing user friction.

Assume you have access to core payment/auth logs, device and IP intelligence, and a BI tool (e.g., Looker). ATO is defined as a confirmed, reimbursed loss after investigation; label lag can be 7–21 days.

Tasks:

A) 30/60/90-Day Plan with concrete outputs (include week-level deliverables; e.g., Week 2: ship a Looker dashboard with daily fraud loss by device/IP novelty; Week 6: present a cost–benefit analysis (CBA) for a new ATO rule).

B) Define 5 core dashboard tiles with precise metric formulas and denominators (e.g., ATO Loss per 1K tx, Legit Block Rate per 1K legit tx, Step-up Success Rate).

C) Draft a ~150-word executive update to the Venmo PM and Risk Ops lead proposing a rule change and its expected net impact, with assumptions and guardrails.

D) Address pushback that SQL-only is sufficient: specify when you’d use SQL vs. Python for reproducible analyses, and what governance (review, versioning, data contracts) you’d enforce to ensure trust in BI.