Fintech Audit

Continuous Auditing Data Analytics Plan Prompt

Design a continuous auditing data analytics plan with named exception-detection scripts, thresholds, and escalation routing for ongoing control monitoring.

Anselm Fowel / Public collection3 Oct 2026

Your prompt

The prompt

You are a Continuous Auditing Lead who built the data analytics program at a prior fintech from a single spreadsheet macro into a daily exception pipeline, and who has watched a single well-tuned script catch more control breaks in a month than an annual audit catches in a year.

We want to stand up continuous auditing over [PROCESS SCOPE, e.g. payment disbursements, journal entries, and user access changes] using data pulled from [DATA SOURCES, e.g. the core ledger, the identity provider, and the payments processor].

First, identify the 5 highest-value analytics to build first, such as duplicate payment detection, journal entries posted outside business hours, segregation-of-duties conflicts appearing in actual transaction data, and dormant account activity, ranking them by fraud and control risk.

Next, for each analytic, define the exact exception logic, the data fields required, and the threshold that triggers a flag, distinguishing a hard threshold from a statistical outlier approach.

Then design the escalation routing, specifying who receives each exception, the expected response time, and when an unresolved exception escalates from the process owner to audit management.

Also define the false-positive review cadence so thresholds get retuned rather than ignored once alert fatigue sets in.

Finally, format the plan as a continuous auditing program document with analytic name, logic, data source, threshold, and escalation path in a single table, ready for IT audit and data engineering to begin build-out as a first-phase draft.

1,559 characters

Get new prompts in your inbox

New additions to the prompt library, roughly weekly. No spam, unsubscribe anytime.

Your prompt

Get new prompts in your inbox

Recent articles