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🧾 How Can I Use AI to Spot Fraud and Anomalies in Transactions?

🧾 How Can I Use AI to Spot Fraud and Anomalies in Transactions?

Audits don’t have to take days. This week’s AI+ shows you how to prompt ChatGPT to flag irregular transactions and surface fraud risks in seconds.

September 09, 2025

☕ Morning, finance fam!

Financial anomalies don’t wait—they hide. Miss one, and you're explaining discrepancies instead of educating clients.

What if AI could:

Highlight suspicious patterns in minutes, not days?
Pre-fill your audit checklist with flagged risks?
Save you both time—and the potential cringe when a client spot-checks a report?

You don’t need a forensic accounting team to do it either. This week, we show you how to use AI like a flashlight in your audit—finding what matters, fast.

Here’s what’s inside this week:

⚡ 1 AI Hack Prompt for anomaly detection in your transactions
🛠️ 3 Free Tools From ChatGPT hacks to anomaly-detection apps
🧠 1 News Byte One powerful story on how AI is already outpacing human audit filters—raw link included
📚What’s Happening 3 must-know developments with raw URLs
😂 Meme Corner: When AI calls out your “Big Latte Expense” in neon red
And more…

Let’s get to it: 👇

⚡1 AI Hack: Clean Up, Summarize, and Formula‑Generate—In One Prompt

🧠 The Problem:

Manual reviews miss subtle outliers—or drain your day. Transactions flagged late can spell client mistrust or even compliance headaches.

🧰 What You’ll Need:

ChatGPT (Free or Plus)
A CSV or list of recent transactions (redact sensitive info)
A prompt tuned for exceptions—not summaries

🪜 Step-by-Step Instructions:

🧾 Scenario:

You want to quickly surface oddities—large amounts, strange vendors, or unexpected frequencies.

✅ Step 1: Copy/paste sample transactions (CSV format)

Use a small slice of recent activity (10–30 rows). Keep the simple header:

Date, Payee, Amount, Category. See data dump below as example:

Date,Payee,Amount,Category 2025-07-02,Blue Harbor Cafe,12.50,Meals 2025-07-02,Blue Harbor Cafe,12.50,Meals 2025-07-03,Apex Office Supplies,124.99,Office Supplies 2025-07-03,Apex Office Supplies,1249.90,Office Supplies 2025-07-05,CryptoMax Exchange,3000.00,Investments 2025-07-06,Star Ride Car Service,842.20,Travel 2025-07-07,CoffeeCloud,12000.00,Meals 2025-07-08,Northwind Consulting,2500.00,Professional Fees 2025-07-08,Northwind Consulting,-2500.00,Refunds 2025-07-09,Cash Withdrawal,500.00,Miscellaneous 2025-07-10,Office Depot,62.41,Office Supplies 2025-07-10,Office Depot,62.41,Office Supplies 2025-07-11,Overseas Wire HK,4575.00,Miscellaneous 2025-07-12,Midnight Diner,58.20,Meals 2025-07-12,Midnight Diner,5820.00,Meals 2025-07-13,Gymflex Membership,120.00,Subscriptions 2025-07-14,Gift Cards R Us,800.00,Miscellaneous 2025-07-15,Parking Authority,25.00,Fees 2025-07-15,Parking Authority,25.00,Fees 2025-07-16,Apex Office Supplies,0.00,Office Supplies

✅ Step 2:

Use this prompt:

“Act like a forensic accountant. Analyze the following CSV of transactions (headers: Date, Payee, Amount, Category). Identify irregular transactions (outliers vs typical amounts, suspicious vendors, negative or zero amounts, duplicates, unusual frequency, or international wires). Return a table with: Date, Payee, Amount, Category, Flag Type, Why Flagged, First Check to Perform. Then list 3–5 suggested follow‑up actions.”

Paste the CSV right after the prompt.

✅ Step 3: Example output you should expect (from ChatGPT)

Date	Payee	Amount	Category	Flag Type	Why Flagged	First Check to Perform
2025-07-02	Blue Harbor Cafe	12.50	Meals	Duplicate	Two identical charges on same day	Confirm if one is a duplicate; request receipt
2025-07-03	Apex Office Supplies	1249.90	Office Supplies	Outlier (10×)	Amount ~10× larger than nearby purchase at same vendor	Verify invoice; confirm approval threshold
2025-07-05	CryptoMax Exchange	3000.00	Investments	Restricted/Risk	Crypto exchange; higher fraud/AML risk	Confirm policy allows crypto; source of funds
2025-07-06	Star Ride Car Service	842.20	Travel	Outlier	Unusually high car service vs typical local rides	Check trip details; receipt & purpose
2025-07-07	CoffeeCloud	12000.00	Meals	Extreme Outlier	Implausible “Meals” expense (likely miscoded or extra zeros)	Verify merchant category; correct coding
2025-07-08	Northwind Consulting	-2500.00	Refunds	Negative Amount	Large refund; ensure it matches a prior charge	Tie to original invoice; confirm counterparty
2025-07-09	Cash Withdrawal	500.00	Miscellaneous	Cash Handling	Cash withdrawals raise control/receipt risks	Obtain receipt log; confirm petty cash policy
2025-07-10	Office Depot	62.41	Office Supplies	Duplicate	Two identical charges on same day	Confirm if one is duplicate or split tender
2025-07-11	Overseas Wire HK	4575.00	Miscellaneous	Intl Wire/AML	International wire; potential AML/compliance screening	Verify beneficiary; purpose; KYC/OFAC checks
2025-07-12	Midnight Diner	5820.00	Meals	Typo/Outlier	5820.00 vs 58.20 same day/vendor suggests misplaced decimal	Request receipt; correct amount if error
2025-07-16	Apex Office Supplies	0.00	Office Supplies	Zero Amount	Zero‑amount entries can indicate voids/test items	Validate posting status; remove/adjust
2025-07-14	Gift Cards R Us	800.00	Miscellaneous	Gift Cards Risk	Gift cards commonly used to circumvent controls	Require approval trail; business justification

Suggested follow‑ups (example):

Reconcile all duplicates (Blue Harbor Cafe, Office Depot, Parking Authority) against receipts; void or credit one if confirmed duplicate.
Validate outliers (CoffeeCloud $12,000; Apex 10×; Midnight Diner $5,820) against invoices; correct miscoding/decimal errors.
Run vendor concentration analysis (Apex, recurring meals) and set soft thresholds for alerts (e.g., >3× rolling median).
Enforce policy checks for crypto, gift cards, cash withdrawals, and international wires; document approvals and KYC steps.
Create an “exceptions” view in your accounting system/CRM and tag each item with owner + due date for resolution.

✅ Step 4: Batch actions in your workflow

Tag & assign: Add a “Flagged—Review” label and assign each item to an owner.
Timebox: 15–20 minutes to resolve duplicates and obvious entry errors first.
Escalate: Anything AML/policy‑sensitive (crypto, wires, gift cards) escalates to compliance.

💡 Pro Tip:

Save your prompt and the output table as a template. Next month, paste new CSV → compare flags month‑over‑month to show risk reduction in client reviews.

Want this kind of automation on demand? My personal GPT includes inbox prompts, triage workflows, and more.

🔗 Try it here: https://bit.ly/theaiplus_financegpt

🛠️ 3 Free AI Tools to Try This Week

🔍 ChatGPT (Free)

Use Case: Anomaly detection + suggested review steps

Tip: Use “act like a forensic accountant” for precise tone

🔗 https://chat.openai.com

📥 Mindbridge (free trial)

Use Case: Upload files for AI-powered risk scoring

Tip: Great for seeing what “looks weird” at a glance

🔗 https://mindbridge.ai

⚙️ Perplexity.ai

Use Case: Ask “What stands out in these transactions?” and get context with sources

Tip: Good for audit footnotes or compliance backup

🔗 https://perplexity.ai

💡Bonus: Want ready-to-use prompts for audit anomaly detection, transaction triage, and compliance review?

Grab my $9 Prompt Pack for Advisers—plug it into your AI workflow and surface risks, not spreadsheets. https://bit.ly/smartmoneypromptpack

📰 News Byte: AI Is Outpacing Human Audit Filters — Already

Last week, the Wall Street Journal reported on IVIX, a New York–based startup that uses AI to uncover financial fraud across vast datasets—think offshore assets, layered laundering, and crypto networks. Their AI software identifies patterns invisible to traditional checks and flags anomalies that would take humans ages to catch.

In fact, the tool now helps investigators detect illicit activity in seconds—something auditors would spend days chasing. And with a fresh $60 million in Series B funding, IVIX is doubling down on expanding its capabilities to serve financial oversight agencies globally.

Why it matters: Your audit workflow can include this style of anomaly detection—if your AI prompt is sharp and your review smart. Instead of being reactive, you become preemptive.

Raw URL: https://www.wsj.com/articles/a-startup-that-uses-ai-to-spot-financial-fraud-raises-60-million-24a0ca7e

📚 What’s Happening

📥 AI detecting patterns humans miss
New algorithms can flag suspicious behavior in real time—a game-changer for both audit efficiency and accuracy.
https://en.wikipedia.org/wiki/Audit_technology
💡Internal audit meets AI-powered precision
Firms now use machine learning, NLP, and predictive analytics to broaden audit scope and reduce manual sampling.
https://www.plantemoran.com/explore-our-thinking/insight/2025/07/ai-and-internal-audit
AI fraud detection reaches ~91% of US banks
Most banks now lean on AI for fraud prevention—and nearly all anti-fraud pros plan to add GenAI capabilities in 2025.
https://www.elastic.co/blog/financial-services-ai-fraud-detection

Meme Corner 😂

That’s a wrap, audit pro.

✅ You learned how to prompt ChatGPT to detect irregularities

✅ Tested tools that score risks and flag anomalies instantly

✅ Saw how AI reduces audit time from days to minutes

Audits → faster, sharper, smarter.

Requests, ideas or prompts, hit reply or comment and let me know - I read every response/comments.

Know an auditor who needs help? Share this issue → https://theaiplus.beehiiv.com/subscribe

Until next time,

Audit smarter, flag faster, and let AI handle the heavy scanning. 😎

Shirley, Chief Nerd at The AI+

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