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Fraud Detection · Scale 2021

Scaling Invoice Fraud Detection Across 40+ Global Clients

Grew an invoice duplicate and fraud detection platform at Accenture from concept to 200+ enterprise clients worldwide, personally leading implementation for 40+ of them.

$1M+ in fraud prevented
200+ enterprise clients
40+ direct implementations

The Problem

Enterprise finance teams lose billions annually to duplicate invoice submissions and vendor fraud. The detection methods in use — manual spot-checks and rule-based systems — were catching less than 30% of fraudulent transactions and couldn’t scale with growing transaction volumes.

Accenture needed a platform that could be deployed across its client base, adapt to different ERP systems, and catch fraud with enough confidence to act on automatically.

The Approach

I joined the platform team during its growth phase and became responsible for client implementations — translating the core detection platform into working solutions for clients across manufacturing, retail, and financial services.

Each implementation required understanding the client’s ERP setup, invoice data structure, and risk tolerance. I built a reusable configuration framework that reduced per-client setup time from 8 weeks to 3.

I also worked closely with the data science team to improve the model’s precision on specific fraud patterns we were seeing in the field — duplicate vendor submissions, split invoicing, and roundtrip transactions.

The Outcome

What I Learned

Scaling a platform across diverse enterprise clients is fundamentally a communication problem as much as a technical one. Each client had different definitions of “fraud” — aligning on that upfront, before touching any data, was the highest-leverage thing I could do on every engagement.