Accounts Payable: How AI Agents Detect Fraud

Fraud is an unfortunate reality in the world of accounts payable. Where there’s money, there are people who are willing to do almost anything to get their hands on it. It might be a new supplier that has altered an invoice by a small amount, hoping to go unnoticed. Or an opportunistic cybercriminal who has found a way into your system. Worst of all, it could be someone on the inside, forging blank checks to themselves.

The harsh truth is that the more your accounts payable workflows rely on humans, the more potential there is for fraud. Automating workflows can help, especially within large organizations that have siloed systems and a high volume of invoices. AI agents can make automated workflows even smarter by flagging inconsistencies and alerting human decision-makers to potential fraud.

But before you can reconcile invoices with their corresponding purchase orders, check for duplicate payments, and verify that 

payments are going to whom they’re meant, you need to be able to see all your accounts payable documentation. This can be incredibly difficult when dealing with financial data for two reasons. One, moving data to a centralized database can lead to even more risk of data exposure. Two, financial data comes from many disparate sources and in various forms: for example, hand-written invoices, PDFs, or entries in purchasing systems or accounting systems. One research firm found that nearly half (49.7%) of all invoices received by the average enterprise were paper-based.

Kamiwaza designed an Intelligent Document Processing (IDP) solution that processes data where it lives, instead of forcing it into a cloud. This distributed data engine, combined with AI agents that automate complex, multi-step processes and orchestrate data from different sources, provides a unique solution that’s helping accounts payable teams more easily prevent fraud.

How Much Money Do Finance Teams Lose to Fraud?

Accounts payable fraud is more common than you might think. Organizations lose about 5% of their revenue to fraud each year, according to the Association of Certified Fraud Examiners. In its report, the ACFE says that two of the most common schemes are check and payment tampering, with a median loss of $155,000, and billing schemes, with a median loss of $100,000.

With check and payment tampering, the person committing fraud steals or intercepts a check and forges a signature, changes the payee name, or modifies the amount. Billing schemes can happen in several ways. A supplier or employee might solicit a payment for fake goods or services, often by creating a shell company. A vendor might submit duplicate invoices for legitimate work. An employee might request reimbursement for personal items.

Finance teams usually attempt to detect and correct these kinds of fraud by reconciling cleared checks against the issued check register on a regular basis (sometimes daily). 

But in spite of their best efforts, accounts payable teams are rarely able to recover every dollar lost to fraud. And the monetary losses are just the beginning. Fraud takes time to investigate and can damage an organization’s reputation. Weak controls can also trigger audits under the Sarbanes–Oxley Act (SOX), Payment Card Industry (PCI) standards, or internal processes.

Document Automation Agents Provide the Best AI Analytics for Fraud Detection

Although accounts payable teams can’t eliminate fraud attempts, they can make their processes more resistant to fraud. AI agents are adding more intelligence to document automation workflows, improving the ability to detect and prevent fraud in accounts payable, expense processing, and vendor management. 

Instead of relying on passive rule-based checks, agentic AI for fraud detection uses machine learning to detect suspicious behavior, alert human decision-makers, and stop payments. AI agents can validate more complex information, like vendor names, bank accounts, tax IDs, and invoice totals, across multiple data sources. They can also integrate into other finance workflow systems, such as invoice capture and payment execution.

AI can recognize patterns better than even the most experienced finance professional, picking up on anomalies that may get missed by rules-based systems. For example, AI can flag payments to new vendors outside business hours or sudden bank account changes.

What are the Best AI Agents for Fraud Detection in Accounts Payable?

Many enterprises and large organizations have finance and purchasing data across multiple locations. Moving that data would be expensive and time consuming. The best AI-driven solutions for preventing expense fraud should work across all of your data sources, eliminating blind spots in your organization. This is especially helpful if you have siloed departments with multiple approvers. Here are a few considerations when using AI for payment fraud.

Accounts payable data isn't centralized. How will you access it all? 

A distributed data engine, like the one in Kamiwaza’s Intelligent Document Processing (IDP) solution, can access and process data across any system without moving it. This gives you a complete view of all your sources, including invoice and billing data, vendor master data, payment data, expense and reimbursement systems, procurement systems, ERP systems, and general ledger data.

How will you keep data secure while it’s being processed?

Many AI solutions require you to send your data to the cloud or share it with third parties, which can put sensitive or regulated data at risk. Kamiwaza’s IDP solution processes documents and data within your secure environment, so that no data leaves your infrastructure. You can assign members of your team to different data permissions based on their roles, reducing the risk of data being mishandled. 

How will you maintain the audit trail required for SOX/SOC compliance? 

Weak internal controls for accounts payable increase your fraud risk and jeopardize Sarbanes-Oxley (SOX) and Service Organization Control (SOC) certifications. Audits require detailed evidence, such as general ledger and accounts payable/receivable reports. With an internal control accelerator, Kamiwaza’s IDP solution automates the audit trail, provides real-time tracking of financial entries, and delivers immutable records. Every step is timestamped and recorded, creating a verifiable chain of custody. This can help detect unauthorized approvals, payment tampering, and edits that were made after approval.

What kind of results can you expect?

Before deploying a solution, your finance team should work together to determine what success looks like. For example, with Kamiwaza’s IDP solution, we have seen cost savings and an 87% reduction in processing time compared to manual data entry, with automation ensuring the consistency required for SOX compliance. 

Learn More about Using AI Agents for Fraud Detection 

When it comes to accounts payable fraud, it’s not a question of if or even when it will happen. It’s already happening today across organizations of every size. Automating workflows can help finance teams detect, prevent, and correct fraud without adding to their headcount.

Kamiwaza is ready to help you explore how agentic AI and distributed processing can prevent fraud while keeping data secure. Learn more about use cases for AI agents in finance, including invoice capture, three-way matching, and reconciliation.