Cheaper, more accurate, easy to extend: automating fraud and compliance operations

13 October 2026 · AgenticAuto

It is 8:10 on a Monday. The overnight queue holds 1,412 alerts. Most will turn out to be nothing, but each one still needs an analyst to pull the transactions, check the device, look up the beneficiaries and read the customer's file before deciding. Somewhere around number 900 is a real mule account, still moving money. Down the corridor, a backlog of KYC reviews is overdue, and a customer has been waiting a week for a claim.

Every financial institution knows this work. It is the most expensive part of fighting fraud and staying compliant, and it is still mostly done by hand.

Why hasn't this been automated? Because the work needs judgement, which robots that copy clicks on a screen cannot provide. And it needs proof, which AI chatbots cannot give. No regulator will accept "the AI decided".

The goal is not to let AI decide. It is to make sure every decision is made faster, by the right person, with the evidence in front of them.

MadeEasy is an AI operations platform. A team describes how a process works, in plain language or with its procedure manual, and MadeEasy builds the AI agents, rules and connections that run it, proves them on real past cases, and runs the process every day. It works in any industry. Here is what it does in fraud and compliance.

1. Fraud detection, at bank volume

MadeEasy connects to the bank's transaction feeds and scores transactions as they arrive, against the bank's own rules and fraud models: velocity, unusual amounts, new beneficiaries, device changes, known bad accounts. Scheduled sweeps look across days and weeks for what a single transaction cannot show, such as mule networks, structuring and money moving in and straight out.

Scoring runs as ordinary software, so every transaction can be checked at very low cost. AI is used only on what is flagged. Suspicious accounts can be restricted under the bank's fraud desk procedure, with the fraud desk's approval. MadeEasy works alongside the bank's existing fraud controls rather than replacing them.

How a fraud detection process is set up in MadeEasy

Fraud moves fast. In Nigeria most transfers settle in seconds over NIBSS Instant Payment, and stolen funds typically pass through a chain of mule accounts within minutes to hours. So the work that recovers money happens in the minutes after a transfer posts: spotting the mule account, restricting it, alerting the other banks, and reporting. That is where MadeEasy works. The decision to approve a card payment at the till stays with the bank's in-line authorisation system.

Regulation sets the clock:

The bank's fraud team describes the process in its own terms. For example:

"Monitor every inward and outward NIP transfer as it posts. Flag an account that receives money from many unrelated senders and moves most of it out within minutes, a high-value transfer to a first-time beneficiary straight after a SIM or device change, or anything our fraud model scores above our threshold. For a flagged account, ask the fraud desk to approve a post-no-debit restriction, alert the other bank's fraud desk, and open a case. If the analyst confirms fraud, watch-list the BVN and draft the suspicious transaction report for compliance to file on goAML."

From that description, MadeEasy builds the process below.

Setting it up takes five steps:

1. Connect the data. Postings from core banking and NIP, channel and device logs, and the customer's KYC and BVN details, read through the bank's own interfaces.
2. Write the typologies as rules in code. From the bank's fraud policy and the NFIU's red-flag indicators: money fanning in from many senders and straight out again, balances left near zero, amounts kept just under thresholds, a SIM or device change before a high-value transfer. Each rule is reviewed before it is used, and the same transfer always gets the same result.
3. Add the model and set the thresholds. The bank's own validated model, or one we build from its labelled past cases. Thresholds are tuned on past alerts to balance missed fraud against the alert volume the team can handle, and scores are watched for drift.
4. Tie every action to the fraud desk's procedure. A post-no-debit restriction only with the fraud desk's approval, the alert to the other bank, the BVN watch-list, the case and the report draft: each one logged with who approved it and when.
5. Back-test before go-live. Replay months of past transactions, including confirmed fraud and clean activity. The gate refuses go-live until the process catches the known fraud within an alert volume the team can work.

Once live, the typologies change as fraud changes. "Flag accounts opened in the last 30 days that receive more than ₦2 million from over ten senders in a day" is described, back-tested, approved and released as a new version.

2. Investigation and reporting

For every alert, whether raised by MadeEasy or by the bank's existing systems, MadeEasy gathers the evidence: the transactions, the device, the beneficiaries, the customer's KYC file and past alerts. It writes the case in plain language, citing that evidence, with a recommendation and its reasons.

The analyst reviews a complete case instead of assembling one, and decides: close it, or escalate. When a case is escalated, the suspicious-transaction report is drafted for the compliance officer to review and file. Nothing is closed or filed without a named person.

3. KYC and customer due diligence

MadeEasy reads identity documents, utility bills and statements, including photos customers send from their phones, and checks each one: does the name match, is the document current, is the address consistent, does the income fit the profile? It reviews screening results, schedules periodic refreshes, and asks the customer for anything missing. Only the exceptions reach a compliance officer.

4. Claims, prepared for a fast decision

For insurers and bancassurance teams, claims arrive by email, app or website with photos and documents. MadeEasy checks them against the policy terms, flags indicators of fraud, and prepares each claim for a decision. Straightforward claims go for approval in hours; complex ones reach an adjuster with a complete file.

5. Customer service on any channel

One assistant, trained on the institution's approved policies, answers customers on whichever channels it chooses: website, email, WhatsApp, its mobile app or internet banking. It can read a photo of an error screen or a document, and when a customer needs a person, such as for a complaint or a dispute, it hands over with the full conversation.

What changes, in one table

Cheaper: what automation really costs

The licence is the smallest part of a traditional automation bill. Forrester found that for every dollar spent on the software, $3.41 went on services to make it work: building the robots, maintaining them, and repairing them when the applications they click through change. EY has found that 30 to 50% of initial projects with traditional robots fail. And single-purpose tools for fraud cases, KYC and claims each come with their own contract and integration.

List prices and published contract data; actual contracts vary with volume and negotiation. A process may need more than one robot in traditional automation; we assumed one.

MadeEasy costs less for structural reasons, not because of a discount:

• One platform for every process. Fraud, KYC, claims and service run on the same platform, with one record and one contract.
• Volume work costs almost nothing. Scoring, matching and arithmetic run as software. AI is used only where reading, judgement or writing is needed.
• No months of development. A process starts from a description of the work, not from a developer recording clicks.
• No mark-up on AI. MadeEasy uses your own account with your AI provider, and shows you the cost of every task.
• Less to repair. MadeEasy works with your systems' data, not by clicking through screens, so a new screen layout does not break it. A change is described, tested and approved, not rebuilt.

What could it give back to your team?

Use your own figures. Nothing below is our estimate of your institution.

More accurate: proof, not promises

The question to ask of any automation in fraud and compliance is not "is it clever?" but "can we prove it did the right thing?" MadeEasy answers that in four ways:

• Rules and calculations run in code, not AI. Scores, thresholds and totals give the same result every time. Where AI is used, the reason is written into the design.
• Nothing goes live without passing its tests. Each process is tested on real past cases, including the hard ones, and can only be switched on through a gate that refuses if any test fails. The tests run again after every change.
• People make the decisions. Closing an alert, filing a report, approving a claim: each waits for a named person, and their decision is recorded.
• Every step is on record. What each step received, what it did, what it produced and who approved it, ready for an auditor or regulator, and replayable from start to finish.

Easy to extend: the next process is configuration, not a project

The real cost of automation is rarely the first process. It is the tenth, when every change needs another project.

In MadeEasy, a new process starts from a description of the work, or from the procedure your team already follows. MadeEasy proposes the steps, checks each one against the systems it will use, and shows you the design before anything is built. Changing a process works the same way: "escalate any transfer above ₦5 million to a second reviewer" is described, shown, tested and approved. Connections built once, to the core banking system, the card platform or the screening service, are reused by every process after it.

Fraud detection, KYC, claims, disputes, reporting: one platform, one record, and the tenth process as easy as the first.

Questions your board will ask

A 90-day plan

1. Weeks 1 to 2

   Choose and describe. Pick one costly process, such as fraud alert review. Share the procedure and a set of past cases. MadeEasy drafts the design; your team reviews it.

2. Weeks 3 to 4

   Connect and test. Connect the systems it needs, and test it on real past cases, including the hard ones. It must pass them all.

3. Weeks 5 to 8

   Run alongside. It runs on live alerts next to your analysts, who still decide. Compare speed, accuracy and cost every day.

4. Weeks 9 to 12

   Go live, then the next one. Switch it on with sign-offs in place, and start KYC, claims or disputes on the same platform.

Prefer us to build it?

We can build the process with your team at a fixed price agreed before we start, then hand it over running. The price depends on how complex it is:

One-off, per process, including tests, a run alongside your team and 30 days of support after go-live. Delivery is often faster when everything the process needs from outside MadeEasy is ready at the start: access to your systems, sample files, and the people who sign off. See pricing for what each level covers.

Your data, your rules

MadeEasy can run as a service, or on your own infrastructure, in your own data centre or cloud region. Customer data then never leaves the environment you control, which supports your obligations under data protection law and your own risk policies.

Sources

1. NIBSS fraud figures for 2025, reported by TechEconomy, June 2026.
2. "The investigator-centered approach to financial crime", McKinsey.
3. Fenergo, regulatory penalties in 2025, January 2026.
4. CBN on the 30-minute fraud response time, ThisDay, January 2026.
5. CBN circular on the BVN fraud watch-list, Nairametrics, March 2026.
6. Compliance requirements for the NFIU, Legal500 (Money Laundering Act 2022, section 7).
7. CBN Baseline Standards for Automated AML Solutions, DLA Piper Africa, April 2026.
8. Fraud monitoring obligations in Nigeria's payment system, SRJ Legal.
9. A major vendor's published price for an unattended robot, $150 per robot a month.
10. "4 surprising RPA research findings from Forrester", CIO, December 2019.
11. Published contract data for a leading automation suite, median annual value across 42 purchases.
12. An automation vendor's analysis of why projects fail, citing EY.
13. MadeEasy pricing.