Fraud & AML Monitoring · Use case

Run transaction monitoring for AML

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Short answer

AML monitoring looks across transactions and time for patterns that suggest money laundering — structuring, rapid pass-through, mule networks. Regulators expect scenarios that fit your products, documented tuning and a clear audit trail from alert to decision.

What this use case is

AML monitoring looks across transactions and time for patterns that suggest money laundering — structuring, rapid pass-through, mule networks. Regulators expect scenarios that fit your products, documented tuning and a clear audit trail from alert to decision.

Who builds this

EMIs and payment institutions
Neobanks
Crypto platforms
Lenders
BaaS providers

What your customer sees

  1. 1Nothing, unless an investigation leads to a request for information

How Fraud & AML Monitoring solves it

1

Transactions and customer data ingested

Transactions and customer data ingested

2

Scenarios and models run on events and over time windows

Scenarios and models run on events and over time windows

3

Alerts generated with context

Alerts generated with context

4

Alerts triaged and investigated

Alerts triaged and investigated

5

Decision documented

Decision documented

6

Reportable cases escalated

Reportable cases escalated

Want to have

  1. Typology library relevant to your products
  2. Configurable scenarios and thresholds
  3. Customer risk scoring
  4. Network or link analysis
  5. Alert triage tooling
  6. Tuning documentation
  7. Audit trail

Optional

  1. Machine-learning alert prioritisation
  2. Crypto-specific typologies
  3. Simulation of threshold changes

Design decisions

Approach

Rules-based scenarios
Model-assisted
Hybrid

explainability versus efficiency.

Timing

Near real time
Batch

speed of detection versus cost.

What to put in your RFP

Scenarios

  • typologies
  • configurability

Risk

  • customer scoring

Analysis

  • networks
  • links

Workflow

  • triage
  • investigation
  • escalation

Governance

  • tuning records
  • audit

Commercials

  • per customer or per transaction
Add these to an RFP

How to evaluate providers for this use case

  1. 1Fit of typologies to your products
  2. 2Alert quality on sample data
  3. 3Tuning governance
  4. 4Investigator experience

Pitfalls

  • Generic scenarios that do not match your products
  • Untuned thresholds creating backlogs
  • No record of why thresholds changed

What providers will ask you

  1. Products and customer types
  2. Transaction volumes
  3. Current alert volumes
  4. Team size and licence holder requirements

Other Finlane categories that cover parts of this

This use case is solved mainly with Fraud & AML Monitoring. These categories cover specific parts of it and can be tendered alongside it.

RegTech & Compliance Ops

Regulatory reporting and compliance workflow

KYC, KYB & Identity

Customer risk data from onboarding

Crypto & Stablecoin Infrastructure

Blockchain analytics for crypto flows

Frequently asked questions

Other Fraud & AML Monitoring use cases

Prevent account takeover at login

Combine device, behavioural and network signals to challenge or block suspicious sign-ins.

Score transactions in real time

Run every payment through a scoring engine with rules and ML, and step-up risky flows to SCA or review.

Manage cases and SAR reporting

Investigate alerts in a shared case manager and export SAR/STR reports to regulators.

Scope run transaction monitoring for AML with Fraud & AML Monitoring providers

Scope this use case