Segmentation

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Glossary · Transaction monitoring

Segmentation

Also called customer segmentation, peer grouping

Definition

Segmentation is the grouping of customers or accounts with similar characteristics and expected behaviour so that transaction monitoring rules and thresholds can be set for each group. A retail current account and a corporate treasury account behave differently, so each segment gets scenarios and limits calibrated to its normal activity.

01 RETAIL02 SMALL BUSINESS03 CORPORATE04 PRIVATE BANKING
Fig. 1 · Segmentation
NYDFS Part 504 · SR 26-2
Key rulesNYDFS Part 504 · SR 26-2
Applies toNew York-regulated banks, check cashers and money transmitters
RegionsGlobal · US
01

How it works

Analysts build segments from data such as customer type, product, business sector, turnover and geography. Statistical techniques like clustering help confirm that customers in each segment behave alike. Thresholds are then tuned per segment, often using percentiles of historical activity. Segments are reviewed at least annually and whenever products, customer bases or typologies change.

Good segmentation cuts false positives without hiding risk. A single threshold applied to all customers either floods analysts with alerts on large businesses or misses suspicious activity in small accounts. Because segmentation drives what the monitoring system detects, supervisors and validators treat it as part of the model. Firms document the logic, test it and show how it maps to their risk assessment.

Step 1Profile customersCollect attributes such as type, sector, product and turnover.
Step 2Group behaviourCluster customers whose expected activity looks alike.
Step 3Tune thresholdsCalibrate scenario limits to each segment's normal activity.
Step 4ValidateTest segments for stability and coverage of known risks.
Step 5Review regularlyRevisit segments when products or customers change.
02

The rules

US · 1 January 2017NYDFS Part 5043 NYCRR Part 504, Banking Division Transaction Monitoring and Filtering Program Requirements

Requires a risk-based transaction monitoring programme with documented, tested detection scenarios and thresholds, and annual board or senior officer certification.

New York-regulated banks, check cashers and money transmitters
US · 17 April 2026SR 26-2Federal Reserve SR 26-2, Revised Guidance on Model Risk Management

Sets expectations for model development, validation and governance, superseding SR 11-7 and SR 21-8, the earlier statement on models supporting BSA/AML compliance.

Fed-supervised banking organisations, chiefly those above $30 billion in assets
03

Common questions

Why does segmentation matter for transaction monitoring?

Customers behave differently, so one threshold cannot fit all. Segmentation lets firms set limits that reflect normal activity for each group, which reduces false positives and makes genuine anomalies easier to spot.

How often should segments be reviewed?

Many firms review segmentation at least annually, and also when they launch products, enter new markets or see shifts in customer behaviour. Reviews check that customers still sit in the right group and that thresholds remain calibrated.

Is segmentation treated as a model?

Often yes. Because segmentation shapes what a monitoring system detects, validators and supervisors commonly include it in model risk management, expecting documentation, testing and independent review of the logic and data behind it.