Sanctions and AML Screening in Banking

Published on Sept 03, 2026

Sanctions and AML Screening in Banking: 5 Ways Banks Can Scale Their Screening Operations Without Increasing Headcount

Reviewed by: Tom Devlin, Managing Director at KYC360 
Last Updated 03/08/26


Screening volumes can rise quickly for teams managing AML in banking. Clients and counterparties may need screening at onboarding and throughout the relationship as sanctions, PEP and adverse media information changes, while payments may also require sanctions screening at the point of execution. For sanctions screening, the FCA Financial Crime Guide says firms should have effective, up-to-date systems appropriate to the nature, size and risk of their business. The challenge is handling growing volumes without simply adding analysts or weakening controls. 

The Screening Challenge at Scale

The scale of UK sanctions exposure has also increased. OFSI’s 2024-25 Annual Review reported more than £37 billion of assets in the UK as frozen under financial sanctions, compared with £24.4 billion in 2023-24. At the same time, the FCA has identified weaknesses in reference data, list management, name matching and alert handling. At high volumes, poor calibration or weak data can create large queues of low-value alerts. At the other end of the spectrum, insufficient sensitivity can allow genuine matches to go undetected. 

For internationally active banks, changing regimes and potential secondary sanctions exposure add further complexity. Adding reviewers does not address those underlying control challenges. Five areas can help create capacity: risk-based calibration, batch screening, better input data, automated triage and consolidated screening workflows. 

1. Risk-Based Calibration to Cut False Positives  

High false-positive volumes become expensive when analysts must investigate large numbers of alerts that ultimately prove irrelevant. But reducing sensitivity across the board creates the opposite problem: fewer alerts, with a greater risk that relevant matches are missed. In its May 2026 review of firms’ sanctions systems and controls, the FCA found wide variation in screening configuration and testing. It also identified systems that struggled with spelling variations, additional name elements and non-Latin characters.

Risk-based configuration allows banks to vary matching parameters according to client risk rather than applying one threshold across the entire book.  The rationale for thresholds and filters should be documented and periodically tested.  KYC360’s 3D risk-based screening applies configurable screening parameters according to client risk level, helping concentrate analyst attention where greater scrutiny is needed.  


2. Effective Overnight Batch Screening 

Sanctions lists and client circumstances do not stand still. A client may present a different risk later because of a new designation, a change in ownership or newly available information. Automated batch screening allows banks to re-screen large populations of existing clients and counterparties as data changes, rather than relying on analysts to repeat checks manually. KYC360 supports screening across large standing populations overnight, with ad-hoc and batch screening serving different operational needs. Batch screening should sit alongside point-in-time or real-time controls where an immediate decision is required. The aim is to make repeated screening routine while reserving human intervention for potential matches that need assessment. 

3. Improving Input Data Quality Before Screening  

Better matching starts with better input data. The FCA found gaps in firms’ internal records, including dates of birth that were missing, incomplete or entered as placeholder values. It also found errors and omissions in third-party data feeds and weaknesses where data moved between systems. No amount of matching sophistication can fully compensate for poor source information. Structured names, dates of birth, locations and other identifiers give the screening engine more information with which to distinguish a genuine match from a namesake. KYC360’s data quality assessment capabilities can help identify gaps and inconsistencies before screening, giving teams an opportunity to address input-data issues earlier in the process. 


4. Automating Alert Triage  

Once the underlying data is reliable, automation can take more of the repetitive work out of alert handling. Secondary identifiers such as date of birth, nationality and country can help narrow ambiguous name matches and distinguish them from unrelated people with similar names. Automated adverse media monitoring can also help narrow large volumes of information to cases that warrant closer assessment. 

Automation does not remove the need for judgement or effective escalation. OFSI’s Bank of Scotland case illustrates why. The bank’s automated sanctions screening did not generate an alert because it could not reconcile spelling variations associated with Russian-to-English translation. A manual adverse media check during a subsequent PEP review identified that the client was designated, but the sanctions connection was not correctly escalated. 


5. Consolidating Screening and Alert Management 

Even well-calibrated screening can create unnecessary work when sanctions, PEP, watchlist and adverse media checks are split across separate tools, workflows and reporting processes. Consolidating them can reduce duplicate handling. A single sanctions screening platform can bring sanctions, PEP, watchlist screening and adverse media results into a more consistent workflow. KYC360 integrates with data from Dow Jones, LSEG World-Check and LexisNexis and supports API-based integration, giving banks a choice of data while centralising screening and reporting. 

Consolidation does not remove the need to understand how screening logic and external data work. The FCA’s May 2026 review found examples of firms relying too heavily on historic vendor settings or assurances without sufficient internal challenge, validation or testing. OFSI has similarly made clear that delegating compliance functions within a group does not transfer responsibility away from the legal entity responsible for the relevant conduct. 

Conclusion

As screening volumes grow, weaknesses in data, calibration or workflow create more operational friction and greater control risk. Effective screening creates capacity by filtering noise earlier while preserving human judgement for the cases that need it. For a broader view of screening strategy, data, controls and implementation, read the Definitive Guide to Customer Screening for Banking.  

KYC360 applies these principles through risk-based configuration, flexible data sources and centralised alert handling. Request a demo to see how the KYC360 AML Screening Platform improves screening performance.  

 

FAQs

 

Sanctions screening compares client, counterparty and, where relevant, payment information against applicable sanctions lists to identify potential exposure to designated persons or restricted activity. Effective screening depends on accurate source data, appropriate matching rules, timely list updates, investigation procedures and clear escalation. 

Banks can reduce manual screening work through risk-based calibration, automated batch re-screening, better input data, secondary-identifier matching and consolidated alert workflows. Automation should remove repetitive work while directing trained analysts towards alerts that genuinely require investigation, escalation or a sanctions decision. 

Batch screening checks populations of existing clients or counterparties together, usually on a scheduled basis or following updated risk data. Real-time or ad-hoc screening is used when an immediate decision is required, such as during onboarding or payment processing. Banks may use both because they address different screening needs. 

The FCA expects screening and alert-management controls to be proportionate to sanctions exposure, appropriately calibrated, and regularly tested and reviewed. 

Banks should avoid simply lowering matching thresholds. Risk-based calibration, reliable secondary identifiers, better source data and testing against spelling, transliteration and formatting variations can help reduce low-value alerts. Thresholds, filters and exclusions should be documented and regularly tested so efficiency improvements do not introduce gaps in detection. 

 

 

 

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