Transaction Monitoring
We provide end-to-end transaction monitoring operations for firms dealing with high numbers of alerts, growing backlogs, rising regulatory expectations and limited capacity. We work directly within your existing TM environment to improve throughput and quality, helping your teams focus on the cases that matter most.
The service is designed for banks, fintechs, crypto, payments and other regulated firms who want a fast, low-risk way to stabilise TM performance, with a clear pay-per-alert commercial model and a straightforward pilot to get started.
Our Delivery
We handle the full TM workflow, including:
Working alerts from your existing transaction monitoring systems
Building and reviewing cases in your case manager
Investigating behaviour over time (customer, peer group and historic patterns)
Preparing recommendations, escalation rationale and SAR-ready narratives where required
We also support TM teams through periods that typically increase operational risk, including:
System transitions and parallel implementations
Step-changes in alert volumes following rule/scenario updates
Region-specific language and regulatory coverage, including EU-based operations where local data and compliance rules apply
Integrate “in flight” without disrupting live operations
Our teams and tooling plug into your existing TM platform and case management workflow without disrupting live rules, scenarios, workflows or projects already underway. We operate “in flight” so you can improve performance quickly while keeping business continuity.
Agentic AI in Transaction Monitoring
Our TM service is powered by agentic AI workflows designed by financial crime SMEs. In practice, our agentic AI can:
Pull data from multiple systems
Join it at customer, relationship or network level
Normalise key signals and present a clear view of each alert
Prepare the context and evidence pack so analysts start with a structured case, not a blank screen
Agentic triage and prioritisation: focus on what matters first
Alert volumes aren’t the problem, attention is. Our agentic AI helps reduce operational drag by:
Scoring and prioritising alerts using risk, behaviour and contextual signals
Routing work so higher-risk items are handled first
Reducing aged alerts and improving SLA performance by smoothing peaks and queue pressure
This means human teams spend their time on judgement and risk decisions, not queue management.
Once an alert is selected, our agentic AI acts as a digital investigation assistant:
Gathering supporting evidence across approved sources
Checking peer and historic behaviour patterns
Organising notes and assemble key findings
Draft clear case summaries so analysts can focus on judgement, escalation and decision quality
QA-first validation for stronger control
We deploy automation safely using a validation-first approach:
Our agentic AI can run in parallel with analysts, comparing outcomes and highlighting disagreements
Providing a 100% QC layer on alert dispositions, decision consistency and scenario performance
Supporting both Level 1 and Level 2 operating models by improving accuracy and standardisation before any automation is expanded
Specialist investigators, assessed for quality, not just throughput
We select and train specialist TM investigators through practical scenario-based assessment so teams can operate confidently in live environments. Performance is managed against quality outcomes, not just volume, with senior oversight on hiring, coaching and consistency.
To accelerate readiness, analysts train on a custom TM case simulator built from real-world examples — helping them reach productivity quickly and handle live alerts with confidence.
Continuous learning and calibration with SMEs
TM performance drifts unless it is actively managed. We run regular calibration and knowledge-sharing to keep alert handling aligned to your risk appetite:
Rules and scenario interpretation
Agent workflows and triage behaviour
Analyst decision consistency and documentation quality
Monitoring, reporting and operational control
We provide near real-time MI and dashboards so performance is visible and controllable, including:
Alerts received and worked, aged alerts and SLA performance
Quality scores and decision consistency
Typology trends and emerging risks
Rule/scenario performance signals so issues are spotted early and corrected quickly
We also use analytics to forecast demand and resource correctly across hubs. This supports:
Capacity planning and demand forecasting
Fast pilot stand-up
Rapid scaling when volumes spike, typologies change or systems are updated
Global delivery with flexible coverage
We operate a multi-hub delivery model with flexible shift patterns and 24/7 coverage where needed, allowing work to move between locations as volumes change during the day.
Ongoing BAU TM support is delivered by stable teams with capacity flexed up or down as your business and risk appetite evolve.
Backlogs, lookbacks and remediation are supported through rapid mobilisation to clear historic backlogs, support regulator-driven lookbacks and remediate weaknesses found in past reviews.
Governance, explainability and regulatory comfort
TM decisions are regulated and accountable, and we keep them that way:
Financial crime SMEs design scenarios, workflows and agentic AI behaviour
Edge cases are reviewed by experienced leads
Final responsibility for escalation, exits and SAR decisions stays with humans
We run TM with the control framework supervisors expect:
Documented processes and consistent case handling standards
Clear audit trails for both human decisions and AI-assisted recommendations
Reporting that supports internal audit, model governance and supervisory review
Transparent pricing built for predictable budgeting
Our standard commercial structure is a transparent per-alert model, so your cost is predictable and does not fluctuate with training time, sick leave or holiday. Where flexibility is needed, we also support:
Time-and-materials for project work and remediation
Pre-scoped blocks for urgent investigations, lookbacks or change programmes
Our pricing is designed to compete with in-house offshore teams on cost, while adding agentic AI, stronger MI and a QA-first control layer on top.
We agree quality thresholds upfront and stay accountable to them:
Outcome-focused incentives that reward accuracy and defensibility
“Not charged” policies for work below the agreed standard, so quality remains non-negotiable
Faster procurement and onboarding
We have experience operating as a material outsourcer to major banks, with ready-made due diligence packs and responses to support vendor risk, procurement and onboarding, so onboarding doesn’t drag on for months.
How we start: a simple pilot-to-BAU journey
Working with us follows a clear, low-risk path:
Discovery and scoping (systems, volumes, controls, risk appetite)
Initial calibration (scenario interpretation, QA standards, triage approach)
Short parallel run / pilot on pay-per-alert
Review, refine and agree success measures
Scale into BAU and (if needed) backlog/lookback work