Banks and microfinance institutions
Monitor account and transfer activity while keeping AML investigations and reporting evidence connected.
Typical fit
- Account and transfer monitoring
- AML case operations
- goAML-ready evidence
Ingest transaction activity, apply rules and behavioural signals, investigate alerts, and prepare reporting evidence from one operational workspace.

Product overview
Bring ingestion, monitoring controls, alert review, case evidence, and reporting preparation into one traceable workflow.
Apply rules, screening controls, and behavioural signals to eligible events.
Customer, transaction, device, and case history stay linked.
Decisions and filing evidence remain review-ready.
Flexible deployment
Use live API ingestion for supported decisioning integrations, or monitor asynchronously through adapters and batch uploads.
WatchTower capabilities
Give risk teams the live activity, decision context, and case evidence they need without moving between disconnected tools.
Live monitoring
Stream events through the API, evaluate eligible activity against rules and customer context, and return an allow, review, or block response where inline decisioning is supported.
Real-time decisions
Inline where supported
Customer context
Transactions and behaviour

Controls and decisions
Start with built-in AML and fraud typologies, add your own rules, and dry-run changes before production.
Rule preview
High value + new device
Investigations and reporting
Assign alerts, track SLAs, document the decision, and prepare reporting from the same case record.
Case CASE-2048
Unusual transfer sequence
Evidence
12 records
Filing readiness
Ready
Start with built-in AML and fraud controls, add tenant-specific rules, and dry-run changes before activation.
Customer intelligence
Connect transactions and behavioural events to one customer profile, so activity such as a password reset followed by a large transfer reads as one risk story.
Use AI assistance where enabled while keeping controls, activation, and final investigation outcomes under team review.
01
Where enabled, describe the behaviour to monitor, review the drafted rule, and dry-run it before activation.
02
Use baseline and event signals to prioritize review. These signals support analysts and do not autonomously block activity.
03
Dry-run control changes and preserve who changed what before a rule reaches production monitoring.
Send eligible events through the API, an adapter, or a batch upload.
Apply active rules and screening controls to the available event context.
Create alerts with the transactions and signals that triggered review.
Assign cases, preserve evidence, and document the analyst decision.
Export case evidence or prepare goAML-ready XML when required.
Regulatory reporting
Run readiness checks, generate XML from captured case evidence, and preserve filing versions and status. Your team remains responsible for final review and submission.
Give analysts one place to review alerts, collaborate on cases, and preserve the final decision.
In compliance software, trust is specifics, not adjectives.
Sensitive customer fields are encrypted with AES-256-GCM before they touch the database.
Rule changes, case actions, and decisions are preserved in the audit history.
Analysts, reviewers, and admins each see and do only what their role allows.
Machine-to-machine ingestion uses hashed API keys with optional IP allowlisting.
Customer fit
Built for regulated financial teams that need to monitor high-volume money movement and carry risk decisions through investigation and reporting.
Monitor account and transfer activity while keeping AML investigations and reporting evidence connected.
Typical fit
Apply monitoring and fraud controls to high-volume payment activity, with inline responses where supported.
Typical fit
Monitor disbursements, repayments, and borrower activity for abuse and account takeover signals.
Typical fit
Detect corridor, velocity, sanctions, and cross-border risk patterns with full customer context.
Typical fit
See how WatchTower can fit your ingestion model, monitoring controls, case operations, and reporting process.
WatchTower works alongside Remllo Compliance and Remllo Identity, connecting transaction monitoring, AML monitoring, regulatory compliance, and identity verification in one ecosystem.
Related solutions: Transaction Monitoring, AML Transaction Monitoring, AI-native Transaction Monitoring, AI Fraud Detection.
Product FAQ
Understand how WatchTower fits into transaction monitoring, AML investigations, fraud controls, and regulatory reporting workflows.
Remllo WatchTower gives banks, fintechs, lenders, payment companies, and other transaction-led financial institutions infrastructure for real-time transaction monitoring, AML review workflows, fraud detection, and alert investigation.
Yes. WatchTower is designed to handle anti-money laundering monitoring and fraud detection in the same risk operations environment so teams can investigate with shared context.
Yes. WatchTower supports real-time event ingestion and alerting. For supported inline integrations, a response can inform an allow, review, or block decision; other deployments can monitor activity alongside the transaction flow.
It combines rules, behavioural context, and workflow automation, with AI-assisted rule drafting where enabled. Analysts remain responsible for reviewing controls and investigation outcomes.