Trusted by institutions building next-gen finance
AML Transaction Monitoring
Streamline regulatory compliance and minimize false positives.
Analyze every transaction in milliseconds, using sophisticated ML algorithms to detect suspicious patterns that traditional rule-based systems miss.
Real-time and batch transaction analysis
Pre-built, adaptable rulesets for current money laundering detection
Advanced ML models with 95% detection accuracy
Continuous learning and adaptation


KYC/KYB Automated Onboarding
Reduce your manual verification workload without sacrificing thoroughness.
Transform your customer onboarding process with intelligent automation that maintains rigorous compliance standards while accelerating legitimate customer acquisition.
Streamlined customer onboarding with automated verification
Advanced data analysis and verification technologies
Compliance assurance with reduced manual errors
Integration with 80+ third-party data sources
FRAML (Fraud + AML)
Improve visibility across the entire customer lifecycle.
Break down operational silos with Oscilar's unified FRAML approach that combines fraud prevention and AML compliance into a single, comprehensive risk management strategy.
Unified view of fraud and AML risks
Enhanced collaboration between teams
Comprehensive risk assessment across customer journey
Proactive prevention of financial crime


AI-Powered Insights
Understand the context behind a case. Oscilar AI helps surface details and uncovers connections, pointing you towards potential resolutions faster.

Dynamic Risk Scoring
Continuously assess and score risk profiles using advanced analytics and ML. Dynamically adjust with new data so you can be more proactive.

SAR Automation & E-Filing
Say hello to direct, automated FinCEN SAR filing. Pre-populated templates streamline your submissions so you can stay in compliance.
Unify Your Risk
Ditch the point solutions and fragmented tool chain. Monitor all your risk in one platform.
Fight Modern Threats
AI doesn't just accelerate the good guys. Fight fire with fire using AI that keeps you one step ahead.
Innovate Faster
Adjusting your strategy on the fly has never been easier. Make changes quickly and backtest against historical data.
Customers see results with Oscilar.
FAQ
Glad you asked.
What is AML transaction monitoring for banks?
AML transaction monitoring is the risk-based process of reviewing customer and account activity to identify patterns that may indicate money laundering or other suspicious behavior. It combines transaction data with customer, product, geography, and historical context to create alerts for investigation. It is one part of a broader BSA/AML program, alongside customer due diligence, sanctions controls, case management, reporting, and governance.
How is modern AML transaction monitoring different from rules-based monitoring?
Rules remain useful for explicit policies and known typologies, but rules alone tend to evaluate fixed conditions in isolation. Modern monitoring combines configurable rules with behavioral baselines, anomaly detection, customer risk, network context, and alert prioritization. The goal is not to replace rules with a black box; it is to add context, testability, and adaptive detection while preserving explainable controls and human review.
How can a bank modernize transaction monitoring without replacing every upstream system?
Modernization can be phased. A bank can keep upstream data sources and an incumbent monitoring system while adding a decisioning or investigation layer that normalizes alerts, enriches them with customer context, and improves routing and review. The key requirements are reliable data mapping, reconciled alert counts, clear system ownership, and a controlled migration plan. Oscilar's modular agents can consume alerts from existing monitoring systems, while its broader platform can unify data and workflows when a bank is ready.
How can banks reduce AML false positives without weakening detection coverage?
Reducing false positives should come from better context and testing, not simply suppressing alerts. Banks can segment customers and products, enrich activity with risk and behavioral signals, prioritize alerts, and tune scenarios against historical outcomes. Every change should be backtested for both workload and missed-risk effects, then monitored after release. Oscilar supports rules, models, testing, and prioritization in the same decisioning environment.
What governance controls should a bank expect for model validation, rule changes, and examiner review?
A bank should be able to identify every rule and model owner, preserve versions, document approvals, test changes against historical data, monitor performance after release, and reconstruct the inputs and rationale behind a decision. Human overrides and exceptions should also be logged. Oscilar supports backtests, A/B tests, and unit tests for risk workflows; its agents retain the input, reasoning, and output for review. The bank still owns validation standards, approval authority, and regulatory accountability.
How should a platform support multiple lines of business while preserving centralized oversight?
Use a common data model, control taxonomy, case standard, and reporting layer across the bank, while allowing each line of business to configure its own products, thresholds, workflows, and escalation paths. Central teams should see versions, approvals, exceptions, and performance without forcing identical policies everywhere. Oscilar's unified platform connects data across risk touchpoints and lets teams create, test, and adjust tailored workflows, supporting local risk decisions within a shared operating and oversight framework -- without forcing every business into identical controls.










