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One AI-powered platform for KYC, AML
screening, monitoring, and investigations.
OVERVIEW
ALFA, Automated Learning for Financial Alerts, combines AI, machine learning and data analytics with the configurability required to keep pace with new threat actors and financial crime scenarios.
Its engine learns continuously from customer information and behavioral patterns in real time, and its deep learning capability is applied to the work that consumes the most capacity: identifying and eliminating false positives at Level 1.
CAPABILITIES
Continuous monitoring across accounts and payment activity, with machine learning applied alongside your existing rule-based detection rather than in place of it.
Intelligent automation applied to sanctions and watchlist screening with politically exposed person matching, providing a consistent safeguard against high-risk individuals and entities.
Matrixed risk scoring and customer profiling built on input parameters you configure, supporting customer due diligence and enhanced due diligence.
A risk-based approach that categorizes alerts by perceived severity, impact score and other parameters, with data-driven recommendations presented to the financial crime analyst.
Real-time reports generated from datasets within ALFA and presented through a dashboard accessible across devices, supporting the financial intelligence unit and enhanced due diligence teams.
HOW ALFA IS BUILT
ALFA generates alerts without suppressing or altering the alert-generating algorithm of your institution. Every alert remains intact and available, and ALFA improves the decision by making recommendations to your FIU and EDD specialists.
Rule-based detection is augmented with unsupervised learning techniques, including K-means clustering and support vector machines.
Every alert carries a tamper-proof audit record with date and time stamps and historical screenshots, which is what an examination requires and what most tooling cannot reconstruct afterwards.
Alerts and insights are built on certified, pre-authenticated records gathered in real time, not on aggregated data of unverified provenance.
Built-in evolutionary algorithms improve accuracy as volume grows, so returns increase with the institution rather than plateauing after deployment.
ALFA evaluates every integrated data source to reach a decision and, where the case requires judgment, presents the complete record to the analyst for manual review.
WHAT YOU GAIN
A unified platform to detect AML compliance risks and perform customer due diligence against current regulations and sanctions requirements, rather than across separate tools with separate records.
Investigative resource is allocated to high-risk cases and Level 1 analyst capacity is released from false positive review, which reduces the operational cost of investigations.
Reports are generated in real time from data already inside ALFA and presented on a dashboard, so periodic reporting stops being a separate manual task.
Alerts on suspicious transactions, sanctioned parties and high-risk customers are generated from pre-authenticated datasets and primary sources, and that consistency holds as volume grows.
ALFA integrates each institution’s historical data as portfolios come together, and builds connections between associated parties to reduce alert volume across the combined book.
DEPLOYMENT
ALFA integrates with your existing monitoring, case management and customer data platforms, and does not require replacement of the detection system your tuning and validation history are built on. Typical deployment runs to approximately two months.
Programs under sustained examination attention where alert volume has outgrown Level 1 capacity.
Institutions carrying full BSA and AML obligations without a proportionate investigation team.
Screening and due diligence across complex ownership structures and higher-risk client profiles.
High transaction volume with obligations that scale directly with customer growth.
Monitoring and screening across on-chain and fiat activity.
Long formLayered research on governance, model risk, and controls.
WeeklyShort signals from teams building AI inside regulated walls.
Practitioner guidesStep-by-step playbooks you can hand to an operating team.
Live & on demandSessions with practitioners, broadcast and archived.
NEED A TEXT HERE
ALFA integrates with your existing monitoring, case management and customer data platforms, and does not require replacement of the detection system your tuning and validation history are built on. Typical deployment runs to approximately two months.
No. ALFA works over your existing detection system and does not modify or suppress its alert-generating logic.
No. ALFA categorizes alerts by risk and presents a recommendation with the supporting data. Disposition remains an analyst decision, recorded in the audit trail.
It applies machine learning to categorize alerts by severity and impact and to connect associated parties, so analyst effort concentrates where risk is highest. The underlying alerts remain intact.
A date and time-stamped, tamper-proof record for each alert, including the data considered, the recommendation presented and the analyst disposition.
It is the optimization approach behind the engine that lets detection models improve against your own data over time rather than being retuned manually.
Approximately two months, against an industry norm of around four.
Share how your monitoring, screening and investigation workflows run today. We will show you
where ALFA reduces Level 1 review effort while your analysts keep every disposition decision.
