Finance: Every transaction, checked as it happens.
For banks, fintechs, exchanges, payment companies and brokers: fraud, AML and risk decisions in real time, and the review work that follows.
What we build
Transaction monitoring
Rules and models on every payment, trade, transfer and withdrawal as it arrives, alongside the KYC, KYT and sanctions vendors you already use.
Fraud detection
Account takeover, scam payments, mule accounts and address poisoning, detected from behavior across logins, devices, payments and on-chain activity.
AML and sanctions
Typologies mapped to the jurisdictions you operate in, sanctions screening, and alerts routed to the right queue with the evidence attached.
Risk scoring
Customer and transaction scores that update as behavior changes. Each score carries its reasons, so it can be checked before anyone acts.
Compliance AI
Language models triage alerts, summarize cases and draft SAR and STR narratives from the evidence. An analyst reviews every draft and decides.
Performance at peak
Order paths, payment APIs, websockets and databases profiled and tuned to hold latency when volume spikes. Proven with your own measurements.
Decided before the money moves.
How it works
Transactions leave your core platform as events. Your vendors screen them, rules and models score them, and clear cases pass. The rest reach a review queue with a summary already drafted.
Fast at peak. Auditable after.
Why it holds up
Latency budgets
Each check in the payment path has a time budget. When a vendor is slow, a defined fallback takes over before it runs out.
Back-pressure
Queues absorb bursts and scoring scales with load. High-risk work goes first, and nothing is dropped silently.
Replay and audit
Every event and decision is stored with the rule and model versions behind it, so any alert can be replayed and traced.
Fault tolerance
Processing runs across zones and restarts from checkpoints, so a failed node delays a check instead of skipping it.
What we measure
- p99 decision latency
- Throughput at peak
- Alerts that lead to action
- False positive rate
- Time per alert
- Fraud stopped before funds leave
- Cost per transaction
Common questions
What does Stelcorp build for financial companies?
Stelcorp builds real-time transaction monitoring for banks, fintechs, exchanges, payment companies and brokers: fraud detection, AML and sanctions, risk scoring and compliance AI, plus performance work on the payment and order paths that have to hold up at peak. Fraud detection covers account takeover, scam payments, mule accounts and address poisoning, from behavior across logins, devices, payments and on-chain activity.
How does Stelcorp handle large transaction volumes?
Each check in the payment path has a time budget, with a defined fallback when a vendor is slow. Queues absorb bursts and scoring scales with load; high-risk work goes first and nothing is dropped silently. Processing runs across zones and restarts from checkpoints, so a failed node delays a check instead of skipping it.
Does it replace our KYC, KYT and sanctions vendors?
No. Rules and models run on every payment, trade, transfer and withdrawal alongside the KYC, KYT and sanctions vendors you already use. Your vendors screen each transaction, rules and models score it, clear cases pass, and the rest reach a review queue with a summary already drafted.
How is AI used in compliance work?
Language models triage alerts, summarize cases and draft SAR and STR narratives from the evidence. An analyst reviews every draft and decides.
Can every alert and decision be audited?
Yes. Every event and decision is stored with the rule and model versions behind it, so any alert can be replayed and traced. Each risk score carries its reasons, so it can be checked before anyone acts.
Start with one flow.
An alert queue, a payment path, a score you don’t trust. Three weeks to map it, measure it and put a working prototype on your data.
Tell us about the flow