Fraud Detection & Risk Detection
Transaction monitoring systems generate thousands of alerts. Most are false positives. ActionAI detects real anomalies, explains them clearly, and routes them to your team with full investigative.
85%
Fewer false positives
3x
Faster investigation
<4 wks
Time to deploy
01
The Problem
The Challenge
Fraud detection systems flag thousands of transactions daily, so investigators spend most of their time clearing false positives instead of pursuing actual fraud. By the time a pattern emerges, the lead has gone cold because context is spread across multiple systems with no clear explanation of what made the activity unusual.
02
How It Works
How ActionAI Solves It
ActionAI monitors transaction patterns across accounts and counterparties. When an anomaly appears, it shows the pattern that triggered it, the transactions involved, and how the activity compares to known fraud typologies. Alerts below your confidence threshold are routed with additional context for review. Alerts above the threshold arrive as investigation-ready packages. As investigators close cases, their decisions feed back into the model, reducing false positives and improving detection.
03
The Outcome
Key Capabilities
Alerts trigger when supporting evidence meets your threshold for investigation. Each alert includes the pattern, related transactions, and full context, so investigators focus on high-impact cases. False positive rates decrease as the system incorporates investigator decisions.
Results that speak for themselves
85%
False positive reduction
Higher-quality alerts for investigators
3x
Faster case resolution
Context-enriched alerts reduce triage time
100%
Faster case resolution
Every transaction scored and documented
Financial Services
In finance, every mistake has a footnote. A duplicate payment slips through because two instances of the same supplier have slightly different spellings in the vendor master, and the 10-K has to name the correction the following quarter. Reconcile a cash account against last month's bank statement, and the break carries into the year-end audit as a material weakness. Ground truth is the PO and goods receipt for AP, or the bank feed for a reconciliation. ActionAI scores every automated match and reconciliation against those controlling records, and high-confidence transactions post without a clerk opening the entry. When a match falls below threshold, ExEx (Explainable Exceptions) holds the posting and hands it to a reviewer with the failed check and source document on screen, so the reviewer opens the case knowing what to verify.
Related Use Cases
Frequently asked questions
AP and reconciliation at Emirates NBD at 1M+ daily transactions with auto-match moving from 90% to 99%+, invoice and procurement audit at RAK Ceramics at 99.8% accuracy, and month-end close acceleration at Healthy Poke (Day 9-10 to Day 3). Finance is the universal entry point for ActionAI across every vertical.
The posting holds and goes to a reviewer. The failed match and the source document behind it are surfaced together.
No. ActionAI reads from your GL, subledger, and close tools via API or data export; the books stay in your ERP.
A 1-2 hour scoping call identifies the highest-ROI process, then a free pilot delivers results in days to weeks. The enterprise AI average is 13 months; ActionAI runs at a different cadence.
SOC2 compliant with SSO and encryption, deployed in cloud or on-premises. Every decision is logged with full audit traceability from day one.