aisol/solutions/antifraud
solution 8 / 8

AI system for anomaly detection and antifraud transaction control

Detects anomalous transactions in real time, automates compliance checks and monitors adherence to financial regulations. No replacement of your IT infrastructure. 100% coverage instead of sample-based control.

For whom: banks, insurers, telecom operators, large retail, financial companies — with transaction volumes from 1,000 per day. We start the pilot with retrospective analysis, with no risk to production. Timeline — 6–8 weeks.

transaction controlreal-time
anomaly · 5-min responsePayment to a supplier outside the registry
"TechnoSnab" · ₸3.2Mfirst payment without verificationrisk 87
Limit exceeded₸8.5M against a ₸5M limitflag
Flag logaudit-ready · 100% coverageexport
problems

What happens without a system

!

Fraudulent or anomalous transactions are discovered after the fact — the loss and reputational damage have already occurred.

!

Compliance checks are sample-based: with thousands of transactions per day, 100% manual control is unrealistic.

!

The auditor sees violations once a quarter — by then the anomaly has become systematic.

!

Data from different systems (ERP, CRM, bank) is not consolidated — an anomaly is invisible when viewed in isolation.

!

An employee makes an atypical transaction — no one notices until an external audit or a complaint.

!

Audit preparation takes 2–4 weeks of manual work: collecting evidence of compliance from different systems.

pilot benchmarks

Target metrics are fixed before the start

We agree on the metrics with you before work begins. If we don't reach them — we keep working until the result, or refund proportionally.

100%transaction coverage instead of sample-based control
real-timeanomaly detection — not once a quarter at the audit
up to 60%reduction in time spent on compliance checks
from 5 minresponse time to a critical alert
system components

How the AI antifraud control system works

ML model on your data

Trained on your transaction history. It understands what is "normal" for your company — and detects deviations.

Cross-system analysis

Analysis of transactions across ERP + CRM + bank. An anomaly is visible only in the combined data.

Real-time alerts

An anomalous transaction triggers a notification to the risk officer within 5 minutes. Configurable thresholds and rules.

Integration with 1C / SAP / ERP

We connect to financial systems via API. No need to replace infrastructure or change processes.

Scoring of every transaction

Each one is assigned a risk score: high — escalation, low — auto-approval, medium — manual review.

Log of all flags

Full history of every alert: what triggered, who reviewed, the decision, the rationale. Ready for the auditor.

Compliance rules

You upload your regulations and statutory requirements — the system checks every transaction for compliance.

Automated audit preparation

A consolidated controls report for the period — in 20 minutes instead of 2–4 weeks of manual work.

example scenario

Questions to the system — answers based on transactions

QuestionOver the last 7 days, were there any payments to suppliers outside the approved registry?
System3 transactions totaling ₸4.7M to suppliers outside the registry. The largest — "TechnoSnab" (₸3.2M), first payment without verification. The transactions are flagged for manual review. Create a verification task?
QuestionAre there any employees who approved transactions above their authority limit in the last month?
System4 cases of exceeding the limit. Manager Alibekov approved 2 payments of ₸8.5M each against a ₸5M limit. No authorization from a senior manager was recorded. A detailed report is ready to export.
frequently asked questions

What you need to know

The ML model is trained on 6–12 months of your historical data. It detects statistical anomalies: an unusual counterparty, an atypical amount, time, or chain of operations. Compliance rules are an additional layer on top of the ML.
We tune the thresholds during the pilot on real data. Usually within 2–3 weeks we find the balance: minimal false alerts with maximum coverage of real anomalies.
Only on-premise or in Kazakhtelecom Cloud with encryption. For banks — on-premise is mandatory per NBK (National Bank of Kazakhstan) requirements. NDA, data isolation, no training of models on your data.
The architecture is designed to meet the requirements of the NBK (National Bank of Kazakhstan) and Law of RK No. 94-V. For banks, we provide technical documentation for review by your internal compliance team.
A pilot in 2–3 weeks on historical data — without connecting to production. You see retrospectively how many anomalies the system would have found in the past.

Ready to move to 100% transaction control?

We'll start with a retrospective analysis on your historical data — without connecting to production. We'll show what the system would have found over 3 months. Pilot — 6–8 weeks.