AI-powered case investigation
AI-powered case investigation evaluates alerts before they reach the compliance analyst, converting them into reasoned pre-analyses. Instead of starting from scratch with a blank screen, analysts begin their work with a pre-reviewed and interpreted case.
The problem: investigation time
When a case hits the screen, analysts usually perform the same repetitive tasks: comparing IPs, scanning logs, checking customer history, and trying to recall similar cases. This preparation takes longer than the actual investigation, and the vast majority of cases ultimately turn out to be false positives.
Under tight investigation deadlines, this creates a direct capacity bottleneck.
What does pre-analysis include?
TruvaLI reviews every alert before the analyst does, evaluating the following:
- Which rule was triggered and which data generated this result.
- Whether the customer's historical behavior is consistent with this transaction.
- Whether the IP, device, and location patterns align with their usual activity.
- How similar cases were resolved in the past.
- The account status, risk score, and any screening matches.
The result is a readable assessment rather than a pile of logs: "This transaction triggered the 5,000 TL limit rule. However, considering the user's previous IP patterns, industry behavior, and device history, it is highly likely to be a false positive."
Humans remain in control
Pre-analysis is a recommendation, not a final decision. The compliance officer reads the assessment, adds their own mandatory regulatory comments, and closes the case. An investigation that used to take hours is safely reduced to minutes.
For low-risk cases or those previously resolved for the same reason, one-click closure can be suggested, but this remains subject to the Maker-Checker workflow.
Alert summaries and natural language queries
Instead of technical log dumps, a written summary is generated for each alert. You can also query the system using natural language: questions like "which three rules generated the most alerts today?" are answered instantly without needing to request a custom report.
On-premise model execution
This analysis capability operates without sending customer data to external cloud services. Case content, customer history, and transaction details never leave the institution's own infrastructure.
Benefits to the institution
- Reduced time spent per investigation.
- Faster filtering of false positives, leaving more time for real risks.
- Consistent evaluations across analysts.
- Written, auditable documentation of the decision reasoning.
Common questions
- Does the AI close cases on its own?
- No. Pre-analysis is a recommendation. The compliance officer makes the decision and adds their own comments. For low-risk cases, one-click closure may be suggested, but this is still subject to the approval workflow.
- Can we see the reasoning behind the pre-analysis?
- Yes. The signals on which the assessment is based are clearly documented: the triggered rule, customer history, and IP and device patterns. This makes it possible to demonstrate how the decision was reached during audits.
- Is case data sent to an external AI service?
- No. The analysis runs on the institution's own infrastructure. Customer data, transaction details, and case content are never sent to external cloud environments.