Finance Case Study
Fallcrest Financial
An ongoing monitoring framework built for a regulated AI use case.
-45%False Positives
The Challenge
Where things stood before
Fallcrest Financial's biggest obstacle was manual review processes that were both slow and inconsistent — something their team had tried to patch more than once without lasting success.
The problem was quietly getting more expensive to ignore every month it went unaddressed.
The Solution
What we built
Our approach focused on the root cause rather than the most visible symptom.
The result was straightforward: an ongoing monitoring framework built for a regulated AI use case, built specifically around what Fallcrest Financial needed.
- Benchmarked against clear, agreed-upon success metrics from day one
- Designed around Fallcrest Financial's actual data and workflow, not a generic template
- Delivered within a 5-week timeline without cutting scope
- Structured so Fallcrest Financial's own team could monitor and maintain it going forward
Results
The impact, by the numbers
-45%
False Positives
-45%
Review Time
+39%
Detection Accuracy
91.2%
Model Explainability Score
Tech Stack
Built with
NotionConfluencePythonSQL
Cyphergate Software
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