Case Study
Improving document verification accuracy with a custom ML fraud detection system
Financial Services
Content
99% precision
1.2% false positive rate in production
~50% reduction
Manual escalation workload
10× better
Accuracy vs LLMs and baseline tools
Services
AI Deal Analysis, Workflow Automation, Investment Intelligence Platform
Industry
FinTech / Real Estate Technology
Client
Confidential Large-scale fintech platform
Duration
3 months
The Challenge
The platform processed hundreds of document-based applications daily, with a large percentage flagged for human review. Manual verification consumed significant reviewer time, while existing tools generated high false-positive rates that drove unnecessary escalations.
As volume increased, the team needed to improve fraud detection accuracy without scaling headcount or slowing application processing.
The Solution
Casper Studios designed and deployed a custom ML fraud detection system optimized for document verification accuracy, not generic text reasoning. After evaluating LLM based approaches, we identified traditional machine learning as significantly more reliable for this use case.
Key capabilities included:
Interpretable ML classifier trained on 65+ engineered document metadata features
Pass / Fail / Caution prediction architecture using calibrated one-vs-rest models
AI Assist layer providing plain-English explanations to support reviewer trust
Feedback-driven ETL pipeline capturing human decisions for continuous retraining
The system consistently outperformed both off-the-shelf LLMs and existing vendor tools in precision and false-positive reduction.
The Impact
The new model dramatically reduced unnecessary manual reviews while maintaining strong fraud detection performance. Reviewers were able to focus on genuinely high-risk cases, cutting workload roughly in half and improving overall throughput.
By emphasizing precision and explainability, the platform established a scalable verification foundation capable of supporting continued growth without proportional increases in operational effort.
