Alert-volume reduction in fraud and AML with ML scoring before human review.
Measured AI benefit JPMorgan Chase reported in February 2026, offsetting an equal $2B of AI cost inside its technology budget.
Less time preparing documentation for regulator exams with automated MRM workflows.
Achieve immediate, organization-wide results
Six measurable outcomes across fraud, credit, markets, and compliance functions, deployed in months rather than years.
Real-Time Fraud Scoring
Per-transaction ML scoring under 200ms. Cuts false positives 40–60% so analysts work the alerts that matter.
AML & KYC Automation
Entity resolution, sanctions screening, and SAR/STR narrative-drafting LLMs. Regulator-exam-ready documentation by default.
Credit Decisioning
Alternative-data credit models with explainable scorecards and adverse-action reasoning built to Regulation B as amended by the CFPB final rule effective July 21, 2026.
Markets & Asset Allocation
Signal generation, regime detection, and portfolio optimization, built per strategy and deployed in your own environment.
Investment Research & M&A Diligence AI
RAG-grounded research-AI over your private analyst notes + filings + earnings calls + regulatory rulebooks. Custom for sell-side, buy-side, and M&A advisory teams that can't ship data to vendor SaaS.
Model Risk Management
Documentation, backtesting, sensitivity testing, and validation packs built to SR 26-2, the interagency model risk guidance that replaced SR 11-7 in April 2026.
Capabilities across the financial services value chain
Lending & Credit Risk
- Alternative-data credit models with explainable scorecards
- Default-probability (PD) and LGD models per segment
- Application-fraud detection at origination
- Early-warning indicators and watchlist scoring
Fraud, AML & Compliance
- Real-time transaction-fraud scoring at sub-200ms latency
- Entity resolution and beneficial-ownership graphs
- AML narrative drafting and SAR/STR support LLMs
- Sanctions screening with reduced false-positive rates
Markets, Trading & Asset Management
- Alpha-signal generation across alternative datasets
- Regime detection and volatility forecasting
- Portfolio optimization under regulatory constraints
- Investment-research and M&A-diligence LLMs over private + public corpora
Customer Experience & Operations
- Voice and chat LLMs for contact-center automation
- Personalized offer and pricing engines
- Complaint-classification and CFPB-pattern detection
- Document-extraction and lending-ops automation
How a mid-size bank cut fraud false positives 55% and saved $12M in analyst hours
A $25B-asset regional bank was drowning in 40,000 daily fraud alerts, with analysts dispositioning each one in 4–6 minutes. We built a gradient-boosted fraud scoring pipeline trained on 18 months of dispositioned alerts, enriched with device, geolocation, and behavioral-biometric features. Daily alert volume dropped from 40,000 to 18,000 with 55% fewer false positives at the same true-positive rate. Annual analyst hours recovered: $12M. The same scoring engine now feeds real-time decline decisions on card-not-present transactions, with a documented MRM package that passed the bank’s annual OCC exam.
Speak with a financial services AI expert
A 45-minute scoping call. We come prepared with your portfolio mix, your transaction volumes, and a directional read on which workflows are worth automating first.
Ask us about
- Real-time fraud detection with sub-200ms latency
- AML entity resolution and SAR/STR narrative LLMs
- Alternative-data credit and adverse-action modeling
- Alpha-signal generation and regime detection
- Investment research and M&A diligence LLMs over private corpora
- MRM-ready models for OCC/Fed/CFPB review
Frequently asked questions
Explore AI/ML solutions for financial services
Ready to talk financial services AI?
Start with a 45-minute strategy session. We come prepared with a directional read on your operation and a scoped proposal.