FinTech AI
AI models for Insurance and Asset Management—built with governance and production-readiness.
Insurance Models
Pricing & Risk
Loss cost modeling, underwriting signals, and dynamic pricing.
Fraud & Anomalies
Graph + anomaly detection for suspicious activity.
Claims Triage
LLM-assisted intake, routing, and QA guardrails.
Asset Management
Signals & Alpha
Factor/alt-data pipelines and model experimentation.
Risk & Forecasts
Scenario analysis and portfolio risk dashboards.
Research Copilot
RAG + LLMs over research, filings, and notes with governance.
We design with controls for drift, fairness, and auditability from day one. That includes clear data lineage, documented assumptions, monitoring, and simple rollback paths. You ship fast without skipping safety.
Typical stack: Python, SQL, dbt, modern warehouses, and cloud-native orchestration—plus LLMs wrapped behind guardrails using RAG, prompt evaluation, and role-based access controls.
See Trust & ComplianceIs FinTech AI a good fit for you?
- You have data (claims, trades, transactions, research) but it lives in silos or spreadsheets.
- You want a focused use case in production within 90 days, not a multi-year platform project.
- You operate in a regulated environment and need clear controls, approvals, and audit trails.
- Your team is lean and prefers a partner who can both design and build.
We typically start with a short discovery and architecture sprint, then move into a fixed-scope build with clear success metrics (e.g., hours saved, loss ratio impact, research coverage, or time-to-insight).
To understand how we think about safety and compliance, see our Trust & Security guidelines.