MouseCat provides an AI‑driven platform that automates fraud investigation by ingesting data from warehouses like Databricks and Snowflake, summarizing alerts, and generating explainable, production‑ready detection rules with back‑testing and audit trails. The solution supports KYB, account‑take‑over, and payment fraud use cases and can be deployed on‑premises for strict security and compliance needs.
Funding
Funding not disclosed
Founders
Product
Problem
Risk teams spend extensive time manually investigating fraud alerts, engineering features, and testing detection rules, which leads to delayed responses, inconsistent decisions, and high operational costs. Existing AI tools often act as black boxes or require separate implementation steps, limiting auditability and integration with a company’s data stack.
Solution
MouseCat offers an AI‑driven platform that automates the entire fraud investigation workflow. The system ingests data directly from warehouses such as Databricks and Snowflake, analyzes alerts, and surfaces the most relevant risk signals. From each investigation it automatically generates explainable features and high‑precision detection rules, back‑tests them against historical data, and provides full audit trails. The platform supports KYB, account‑take‑over (ATO), and payments fraud use cases, and can be deployed on‑premises to meet strict security and compliance requirements. By turning investigative insights into production‑ready rules, MouseCat enables faster, more consistent fraud mitigation without manual feature engineering.
Target Audience
Primary customers are risk operations and fraud detection teams within financial services, payments processors, and enterprises that manage large volumes of transaction and onboarding data.
Features
- Direct integration with major data warehouses (Databricks, Snowflake) and existing rule engines or feature stores
- AI‑powered alert summarization that surfaces the riskiest signals and recommended actions
- Automatic generation of point‑in‑time features and detection rules with deterministic back‑testing on historical data
- Explainable decision outputs with complete audit logs for regulatory compliance
- On‑premises deployment option for environments with strict security or data residency requirements
- Support for KYB investigations, ATO detection, and payment fraud modeling, including synthetic label creation for chargebacks