Quatr raises $18M to expand financial data services

Quatr, a financial data startup, announced it raised $18 million to broaden its product offerings and scale operations. The funding was disclosed recently as the company seeks to grow dataset coverage and serve more institutional and fintech customers.

The company plans to use the capital to accelerate product development, increase the size of its engineering and data teams, and expand cloud infrastructure to handle larger volumes of market and alternative data. Quatr intends to add regional market data, extend coverage of instrument types and corporate events, and bring in more alternative datasets used by institutional clients.

Quatr provides structured financial datasets and APIs that deliver pricing, reference data, corporate actions and other market information. The platform supplies consistent identifiers and update mechanisms designed to reduce the time firms spend collecting, normalizing and maintaining data feeds.

Customers include asset managers, hedge funds, banks and fintech firms that require low-latency delivery and consistent schemas for trading, risk and research workflows. The company reports growing adoption among teams building quantitative strategies, risk models and regulatory reporting systems where consistent data and timely updates are required.

The funding will also support geographic expansion and partnerships to broaden data sources. Quatr plans to invest in tooling to simplify customer onboarding and data mapping for new clients integrating its services.

The market for financial data includes established market-feed and reference-data vendors alongside newer cloud-native, API-first providers. Buyers of data have sought alternatives that reduce engineering overhead and streamline delivery of programmatic data services.

Quatr competes with incumbent market-data firms and other API-first providers targeting institutional data needs. The company was founded to address the technical burden of aggregating and normalizing diverse market data sources and to deliver ready-to-consume datasets for production use in trading and analytics.