Funding
Funding not disclosed
Founders
Product
Problem
Financial institutions often face challenges with existing ESG data providers due to score divergence and a lack of transparency in their methodologies. Similarly, quantitative teams struggle with the time-consuming process of transforming raw alternative datasets into actionable market signals and mapping them to financial instruments.
Solution
Gematria provides a no-code engine that empowers financial institutions to construct custom market signals and ESG scores. The platform allows users to define proprietary scoring methodologies through intuitive rule-based systems for data selection, processing, and aggregation. This approach ensures interpretability and granular control over financial data analysis. For quantitative hedge funds and data scientists, Gematria streamlines the curation and aggregation of alternative datasets, reducing time-to-insight. The engine also handles the complex mapping of data to various financial instrument identifiers, simplifying the integration of alternative data into existing workflows.
Target Audience
The primary customers are banks, asset managers, quantitative hedge funds, and data scientists within financial institutions seeking to develop bespoke analytical tools and gain deeper insights from diverse data sources.
Features
- No-code interface for designing custom ESG scores and market signals.
- Rule-based engine for defining data selection, processing, and aggregation logic.
- Visual inspection tools to understand data point contributions to final scores.
- Support for mapping data to financial instruments including ISIN, BloombergID, and OpenFIGI.
- NLP capabilities for entity detection, keyword extraction, and sentiment analysis on text data.
- Customizable and shareable dashboards for visualizing search statistics and sentiment trends.
- API access for programmatic querying of historical and real-time data streams.
- Option for on-premises deployment for enhanced data confidentiality.