Our labelers have extensive experience working with financial data across various asset classes, market segments, and financial instruments. They understand the nuances and complexities in finance training data, including market-specific terminologies, regulatory requirements, and data privacy considerations.
At Sapien, we tailor our annotation processes to the specific needs of the finance industry, which includes tasks like classifying and extracting information from financial statements, labeling time-series data for predictive modeling, annotating news sentiment for algorithmic trading, and analyzing customer interactions for compliance monitoring.
The Sapien platform enables on-demand scaling of annotation throughput to meet aggressive timelines for financial model development and backtesting. Scale your project up or down with dedicated teams to support both early-stage research initiatives and enterprise-scale deployments across front, middle, and back-office functions.
Our multi-stage QA processes, combining automated consistency checks, cross-validator consensus, and expert reviews, ensure training data of the highest accuracy and integrity. Sapien's QA is designed to meet the stringent standards of regulated financial applications and the low error tolerance of high-stakes trading and investment decisions.
Quantitative Investing
Risk Management
Compliance and Fraud Detection
Customer Insights
Sapien maintains ISO 27001 certified data security controls and adheres to data privacy regulations like GDPR, CCPA, and GLBA. Our annotators are trained in handling material non-public information (MNPI) and operate under strict confidentiality agreements.
Learn how Sapien can build a scalable data pipeline for you. Schedule a consultation to learn more.