Client Overview
A leading US-based financial data provider offering deep market intelligence sought to strengthen the accuracy of its industry classification engine—critical for clients in investment management and financial analytics.
Problem Statement
The existing classification system lacked precision, often misplacing companies in incorrect industry sectors. This undermined client confidence, reduced downstream analytics value, and affected strategic decisions relying on accurate industry mapping.
Solution Provided
Decimal Point Analytics deployed a hybrid AI-powered solution that combined:
- Supervised Machine Learning Models to identify deep patterns in financial datasets.
- Domain-driven Rules layered to align with market conventions and regulatory definitions.
- Ongoing Model Training using real-time classification feedback to continuously improve outputs.
- Data Cleansing Pipelines to ensure the foundational input data was clean and contextually aligned.
Outcome
The solution resulted in a 90% classification accuracy rate-significantly improving data reliability and end-client trust. The provider also accelerated on-boarding for new datasets and reduced manual effort for audit and compliance checks.
Key Takeaway
Precision in classification is not just a data quality metric—it directly impacts the value of financial insights delivered to clients. AI-led, rules-augmented automation is the way forward for scalable, consistent accuracy.
Looking to elevate your data intelligence framework with precision and scale?
Talk to Us to explore how our classification and AI capabilities can help you lead with confidence.
