Financial services firms managing RMBS portfolios process large volumes of loan-level performance data to calculate portfolio performance and feed rating models. Traditional manual processes copying data into Excel templates, applying validation rules, and tracking changes are slow, error-prone, and difficult to audit. To address these challenges, a leading firm implemented Decisions low-code platform to centralize and automate data validation, improve compliance, and reduce operational inefficiencies.
Challenge
Before adopting Decisions, the company faced several barriers:
- Transaction data from multiple regions (UK, EMEA, APAC) required manual scrubbing and validation.
- Analysts spent extensive time copying raw data into templates and applying validation rules.
- Technical resources were burdened with repetitive, low-value tasks.
- Tracking rule execution and maintaining an audit trail was complex and compliance-risky.
These inefficiencies created delays, increased costs, and reduced agility in reporting and analytics.
Solution
The company deployed Decisions to automate RMBS data validation and centralize rules management. Key solution features included:
- Automated Validation: Rules-driven scrubbing, validation, and transformation of incoming transaction data.
- Centralized Repository: Raw and transformed datasets stored in a database for consistency and auditability.
- APIs for Integration: Transformed data fed into rating models, with outputs also recorded.