Regulatory Data Quality & Template Automation Digital Worker
Deploys an 8-agent agentic system that ingests fund data files, executes 487+ validation rules, cross-references data across multiple sources, detects statistical anomalies using Isolation Forest algorithms, generates regulatory-compliant templates, performs quality assurance, and distributes outputs to multiple platforms via API and SFTP..
Problem Statement
The challenge addressed
Solution Architecture
AI orchestration approach
AI Agents
Specialized autonomous agents working in coordination
Orchestrator Agent
Managing complex multi-phase workflows with dependencies between agents, generating executive compliance reports, and coordinating mission-wide decisions requires centralized intelligence.
Core Logic
Coordinates all 8 agents through 9 workflow phases, manages agent dependencies and execution order, generates AI recommendations with confidence scores for detected issues, creates executive compliance reports with audit trails, and tracks overall mission metrics including quality scores, processing times, and cost estimates.
Data Ingestion Agent (Nexus)
Fund data arrives in various file formats (CSV, XML, Excel) with inconsistent structures, requiring parsing, normalization, and initial validation before processing.
Core Logic
Processes uploaded data files including NAV data, fund holdings, ESG scores, cost information, and performance metrics. Detects file structure (rows, columns), validates data types, normalizes formats, and prepares structured data for downstream validation. Reports file status and data completeness metrics.
Validation Agent (Sentinel)
Fund data must comply with regulatory schemas and business rules, requiring execution of hundreds of validation rules to identify errors and warnings before submission.
Core Logic
Executes 487+ validation rules across multiple rule sets including data completeness, format validation, range checks, cross-field consistency, and regulatory schema compliance. Reports validation issues by severity (info, warning, critical), identifies affected funds and fields, and generates quality scores for each fund and overall dataset.
Cross-Reference Agent
Data discrepancies between internal systems and external sources (market data providers, regulatory filings) can cause compliance failures and require manual reconciliation.
Core Logic
Cross-references fund data across 5+ external data sources to identify discrepancies. Compares NAV values, holdings weightings, and key metrics against authoritative sources. Calculates variance percentages, flags values outside thresholds, and provides source reliability scores to support data reconciliation decisions.
Anomaly Detection Agent (Cipher)
Statistical outliers and unusual patterns in fund data may indicate data errors or significant changes requiring investigation, but manual detection across large datasets is impractical.
Core Logic
Applies Isolation Forest machine learning algorithm to detect statistical anomalies in time-series data. Loads 12-month historical baselines, identifies outliers exceeding standard deviation thresholds, cross-references anomalies with portfolio changes to distinguish genuine changes from data errors, and provides confidence-scored explanations.
Template Generator Agent (Forge)
Generating regulatory templates (EMT, EET, EPT, TPT, DCPT) requires mapping hundreds of data points to specific schema fields with correct formatting and validation.
Core Logic
Loads regulatory template schemas (EMT v4.1, EET v3.2), maps 156+ data points to template fields, generates templates for all funds and share classes, validates outputs against schema requirements, and produces files in required formats (XML, CSV, JSON) with comprehensive metadata including record counts and checksums.
Quality Assurance Agent (Guardian)
Generated regulatory templates must pass quality checks for schema compliance, data completeness, and accuracy before distribution to avoid regulatory rejections.
Core Logic
Validates all generated templates against regulatory schemas, runs completeness checks (95% threshold), verifies data accuracy (99% threshold), and assigns quality scores to each output. Provides go/no-go recommendations for distribution based on quality thresholds.
Distribution Agent (Mercury)
Regulatory templates must be delivered to multiple platforms (Morningstar, Bloomberg, Refinitiv) using different protocols (API, SFTP, email), requiring coordinated distribution management.
Core Logic
Establishes connections to 6+ distribution platforms, uploads templates via appropriate protocols (API for Morningstar Direct, SFTP for Bloomberg Terminal), tracks delivery status, handles retries for failed deliveries, and records confirmation IDs for audit compliance.
Worker Overview
Technical specifications, architecture, and interface preview
System Overview
Technical documentation
Tech Stack
7 technologies
Architecture Diagram
System flow visualization