Data Management Platform for Banks & Custodians

SG Analytics’ data management platform helps banks and custodians navigate complex regulatory and operational environments with confidence. It delivers a single, trusted view of all legal entities, including subsidiaries, branches, and counterparties, to strengthen compliance, reduce risk, and enhance data governance. With AI agents and reconciliation intelligence built in, the platform continuously validates and enriches data across sources, keeping it accurate, connected, and audit-ready. This creates a secure, centralized foundation for reporting, oversight, and regulatory assurance.

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Entity Management Platform for Banks & Custodians

The platform resolves key entity management challenges such as fragmented information, inconsistent data, and manual upkeep. It provides a centralized, governed hub for corporate, legal, and operational data across entities, subsidiaries, and branches.

With AI agents and automated reconciliation workflows, the platform continuously tracks ownership changes, filings, and key deadlines to minimize compliance risk and ensure all information remains accurate, connected, and audit-ready. This allows banks and custodians to respond swiftly and confidently to audits, regulatory reviews, and internal oversight.

Data Management Platform is Built For:

Global Banks

Managing complex entity hierarchies and multi-jurisdictional compliance.

Regional & Community Banks

Modernizing core connectivity and data governance.

Custodians

Maintaining client, fund, and account data with full traceability.

Who Do We Work With

Data Teams

Gain access to clean, reconciled, and audit-ready legal-entity data, eliminating duplicates and manual effort through AI-driven reconciliation and quality dashboards.

Compliance Teams

Ensure KYC/AML accuracy and maintain regulatory alignment with GDPR, FR 2052A, AnaCredit, and LEI frameworks through traceable, policy-based data workflows.

Risk Teams

Receive timely updates on entity structures, ownership changes, and corporate actions, enabling accurate cross-asset exposure and counterparty risk tracking.

Operations Teams

Leverage semi-automated, rule-based workflows to accelerate onboarding, client data enrichment, and exception management across systems.

IT Teams

Deploy secure APIs, scalable architecture, and validation layers that integrate seamlessly with core banking, CRM, and regulatory reporting systems.

Data Teams

Gain access to clean, reconciled, and audit-ready legal-entity data, eliminating duplicates and manual effort through AI-driven reconciliation and quality dashboards.

Compliance Teams

Ensure KYC/AML accuracy and maintain regulatory alignment with GDPR, FR 2052A, AnaCredit, and LEI frameworks through traceable, policy-based data workflows.

Risk Teams

Receive timely updates on entity structures, ownership changes, and corporate actions, enabling accurate cross-asset exposure and counterparty risk tracking.

Operations Teams

Leverage semi-automated, rule-based workflows to accelerate onboarding, client data enrichment, and exception management across systems.

IT Teams

Deploy secure APIs, scalable architecture, and validation layers that integrate seamlessly with core banking, CRM, and regulatory reporting systems.

How SGA’s Data Management Platform is Different

Comprehensive Legal Entity Reference Data

API-based extraction of key identifiers such as LEIs, RSSD, and CRD.
Ability to enrich 80+ entity-related information through our proprietary knowledge base and data sources.

Detailed Hierarchy & Corporate Actions Data

Provides entity hierarchy insights, including beneficial ownership details.
Includes up-to-date corporate actions data for accurate and timely decision-making.

Automated Workflow for Data Quality Assurance

Built-in workflow automation for entity enrichment, maker-checker validation, and rework processes.
Ensures consistent data quality and reduces manual intervention.

Sophisticated ML-Powered deduplication and reconciliation

Ability to identify duplicates using an ML algorithm that identifies common threads between similar entities.
Reconciliation of duplicate entities without loss of critical information.

Seamless API Integration with Third-Party Data Providers

Easily integrates with external data sources to enhance data accuracy and completeness.

Built-In Referential Integrity for Regulatory Compliance Related Data

Domain-specific data validation and built-in referential integrity.
Automatic pre-filling of attributes to maintain data consistency.
FR 2052A Reporting and Anacredit-related attributes.

Our Data Management Platform

SGA’s data management platform is a critical tool for banks, creating a single, accurate view of all legal entities to streamline compliance, mitigate risk, and enhance data governance. It ensures crucial information is audit-ready, providing a secure and centralized system for financial reporting and corporate oversight.

Key Features

Access to a broad range of authentic sources from registries to private market data.

Competent domain expertise to identify, research, and fill in intricate gaps in the entity management process.

AI-led accelerators to fasten the process of extracting data, verifying it, and reviewing it.

Complex deduplication and reconciliation capabilities.

FAQs – Data Management Platform

What problems does the Data Management Platform solve for banks?

The platform solves the critical challenge of maintaining accurate and consistent legal entity data across a bank’s vast, and often fragmented, systems. Banks struggle with data silos, manual reconciliation, and the constant need to meet evolving regulatory requirements such as FR 2052A and AnaCredit. Our platform provides a unified, automated approach that ensures data integrity, regulatory compliance, and operational efficiency.

How does the platform help improve data quality?

Our platform ensures data quality through a multi-layered approach:
AI-powered validation: Automatically extracts and validates key information from various data sources, including unstructured documents.
Automated workflows: Enforces strict data quality checks and validation rules, flagging and preventing errors before they propagate.
Referential integrity: Maintains accurate relationships between entities, accounts, and hierarchies, creating a ‘golden record’.
Comprehensive version history: Tracks all changes with a full audit trail, ensuring every data point is transparent and accountable.
Domain expert-led inputs: Highly experienced domain experts help with enriching the data that can’t be automatically enriched, which differentiates our platform from a pure, rules-led platform.

What makes this platform different from traditional entity resolution solutions?

Unlike traditional solutions that primarily focus on matching algorithms, our platform is a comprehensive entity management system that offers:
AI-led intelligence: GenAI capabilities to intelligently extract and enrich entity data from legal and corporate documents and other authentic sources from the web.
Regulatory-specific data models: Pre-built attributes and validations for major banking regulations, accelerating compliance efforts.
Smart dashboards: Real-time visibility into the health of your entity data and compliance status.
Unified ecosystem: A central source of truth for all entity data, breaking down silos and providing a consistent view across departments.

How does the platform help with regulatory compliance?

The platform helps banks meet and exceed regulatory requirements by embedding compliance into the data lifecycle. It includes pre-built attributes and validations for key regulations and maintains comprehensive version histories with supporting documentation, creating an undeniable audit trail. The automated workflows and alerts ensure that all entity data is continuously monitored for compliance and is always audit-ready.

How does the platform leverage AI & ML?

AI and ML are foundational to our platform’s capabilities:
Intelligent data extraction: GenAI-powered document intelligence automates the extraction of entity information from unstructured documents.
Data standardization: ML algorithms standardize and normalize entity data from multiple sources.
Advanced matching: Our matching engine continuously learns and improves its accuracy in identifying and deduplicating entities across the enterprise.
Anomaly detection: AI models monitor for and flag unusual changes or patterns in entity data, preventing potential fraud or errors.

What kind of benefits can banks expect?

Early adopters have reported significant benefits, including:
A reduction in the time and cost associated with manual data entry and reconciliation.
Faster and more accurate regulatory reporting cycles.
A decrease in data quality issues and operational risks.
An improvement in the speed and accuracy of client onboarding and KYC processes.
Enhanced ability to respond to internal and external audits with confidence.