AI-Powered Entity Resolution: 40% Higher Accuracy, 50% Less Manual Effort

A Case Study in Financial Data Integrity & Regulatory Compliance

EYQA-Vetted Transformations
Community of Practice: Data & AI Excellence
Topic: Regulatory Data Harmonization
Type: Operational Efficiency & Risk Mitigation

How SG Analytics Helped a Leading Custodian Bank Transform Operational Accuracy and Efficiency Using Cloud-Based AI Models

Financial data image 1
Financial data image 2
Financial data image 3
Financial data image 4
Financial data image 5
Financial data image 6
  • 📥 Download SG Analytics Case Slide Carousel

    • Overview

    A global custodian bank struggled with resolving client entity records across multiple disconnected systems. Manual processes resulted in duplicated profiles, errors, and compliance risks. SG Analytics implemented a cloud-native, AI-powered entity resolution platform, delivering:

    • 40% higher accuracy in entity resolution
    • 50% reduction in manual effort
    • Improved operational agility and scalability

    The Challenge

    The bank faced critical pain points:

    • 8,000+ daily transactions across 12+ siloed systems, leading to inefficiencies
    • High manual effort for de-duplication and match resolution
    • Regulatory pressure to improve accuracy and reduce reporting latency
    • Inability to scale operations without escalating costs

    The Solution

    Platform & Architecture

    • Cloud-based infrastructure for scalability and real-time performance
    • Seamless integration with internal and third-party data sources
    • Secure, continuous processing of high-volume client records

    AI & ML Strategy

    • Hybrid ensemble of decision trees and neural networks for optimal results
    • Advanced features like transaction patterns and account linkages to boost precision
    • Rigorous validation using separate datasets to ensure robustness

    Operations Enablement

    • Automated a significant portion of entity resolution
    • Reduced reliance on manual workflows and reviews
    • Integrated with downstream systems like KYC and compliance

    The Impact

    Resolution Accuracy
    ↑ 40% improvement over baseline
    Manual Effort
    ↓ 50% reduction in manual intervention
    Scalability
    Enabled real-time, high-volume data processing
    Data Quality
    Improved consistency and completeness of client records
    Regulatory Readiness
    Strengthened confidence in compliance reporting

    Why It Worked

    • Tailored ML algorithms to address banking-specific data challenges
    • Focused on operational bottlenecks for direct efficiency gains
    • Delivered a unified client view to support regulatory and service improvements

    Key Takeaway

    SG Analytics' AI platform empowered the bank to resolve entities faster, more accurately, and at lower cost—transforming a compliance burden into a competitive advantage.



    EYQA Case Study Vetting Methodology

    This SG Analytics case study adheres to the SHARE framework—evaluating Scalability, Human Value, Actionability, Replicability, and Evidence—with multi-dimensional review for:

    • Strategic Viability (ROI, market readiness)
    • Stakeholder Impact (boardrooms to operations teams)
    • Innovation Rigor (process redesign to AI/ML optimization)

    Empowering executives, investors, and changemakers to turn insights into execution.


    Transformation Amplification Pathways

     Case Study Review Outcomes & Strategic Potential
    Pathway Scalability Evidence Growth Axis
    Experience
    • 12+ system integrations
    • API-first design
    		 Extend to:
    • Asset management data harmonization
    • Broker-custodian account validation
    Yield
    • 50%↓ manual effort
    • Real-time matching
    		 Scale to:
    • Client data remediation pipelines
    • Automated regulatory filings
    Quality
    • 40%↑ accuracy (10%→6% errors)
    • Golden record creation
    		 Apply to:
    • Periodic KYC refresh cycles
    • Subsidiary ownership mapping
    Agility
    • Cloud-native (multi-region support)
    • 8K+ tx/day capacity
    		 Accelerate:
    • Cross-border entity onboarding
    • New product deployment timelines

    Contributor Acknowledgments

    This transformation was delivered by SG Analytics' Data & AI practice. For inquiries:

    Key Contacts:

    Kulwinder Singh

    Chief Marketing Officer

    Kulwinder.singh@sganalytics.com

    Strategic AI/ML partnerships

    Supriya Dixit

    SVP, Marketing

    Supriya.dixit@sganalytics.com

    Client success programs

    About SG Analytics:

    SG Analytics (SGA) is a leading global data solutions firm providing data-centric research and contextual analytics services to its clients, including Fortune 500 companies, across the Financial Services, Technology, Media & Entertainment, and Healthcare sectors. Established in 2007 and a Great Place to Work certified company, SGA has over 1600 employees and has a presence across the US, the UK, Switzerland, Poland, and India. Besides being recognized by analyst firms such as Gartner, Everest Group, and ISG, SGA has been part of the elite Deloitte Technology Fast 50 India 2024 and APAC (Asia Pacific) 2025 High Growth Companies by the Financial Times & Statista.



    By Your Community of Practice (EYQA)
    Last updated on May 02, 2025