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Financial Data Management Services for Banking & Fintech

Financial data management is the process of integrating, governing, and quality-assuring data so it is accurate, auditable, and AI-ready. Accedia has delivered this for regulated banks and fintechs for 13+ years, covering governed pipelines, reconciliation controls, and full audit traceability.

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Built for Banking & Fintech Data Decision-Makers

Accedia’s financial data management services are built for technology and data leaders in complex financial environments. Typical stakeholders and use cases include:

  • CIOs and CDOs needing a partner for banking data quality management

  • Heads of Data seeking data governance and regulatory compliance solutions  

  • CTOs building an AI-ready data foundation for financial projects

  • VPs of Engineering whose data pipelines are subject to regulatory review 

Accedia's Financial Data Management Services

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    Data Readiness Assessment

    Accedia maps your data architecture against reporting, compliance, and AI requirements, identifying gaps and defining a clear path forward.

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    AI-Ready Analytics & Insights

    Reconciled datasets and governed pipelines for AI-driven forecasting, risk analysis, and credit decisioning.

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    Data Integration & Unification

    Core banking, payments, CRM, ERP, and risk systems unified into a single, governed financial data platform where data is consistent and ready to use.

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    Data Security & Compliance

    Encrypt sensitive financial data, enforce role-based access, and align with GDPR, DORA, PSD2/PSD3, and ISO 27001 to support reliable AI-powered fraud detection.

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    Financial Data Governance

    Ownership defined, every data point traceable from source to report. Built to satisfy internal audit, regulatory review, and AI production requirements.

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    Data Quality & Reconciliation

    Automated validation embedded directly into banking data flows, catching reconciliation breaks before they reach reporting or AI systems.

Among Our Partnerships & Awards

    • Microsoft Solutions Partner Badge
    • AWS Partner Badge
    • Databricks Consulting Partner Badge
    • ISO 27001 Badge
    • Google Cloud Partner Badge
    • IOAP Global 100 Badge
    • Banking Tech Awards Finalist Badge
    • Business Brilliance Awards
    • FinTech Awards Bagde
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More AIRecognitions

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Unified Data Platform Giving Andaria a Single Source of Truth

Andaria was running its entire finance operation on ERP exports and Excel files - manual, fragmented, and harder to scale. Accedia built a unified Azure-based data platform that gave finance and operations a single source of truth. Month-end reporting is now automated, and partner billing scales to higher volumes without adding headcount. As a result, teams spend less time reconciling and more time on decisions.

Read Andaria’s Full Case Study
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Data Engineering for AI Readiness

AI initiatives in banking fail when data is inconsistent, incomplete, or unauditable. Here's how our data engineers prepare financial data for AI production by structuring, reconciling, and governing it before models go live.

01

Scope AI use cases and data requirements

02

Build governed data pipelines

03

Implement automated quality and reconciliation controls

04

Establish governance and traceability

05

Monitor and scale continuously as AI use cases expand

How Governed Financial Data Accelerates AI

30%

Faster AI Model Deployment

Eliminating data prep debt to accelerate AI model deployment.

25%

Forecasting Accuracy Improved

Automating reconciliation and standardizing data to improve forecasting accuracy.

20%

Credit Risk Exposure Reduced

Using ML credit scoring and real-time data to reduce credit risk exposure.

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Engineering Manager

Bozhidar Goranchev

Bozhidar Goranchev is an Engineering Manager at Accedia, leading delivery for banking and fintech software engagements. He oversees cross-functional teams building data platforms, automated reconciliation pipelines, and audit-ready data infrastructure for banks and fintechs across the UK and US.

Our Technology Capabilities

  • Cloud Providers

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    • Google Cloud Platform logo
  • Data Platforms

    • Databricks logo
    • Amazon Redshift logo
    • Azure Synapse Analytics logo
    • IBM Data Storage logo
    • Microsoft Fabric logo
  • Data Integration

    • Azure Data Factory logo
    • Meltano logo
    • Apache Airflow logo
    • Azure Functions logo
    • AWS Lambda logo
  • Storage & Databases

    • Azure Data Lake storage logo
    • Amazon S3 logo
    • PostgreSQL logo
    • MySQL logo
    • MongoDB logo
    • Microsoft SQL Server logo
  • Analytics & AI

    • Azure AI Data Foundry logo
    • Amazon Bedrock logo
    • Vertex AI logo
    • Microsoft Power BI logo
    • Tableau logo
    • Qlik logo
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Why Choose Accedia For Your Financial Data Management Project

  • 1

    Compliance Built Into the Design

    Data platforms designed to meet GDPR, PSD2/PSD3, DORA, AML, and audit standards.

  • 2

    AI Data Readiness

    50+ AI projects delivered, with data foundations proven to improve fraud detection, credit risk, and forecasting accuracy.

  • 3

    Certified Across Leading Cloud and Data Platforms

    Delivery on Microsoft Azure, AWS, Google Cloud, and Azure Databricks for regulated banking environments.

  • 4

    Deep Banking and Fintech Expertise

    13+ years building and governing data platforms for banks and fintechs across the UK and US.

  • 5

    91% Client Retention Rate

    Long-term partnerships with banks and fintechs who return for subsequent engagements

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Discuss Your Financial Data Management Project

Tell us about your challenges and what you want to enable with data. We’ll follow up to schedule a no-obligation consultation and outline the most effective next steps.


During the consultation, you'll get:


  • Meeting with a financial data consultant 
  • Review of your current data architecture and compliance context 
  • Recommended starting point and engagement model

FAQs

  • What is financial data management?

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    Financial data management is the process of integrating, governing, and quality-assuring financial data so it is accurate, consistent, and ready for reporting, analytics, and AI. This includes integrating data from multiple sources, applying reconciliation and quality controls, resulting in standardized metrics and full lineage.

  • How to choose a partner for a banking data quality management project?

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    Look for experience in regulated financial environments, strong governance expertise, and the ability to work with complex banking and payments systems. Evaluate cloud and AI data capabilities, delivery track record, and understanding of GDPR, DORA, and PSD2/PSD3. Accedia, for example, brings 13+ years of experience and 50+ AI initiatives in regulated financial environments.

  • How to keep financial data management compliant with banking regulations?

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    Financial data management stays compliant when governance controls are built into the architecture from the start. This includes clear data ownership, end-to-end lineage, role-based access, and audit logging. These measures help financial institutions align with GDPR, DORA, PSD2/PSD3, and AML requirements. Accedia embeds these controls early into the data architecture to support transparency, traceability, and regulatory readiness.

  • How long does a financial data management engagement typically take?

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    A financial data management engagement typically runs in two phases. Initial work - data quality assessments, governance setup, or regulatory remediation - takes 4–8 weeks. Larger platform builds or system integrations run 6–12 months. Beyond the initial delivery, most banks and fintechs treat data management as an ongoing capability, requiring continuous monitoring, governance updates, and pipeline maintenance as systems and regulations evolve.

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