Financial Data Orchestration
Financial services has the most to gain from AI and the most to lose from getting governance wrong. With FCA scrutiny, the EU AI Act, and increasing regulatory pressure, you need a data orchestration platform that delivers intelligence and maintains compliance. This accelerator builds both — together — in 10 weeks.
The Problem
Financial services has the highest concentration of AI-leading organisations of any sector — and the widest gap between leaders and laggards. 77% of banking executives believe AI will be the primary differentiator between winning and losing firms.
Yet most institutions are stuck. Critical data is siloed across legacy systems — core banking, risk engines, CRMs, trading systems, compliance databases, and document stores that were never designed to talk to each other. Getting a unified view of a client, a portfolio, or a risk exposure still requires manual effort across multiple systems.
Regulatory compliance is consuming disproportionate resources. Manual processes dominate back-office operations — reconciliation, KYC onboarding, client reporting, and regulatory submissions still involve significant human intervention and spreadsheet-based workflows. These are exactly the processes where errors create regulatory exposure.
The institutions winning in 2026 are those that have moved beyond AI experimentation to operational AI at scale — built on orchestrated data, governed workflows, and auditable decision-making.
Legacy vs. Orchestrated Financial Data
| Capability | Legacy Approach | Orchestrated Platform |
|---|---|---|
| Client view | Fragmented, manually assembled | Unified, real-time, accessible from any workflow |
| Regulatory reporting | Manual extraction, spreadsheet reconciliation | Automated, auditable, traceable to source |
| KYC / onboarding | Paper-heavy, weeks to complete | Digitised, orchestrated, days not weeks |
| Fraud detection | Rules-based, high false positive rates | AI-augmented, adaptive, context-aware |
| Client reporting | Templated, quarterly, delayed | Personalised, near-real-time, proactive |
| Compliance evidence | Scattered across teams and folders | Centralised, always audit-ready |
| AI governance | Shadow AI, no controls | Governed platform, explainable, auditable |
| Data lineage | Unknown or undocumented | Full traceability from source to output |
What We Build
Data Orchestration & Unified Intelligence Layer
- Map and connect core systems — banking platforms, risk engines, CRMs, trading systems, document stores — through a secure orchestration layer
- Build a unified data model giving every team a consistent, governed view of clients, products, and risk exposures
- Implement data lineage and provenance tracking so every number can be traced to its source system and timestamp
- Design for regulatory data standards and reporting requirements from day one
AI-Powered Automation & Decision Support
- Deploy intelligent document processing — automated extraction from contracts, regulatory filings, KYC documentation
- Automate reconciliation workflows — cross-system matching, exception identification, and resolution routing
- Implement AI-augmented fraud detection that learns from your transaction patterns while maintaining full explainability
- Build client intelligence that surfaces personalised insights, proactive alerts, and tailored reporting
Governance, Explainability & Regulatory Readiness
- Design an AI governance framework aligned with FCA expectations and EU AI Act risk-based classification
- Implement model risk management — version control, performance monitoring, bias detection, and drift alerting
- Build explainability into every AI-assisted decision so compliance teams can demonstrate how conclusions were reached
- Replace shadow AI with a secure, governed platform — productivity benefits without regulatory risk
- Create audit trails satisfying both internal risk functions and external regulatory examination
Before & After
| Metric | Before | After | Improvement |
|---|---|---|---|
| Client onboarding (KYC) | Weeks | Days | 70%+ faster |
| Reconciliation effort | Hours of manual work daily | Automated with exception handling | 80%+ reduction |
| Regulatory report prep | Days to weeks | Hours, automated and auditable | 75%+ faster |
| Fraud false positives | High, overwhelming compliance | Significantly reduced with AI triage | Analyst time recovered |
| Unified client view | Minutes across multiple systems | Seconds, single interface | 90%+ reduction |
| Shadow AI exposure | Uncontrolled, ungoverned | Replaced with secure platform | Risk eliminated |
| Audit readiness | Scramble to assemble evidence | Always audit-ready, full lineage | Continuous compliance |
10-Week Implementation
Three phases. Ten weeks. One working platform.
Discovery & Architecture
- Week 1: Data landscape audit — catalogue every system, data flow, integration point, and manual process across the priority business area
- Week 2: Regulatory and governance assessment — map compliance obligations (FCA, EU AI Act, GDPR), identify AI governance gaps
- Week 3: Architecture design — orchestration layer blueprint, data model, AI model selection, security framework
MVP Build
- Week 4: Data orchestration engine — integrations to priority source systems, unified data model, lineage tracking
- Week 5: Intelligent document processing — AI extraction and classification for highest-volume document workflows
- Week 6: Automation workflows — reconciliation automation, exception routing, or compliance monitoring
- Week 7: AI decision support — fraud detection enhancement, client insight generation, or risk analytics
- Week 8: Governance and explainability — model risk management, audit trails, explainability layer, shadow AI replacement
Launch & Transfer
- Week 9: Pilot deployment with priority team — live data, real workflows, performance measurement against baseline
- Week 10: Evaluation, scaling roadmap, regulatory review preparation, and team upskilling
Governance: The Non-Negotiable Foundation
In most industries, AI governance is important. In financial services, it’s existential. Institutions that bolt governance onto AI after deployment are already behind. We build it into the architecture from day one.
- FCA expectations — operational resilience, Consumer Duty obligations, and increasing scrutiny of AI-assisted decision-making
- EU AI Act — risk-based classification placing credit scoring and fraud detection in the “high-risk” category, requiring conformity assessments and human oversight
- Model Risk Management — regulators extending traditional MRM expectations to AI and machine learning models
- Data protection — UK GDPR and the Data Protection Act 2018 impose strict requirements on automated decision-making and profiling
- Governance isn’t a constraint on innovation — it’s the foundation that makes responsible innovation possible at scale
Who This Is For
- Banks, building societies, and payment providers where legacy systems and manual processes are increasing operational risk
- Wealth managers and advisory firms where client expectations for personalised, real-time insight are outpacing capability
- Insurance companies where claims processing, underwriting, and regulatory reporting are ripe for AI automation
- Asset managers and fund administrators where reconciliation and client reporting consume disproportionate effort
- Any financial institution with 200+ staff seeing shadow AI usage and needing a governed alternative
- Firms preparing for EU AI Act compliance needing governance, explainability, and risk management for AI-assisted decisions
What Makes Our Approach Different
- We start with your data and your regulatory reality, not a technology demo
- We prove value in 10 weeks with a working platform on a real business process, not a sandbox prototype
- We build governance in from day one — explainability, auditability, and regulatory alignment are architectural decisions
- We design for adoption — every automation must make life easier for the people doing the work today
- We keep experiments cheap — validate the approach on one process before enterprise-wide transformation
- We transfer knowledge — your team owns the platform and the governance model
Ready to Get Started?
A 30-minute discovery call is all it takes to work out whether this accelerator is the right fit for your organisation.