Woodgrove Bank — Financial Services

TL;DR

Woodgrove Bank: 340 VMs, 45 SQL databases, 28 .NET apps. Core banking and regulatory systems follow Stabilize (months 1–5); digital banking and fraud detection follow Transform (months 3–9). Fabric supports governed reporting and near-real-time transaction monitoring when controls are configured.

Woodgrove Bank is a regional bank with 200+ branches and a growing digital banking platform. Decades of acquisitions have left them with a fragmented IT estate — multiple core banking systems, overlapping databases, and a compliance team that is perpetually behind on audits.

The Challenge

Woodgrove faces a convergence of pressures:

• Regulatory pressure — New regulations require faster reporting, better data lineage, and demonstrated data sovereignty. The current manual audit process takes weeks and is error-prone.
• Fraud detection gaps — The existing fraud system is rule-based and batch-processed. Sophisticated fraud patterns are detected hours or days after the transaction — far too late.
• Customer experience — The digital banking app is built on .NET Framework and cannot handle traffic spikes during promotions or end-of-month salary processing.
• Data silos — Each acquired system has its own database. There is no unified view of customer relationships across products.

Why now?

The regulator has issued new guidance requiring near-real-time transaction monitoring by Q3 next year. Woodgrove’s current batch-processing architecture cannot meet this requirement. Compliance failure carries significant financial and reputational risk.

The Assessment

Azure Migrate reveals the estate:

Category	Count	Finding
Windows Server VMs	340	240 migration-ready, 60 need remediation, 40 can retire
.NET applications	28	20 are .NET Framework, 5 are .NET 6+, 3 are legacy VB.NET
SQL Server databases	45	38 compatible with SQL MI, 7 need feature review

The Path Decision

Workload	Path	Rationale
Core banking systems	Stabilize	Stability is paramount, minimal-downtime cutover needed
Regulatory reporting databases	Stabilize	Data sovereignty requirements met by SQL MI in-region
Digital banking app	Transform	Customer-facing, needs elastic scale and rapid iteration
Fraud detection engine	Transform	Needs real-time processing, ML integration

Execution

Stabilize (Months 1-5):

• Migrate core banking VMs in controlled waves with extended parallel-run validation (regulatory requirement)
• Migrate reporting databases to SQL Managed Instance
• Enable SQL MI Mirroring to Fabric for regulatory reporting

Transform (Months 3-9):

• Modernize digital banking: containerize, deploy to Container Apps with autoscaling for traffic spikes
• Rebuild fraud detection as a real-time service backed by Azure SQL Database and Fabric Real-Time Intelligence
• Full CI/CD with automated security scanning in pipeline

The Payoff

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  classDef onelake fill:#742774,stroke:#5a1e5a,color:#fff
  classDef bi      fill:#fde8f9,stroke:#742774,color:#3a003a
  subgraph h1["Stabilize"]
    CORE[("Core Banking → SQL MI")]:::azure
    REG[("Regulatory DB → SQL MI")]:::azure
  end
  subgraph h2["Transform"]
    DIGI[("Digital Banking → Azure SQL DB")]:::azure
    FRAUD[("Fraud Engine → Azure SQL DB")]:::azure
  end
  FAB(["Fabric OneLake"]):::onelake
  PBI["Power BI<br/>Regulatory Dashboards"]:::bi
  ML["Data Science<br/>Fraud Detection Models"]:::bi
  RTI["Real-Time Intelligence<br/>Transaction Monitoring"]:::bi
  CORE -->|"Mirror"| FAB
  REG -->|"Mirror"| FAB
  DIGI -->|"Mirror"| FAB
  FRAUD -->|"Mirror"| FAB
  FAB --> PBI
  FAB --> ML
  FAB --> RTI
  style h1 fill:#e6f3ff,stroke:#0078d4
  style h2 fill:#e6f3ff,stroke:#0078d4

Business outcomes:

• Regulatory reporting reduced from weeks to hours — automated dashboards in Power BI with lineage, ownership, and controls configured in Fabric and Microsoft Purview
• Near-real-time fraud detection using ML models trained on unified transaction data in Fabric, complementing the legacy batch-processing system during phased transition
• Digital banking app is designed and tested for traffic spikes with Azure Container Apps autoscaling and production performance validation
• Unified customer view across all acquired banking systems — for the first time, Woodgrove can analyze customer relationships across products