1. The Financial Reporting Challenge
The sector’s challenges stem from complexity in:
- Data Landscape: Dozens of source systems, inconsistent schemas, legacy databases
- Regulatory Change: Basel III/IV, IFRS 9/17, FATCA, ESG reporting standards
- Operational Metrics: Risk-adjusted returns, capital adequacy, asset performance, liquidity ratios
- Client and Product Views: Aggregation across instruments, accounts, and regions
- Decision Timeliness: Executive dashboards require real-time or near-real-time inputs
Yet most firms rely on:
- Manual extraction and transformation using Excel
- Inconsistent definitions of risk, capital, or profitability
- Repetition of logic across reports with no reuse or lineage
- Outdated or unscalable BI stacks
2. Power BI in the Financial Sector: More Than Visualisation
Power BI is often misunderstood as just a visualisation tool. In practice, it provides a scalable enterprise reporting framework with features essential for financial institutions:
- Advanced data modelling with DAX and Power Query
- Integration with SQL, SAP, Oracle, and cloud systems (Azure, Snowflake, etc.)
- Row-level security and access management
- Scheduled refreshes and self-service capabilities
- Report version control and data lineage for auditability
With the right foundation, Power BI becomes the final delivery layer of a sophisticated data architecture.
3. Building the Foundation: Data Modelling and Meta-Modelling
Data Modelling: Turning Raw Data into Logic and Insight
Financial services demand semantic models that translate raw tables into finance- and risk-intelligent outputs:
- Star and snowflake schemas to separate facts (e.g. transactions, risk exposures) from dimensions (e.g. clients, time, products)
- Calculation of derived measures (e.g. cost of risk, duration-weighted exposure, regulatory capital) using DAX
- ETL processes using Power Query to clean, transform, and load
Meta-Modelling: Engineering Reuse and Consistency
Meta-modelling is critical to enterprise scale. It involves:
- Defining models of models: shared business terms, KPIs, hierarchies, and calculation logic
- Enabling report reusability and consistency across functions and jurisdictions
- Creating governed reporting frameworks that align regulatory, financial, and operational metrics
- Ensuring data lineage, documentation, and auditability
By abstracting reporting components, firms reduce duplication and enforce a single version of truth.
4. Case Scenario (Fictional but Realistic)
Client: A UK-based diversified financial group operating in retail banking, insurance, and asset management
Problem:
- Dozens of fragmented reports for executives, operations, and regulators
- Weekly risk reporting involved manual Excel extractions from 11 systems
- No consistent definitions of capital adequacy or cost of risk
Solution:
- Introduced a meta-model covering definitions of key metrics (risk, capital, returns, client profitability)
- Created unified semantic models for asset classes, exposure types, business lines
- Built Power BI reporting packs for executive dashboards, regulatory KPIs, and investment committee metrics
- Integrated reports with Azure Synapse and a data lakehouse
Results:
- Report production time reduced by 72%
- Single source of truth across risk and finance
- New self-service analytics enabled for investment teams and compliance
5. Strategic Reporting Framework: Tidus’s Suggested Architecture
|
Layer |
Description |
|
Data Sources |
Core banking, Murex, SAP, CRM, HR, regulatory feeds |
|
Data Engineering |
ETL pipelines, staging in Synapse/Snowflake, Power Query |
|
Semantic Layer |
Business definitions, DAX measures, table relationships |
|
Meta-Modelling Layer |
Logical entities (Client, Account, Exposure, Risk Event), reusable metrics, lineage |
|
Presentation Layer |
Power BI dashboards, paginated reports, mobile apps |
|
Governance |
Access roles, version control, audit trail, KPI ownership |
This architecture enables scalability, auditability, and cross-functional visibility — vital for banking, asset management, and capital markets.
6. Key Use Cases Across the Sector
|
Use Case |
Stakeholders |
|
Board-level financial risk dashboards |
C-suite, Risk Committee |
|
Real-time credit exposure monitoring |
Credit Risk, Treasury |
|
Capital allocation and performance |
Finance, Strategy |
|
ESG and sustainability reporting |
Sustainability Office |
|
Regulatory reporting packs (Basel, Solvency II) |
Compliance, Legal |
7. Final Thoughts: Reporting is a Capability, Not Just a Tool
Success in financial reporting does not come from deploying software alone. It comes from:
- Engineering the data models and meta-models behind the reports
- Creating an environment for governance and reuse
- Choosing the right delivery tools like Power BI that support iteration, scale, and security
- Building the capability internally to maintain and extend the system
Firms that invest in this structure are not just improving reporting — they are improving how the business sees itself, understands risk, allocates capital, and makes decisions.
