Data Solutions

Data Modelling and Analytics Maturity Transformation Across Multi-Product Domains

Challenge

A leading European multinational bank sought to modernise its data and analytics capability across four major product domains—Capital Markets, Corporate & Retail Banking, Commercial & Wealth, and Digital Platforms.

The bank’s existing modelling ecosystem spanned decades of fragmented infrastructure: bespoke spreadsheets, legacy pricing engines, manual reporting loops, and limited data lineage. Executives recognised that model complexity had outpaced governance and analytics maturity, impeding consistency across pricing, valuation, performance, and risk metrics.

Harmonic Strategy, with 25 years of front-to-back banking product experience, was engaged to perform an AS-IS diagnosis of the modelling environment and deliver a data transformation roadmap to harmonise analytical methods, standardise pricing architectures, and embed a unified governance layer.

Solution

Harmonic applied a structured four-pillar deep-dive combining quantitative model review, data lineage mapping, and maturity benchmarking across business, data, and technology dimensions.

1. Fixed Income, Equity & Derivatives Modelling Framework

• Conducted forensic review of valuation models (FX, Rates, Credit) spanning Black-Scholes, Garman-Kohlhagen, and Black models.

• Reconstructed volatility and yield curve architectures, including treatment of unobservable long-dated points (> 7 years).

• Defined unified PV, sensitivity, and VaR back-testing standards, replacing siloed desk methodologies with consistent risk-based P&L attribution logic.

• Delivered an integrated pricing model inventory and validation framework with ownership, controls, and versioning.

2. Corporate, Retail & Wealth Banking Product Analytics

• Mapped product data lineage across Cash, Trade, and Securities Services to identify breaks between operational, finance, and risk systems.

• Standardised core performance ratios (NIM, ROA, RORWA, ROE, cost/income, LCR, NSFR).

• Implemented unified NFI/NIM repricing models linking product economics to balance-sheet sensitivity.

• Defined data taxonomies and metadata policies for master-data consistency across customer, account, and instrument hierarchies.

3. Commercial Loan Pricing Models

• Built modular frameworks for:
  a. Mortgage Value Model – full driver tree for Net Interest Income, provisioning, and ROE calibration.
  b. Relationship Value Model – discount calibration linked to cross-sell elasticity and total customer value.
  c. Price Elasticity Model – solver-based demand curves (linear + power) using variable cost inputs and third-party consulting calibrations.

• Embedded a data layer enabling dynamic scenario analysis and profitability stress tests by segment, tenor, and collateral class.

4. Retail Platformisation & Digital Transformation

• Quantified potential Cost/Income ratio reduction from ~70 % → 40–50 % via end-to-end digital product orchestration.

• Designed contextual-finance data architecture mapping five customer-journey touchpoints (Search → Evaluate → Acquire → Use → Renew) across three life pillars:

  • Daily Life (payments, cards, travel)

  • Home & Life Events (auto, housing, complex lending)

  • Wealth & Protection (investment, accumulation, insurance).

• Defined API-first integration blueprint enabling product personalisation, embedded pricing, and analytics-driven engagement across digital channels.

Key Deliverables

• Enterprise-wide Data & Model Governance Framework

• AS-IS / TO-BE Analytics Maturity Map and transformation roadmap

• Unified Model Inventory with validation & documentation controls

• Pricing & Profitability Simulation Engine (loan / deposit elasticity models)

• Data Taxonomy & Metadata Standards for product and client hierarchies

• Digital Platformisation Blueprint linking customer-journey data to analytics outcomes

Client Benefits

• Established a single, controlled data and modelling architecture across all major product lines.

• Reduced manual model reconciliation and spreadsheet dependency by > 60 %.

• Enabled consistent pricing, valuation, and performance metrics across front-to-back value chains.

• Improved profitability forecasting and cross-product comparability through standardised ratio frameworks.

• Provided a scalable digital foundation for embedded banking & contextual finance delivery.