Macro Scenarios Data Pack for ECL Models and Analysis

Key benefits & value for IFRS 9 teams

The Macro Scenarios Data Pack delivers validated macroeconomic reference data that reduces model preparation time and increases consistency across ECL calculations and disclosures. By standardising scenario inputs you:

• Reduce operational effort: No need to source, normalise and format multiple series for each reporting cycle.
• Improve model governance: Documented scenario construction and version history for audit trails and internal review.
• Enhance comparability: Use the same macro drivers across PD, LGD and forward‑looking overlays for consistent ECL outcomes.
• Speed up disclosures: Pre-prepared tables and narrative templates to include in financial statements and management packs.

Use cases & real-life scenarios

Monthly reporting and quarter-end ECL runs

Replace manual ad-hoc data pulls with the pack’s monthly and quarterly series. Example: feed baseline and downside GDP paths into your PD migration matrix and produce immediate sensitivity tables for the quarter-end board pack.

Stress testing and ICAAP alignment

Use the downside and severe-downside scenarios to stress-model credit losses over a multi-year horizon. The pack’s scenario narratives make it easier to defend chosen stress levels in regulatory submissions.

Model development and validation

Analysts can test alternative macro-to-credit mappings using consistent input series. The pack includes historical backcasts for sanity checks and benchmarking during validation exercises.

Who is this product for?

The pack is designed for financial institutions and companies that apply IFRS 9 and need accurate, fully compliant models and reports for Expected Credit Loss calculations, including:

• Commercial and retail banks
• Consumer and SME finance companies
• Leasing firms and asset finance providers
• Insurance companies with credit exposures
• Model validation teams, finance controllers and risk committees

How to choose the right pack

Choose based on geography, frequency and time horizon:

• Geography: Global pack vs regional packs — select the regional variant that matches your portfolio concentration.
• Frequency: Monthly series for dynamic models; quarterly for reporting-focused users.
• Horizon: Standard 5–10 year projections for IFRS 9; short (1–3 year) for near-term sensitivity work.

If your portfolio spans multiple regions or requires bespoke scenario weights, choose the customisable option and request a mapping call with our support team.

Quick comparison with typical alternatives

Consider three common approaches: building internal series, subscribing to raw macro vendors, or using this packaged solution.

• Internal build: High cost and governance overhead; slower to produce audit-ready documentation.
• Raw vendor feeds: Good data depth but require significant formatting and scenario design work for IFRS 9.
• Macro Scenarios Data Pack: Designed for ECL — formatted, documented and accompanied by scenario narratives and mapping templates to accelerate IFRS 9 compliance.

Best practices & tips to get maximum value

• Map macro variables to model inputs explicitly (e.g., GDP → PD multipliers; CPI → recovery lag adjustments).
• Use the pack’s historical backcasts to calibrate your macro-to-credit elasticities.
• Apply scenario weights consistently across PD and LGD and document rationale in your model governance files.
• Retain versioned copies of the pack per reporting period to keep a clear audit trail.

Common mistakes when using macro data — and how to avoid them

• Mixing frequencies: Avoid feeding monthly inputs into a quarterly model without proper aggregation — use the pack’s aggregation guidance.
• Unclear scenario linkage: Always document how each scenario maps to PD/LGD changes; our mapping templates help standardise this.
• Over-reliance on a single source: Use the pack’s notes on data sources and validation checks to cross-verify extreme values before running model scenarios.

Product specifications

• Included variables: GDP growth, CPI / inflation, short-term policy rate, selected long-term rates, unemployment rate (where available).
• Formats: Excel (.xlsx), CSV time series, and a mapping template for common ECL engines.
• Frequencies: Monthly and quarterly series; historical backcast (10–20 years depending on region).
• Projection horizon: Up to 10 years with baseline, upside and downside scenarios.
• Documentation: Scenario methodology note, narrative descriptions, source references and version history.
• Support: One included technical consultation for mapping and an option for customisation or additional support packages.

Frequently asked questions