LGD Database for Average Post-Default Losses by Collateral Type

Key benefits & value for the buyer

Our LGD database turns heterogeneous collateral information into consistent, model-ready inputs you can use immediately in Expected Credit Loss (ECL) calculations under IFRS 9. The dataset is designed to reduce estimation risk and support defensible provisioning assumptions.

Direct advantages

• Faster model delivery: Pre-built collateral LGD tables cut weeks off data preparation.
• Regulatory-ready documentation: Methodology notes, sample calculations and disclosure templates tailored to IFRS 9.
• Improved accuracy: Benchmarks segmented by recovery channels and post-default timelines reduce bias in loss given default estimates.
• Cost-effective: Access industry-aligned LGD by collateral type without the overhead of a large data collection program.

Use cases & real-life scenarios

How financial institutions typically use the LGD database:

• Retail mortgage portfolios: Use mortgage collateral LGD curves to set post-default loss given default inputs for Stage 1–3 modelling and sensitivity testing.
• Auto finance: Apply vehicle collateral LGD benchmarks for repossession and secondary-market recovery assumptions.
• Corporate secured lending: Map collateral types (inventory, receivables, fixed assets) to LGD bands when internal loss history is limited.
• Leasing and asset finance: Estimate expected recoveries and write-off timing for leased equipment across vintages.
• Model validation & audit: Use the database as an independent benchmark for validating internally estimated LGDs.

Who is this product for?

Designed for credit risk teams, model validators, finance departments and internal audit functions within institutions that apply IFRS 9:

• Retail and corporate banks
• Consumer finance and leasing companies
• Insurance firms with credit exposures
• Third-party model providers and consultants preparing ECL reports

How to choose the right dataset

Choosing the appropriate LGD database version depends on coverage, granularity and integration needs. Consider:

• Geographic coverage: Local/regional vs global benchmarks — pick datasets aligned with your portfolio geography.
• Collateral granularity: The number of collateral types and whether you need sub-types (e.g., residential vs buy-to-let mortgage).
• Vintage and historical depth: Use longer histories for portfolios with cyclical risk; shorter, recent vintages for rapidly changing markets.
• Delivery format: Excel/CSV for quick analysis; database-ready exports (SQL/JSON) for integration with ECL engines.

Quick comparison with typical alternatives

Common alternatives and why the LGD database is often the better choice:

• Internal-only data: Best when large, high-quality loss histories exist. Our database complements internal data where samples are small or biased.
• Generic industry benchmarks: Generic figures are quick but often lack collateral-level granularity. This LGD database provides collateral-specific benchmarks that align with recovery mechanics.
• Bespoke consultancy studies: Custom studies deliver high accuracy but at higher cost and lead time. Our dataset offers a balance of quality, documentation and price with optional customization.

Best practices & tips to get maximum value

• Map your internal collateral taxonomy to the database and maintain a translation table to ensure consistent use across models.
• Use the database as a conservative floor when internal LGD estimates have limited observations.
• Document any regional adjustments and stress-testing approaches when applying benchmarks to IFRS 9 scenarios.
• Combine database LGDs with behavioural adjustments (e.g., cure rates, time-to-recovery) to reflect your institution’s processes.

Common mistakes when buying/using LGD data and how to avoid them

• Mistake: Applying a single LGD for all secured loans. Fix: Use collateral-specific LGD bands for more accurate ECLs.
• Mistake: Ignoring methodology. Fix: Review the database calculation notes and align assumptions with your recovery timeline.
• Mistake: Poor integration with systems. Fix: Choose the delivery format that matches your ECL engine (CSV/SQL) and use the mapping templates included.

Product specifications

• Product type: Reference data pack (LGD by collateral type)
• Formats included: Excel (.xlsx) with documentation, CSV exports, sample SQL import script
• Collateral types covered: Mortgages, vehicles, equipment, inventory, receivables, cash & securities, mixed collateral
• Geographic scope: Global core set with regional splits (country-level add-ons available)
• Historical depth: Up to 15 years where available; vintage and recovery-timing tables included
• Delivery: Instant download after purchase; customization and integration services available
• Support: 30 days complimentary setup support + optional extended support contracts

Frequently asked questions