Credit Rating Rationale Template (Obligor and Facility Rating, PD, LGD)

Credit Rating Rationale: [Obligor name], [Rating date]

Internal credit rating file for one obligor and its facilities: rating summary, rating system and master scale, financial and qualitative model inputs, score-to-grade mapping, peer benchmarking, rating drivers, overrides with their justification, group and country considerations, facility LGD, CCF and EAD, outlook and re-rating triggers, data quality, rating history and independent approval. Based on the internal ratings-based (IRB) requirements of Regulation (EU) No 575/2013 as amended by Regulation (EU) 2024/1623 (CRR3), Articles 169 to 175 and 178, the EBA Guidelines on PD estimation, LGD estimation and treatment of defaulted assets (EBA/GL/2017/16) and the EBA Guidelines on loan origination and monitoring (EBA/GL/2020/06). Replace every [bracketed] value and every row marked Example. This is a document format, not financial, credit, regulatory or accounting advice; obtain the regulation and guidelines for the normative text.

Document control

Approvals

Revision history

Contents

1. Rating summary
2. Rating system and master scale
3. Financial factors
4. Qualitative factors
5. Model output and grade mapping
6. Peer and benchmark comparison
7. Rating drivers
8. Overrides and adjustments
9. Group, country and support considerations
10. Facility rating: LGD, CCF and EAD
11. Outlook and re-rating triggers
12. Data quality and limitations
13. Rating history and performance tracking
14. Glossary and references

1. Rating summary

Example: The model improves Corvid by one grade because leverage fell to 0.62x and interest cover rose to 13.69x in FY2026. The approver confirmed a one-notch downward override: covenant EBITDA includes EUR 1,000k of net add-backs that flatter the margin input, and the FY2027 budget raises capex to EUR 12,000k (EUR 8,200k paid in FY2026) and the dividend to EUR 3,000k, so the forward cash cover is weaker than the historical inputs suggest. The grade stays FH-5 with a positive outlook; delivery of the FY2027 budget with DSCR above 1.60x would support FH-4 at the next review. The outlook is conditional: both facilities mature on 2028-06-30 and the borrower's board has mandated refinancing for signature by 2027-06-30, so failure to sign by then triggers an immediate re-rating (TRG-006).

Write the summary for a reader who knows the bank's rating system but not the borrower. Lead with the final grade and PD, then explain any difference from the model grade in one or two sentences. If the grade changed since the last review, say which inputs moved and by how much; a migration without a stated cause is the first thing an internal auditor or a supervisor will question. Keep the language factual: the rationale is evidence of an IRB process, and its tone should match that purpose.

2. Rating system and master scale

Master scale (Example):

The 0.05% PD of FH-1 equals the PD input floor for corporate exposures under CRR Article 160(1) as amended by CRR3; no performing grade may carry a lower PD in capital or expected loss calculations.

Explain the rating philosophy because it changes how a grade should be read. A point-in-time grade moves with the economic cycle and suits short-dated exposures and IFRS 9 inputs; a through-the-cycle grade is steadier and suits capital planning and limits. Most banks run a hybrid and convert grades for IFRS 9 using forward-looking adjustments. State which one applies so that readers do not compare grades across systems that use different philosophies.

3. Financial factors

Example: The model specification uses covenant EBITDA as reported in the compliance certificate, because it is verified by the auditors on an agreed-upon procedures basis. Covenant EBITDA (EUR 17,800k) equals management EBITDA (EUR 16,800k) plus a restructuring add-back of EUR 900k and a share-based payment add-back of EUR 500k, less a disposal gain of EUR 400k. Section 8 tests the effect of using management EBITDA instead. Net debt of EUR 11,000k is the covenant figure: Term Facility 30,000 plus lease liabilities 8,000 (gross debt 38,000), less freely available cash of 27,000 (cash of 28,000 excluding 1,000 held in Vietnam).

Source each input from the identified statements, record the extraction date, and keep the spreading worksheet with the file. When accounts are qualified, restated or more than 15 months old, say so here and consider an override or a data quality flag.

Spread the statements in the bank's standard template before scoring, and reconcile the spreading to the audited totals: revenue, EBITDA, net debt and cash. Check the treatment of leases, capitalised development cost, factoring or supplier finance, and pension deficits, because each changes leverage and cash flow ratios. When the borrower changes its accounting presentation (for example under IFRS 18 from 2027), restate the comparatives on one basis so that the trend in the model inputs reflects performance rather than presentation.

4. Qualitative factors

Write the evidence so that a second analyst would reach the same score. Where the model criteria do not fit the business (for example a platform business scored on a manufacturing grid), say so and consider a model scope exception rather than bending the scores.

Interviews with management, site visits and the relationship manager's knowledge are valid evidence, but record the date and the source. Where a score changed since the last review, give the reason in the evidence column, as in the example where the industry score improved because the recurring revenue share rose.

5. Model output and grade mapping

Example: A weighted score of 4.20 falls in the FH-4 band (3.25 to 4.24), with a PD of 0.40%. The score sits 0.05 below the FH-5 boundary, so a small change in any input would move the grade: a one-point worse score on profitability adds 0.10 and gives 4.30, which maps to FH-5. Record any such boundary proximity because it is relevant to the override in section 8.

Run the model in the production rating system, not in a spreadsheet copy, so that the run date, model version and inputs are logged. If the system and a manual calculation disagree, the system result stands until the difference is explained and, where needed, corrected through change control. Attach the system output to this file.

6. Peer and benchmark comparison

Example: Corvid's credit metrics are stronger than Peer A, which shares the grade, but Peer A has a higher and steadier margin and a longer record. The comparison supports FH-5 rather than FH-4 at this stage. External benchmarks (for example, a market-implied PD from a credit data provider) can be added if the bank's policy uses them; record the source and date.

Choose peers from the same model segment and size band, using their latest approved ratings. Comment on any peer that carries a better grade with weaker metrics, because such inconsistencies can reveal either an outdated peer rating or a model weakness. Do not let a peer comparison replace the model: it is a challenge tool for the approver, and any resulting change must go through the override process in section 8.

7. Rating drivers

Explain in a short paragraph how the drivers combine. Ratings that rest on one strong metric deserve more caution than ratings supported by several independent strengths.

Example: The strong balance sheet (DRV-001) and recurring revenue (DRV-002) carry the grade. Against them, heavy capex (DRV-003) and the near maturity (DRV-005) limit it: at 2027-12-31 both facilities will have less than 12 months to run, the Term Facility becomes a current liability and the undrawn revolving facility stops counting as committed headroom in the borrower's treasury policy. With leverage at 0.62x the refinancing should be achievable, but until it is signed it is the main forward risk, which is why the approver kept FH-5 rather than accepting the model's FH-4.

8. Overrides and adjustments

Override policy (Example): the analyst may propose up to one notch either way with the independent credit officer's approval; two notches need the head of credit risk; more than two notches, or any upward override above FH-4, need the rating committee. Upward overrides need evidence not available to the model, such as a binding guarantee or an equity injection after the reporting date.

8.1 Quantified support for OVR-001

Example: Replacing covenant EBITDA with management EBITDA (EUR 16,800k) moves the margin input to 12.0% and its score from 5 to 6, adding 0.10 to the total: 4.20 + 0.10 = 4.30, which maps to FH-5. The FY2027 budget increases capex from EUR 8,200k paid in FY2026 to EUR 12,000k and the dividend from EUR 2,600k to EUR 3,000k; budgeted cash flow is 21,600 - 2,100 - 3,300 - 12,000 = 4,200 against debt service of 1,200 + 1,600 = 2,800, a DSCR of 1.50x, down from 1.71x. Both points indicate that FH-4 would anticipate an improvement the borrower has not yet delivered.

Overrides are tracked in the override log, and the model owner analyses override performance by direction and by approver, as Article 172(3) requires; the bank's policy sets an annual analysis. A high override rate signals that the model needs recalibration; report it to the model risk function under Model Risk Management Policy (finance/model-risk-management-policy).

8.2 Questions the approver asks

Is the reason truly outside the model, or is it already captured by one of the inputs? Is the evidence dated and documented? Would the same reason lead to the same override for a comparable obligor? Does the override direction match the rating drivers in section 7? Is the override within the analyst's authority, and has it been entered in the override log with the approver's name? An override that cannot answer these questions should be rejected and the model grade kept, with the analyst's concern recorded as a monitoring point instead.

9. Group, country and support considerations

Explain any notching between entities (for example, a weaker non-guarantor subsidiary rated below the group) and how intra-group dependencies were assessed. Where support is assumed, describe its form (guarantee, keep-well letter, strategic importance) and the evidence.

10. Facility rating: LGD, CCF and EAD

Example: The LGD model segments unsecured guaranteed corporate exposures by guarantor coverage and jurisdiction; it adds a downturn component estimated per EBA/GL/2017/16 and the bank's downturn LGD methodology. The 32% estimate exceeds the 25% LGD input floor for unsecured corporate exposures under CRR Article 161(4) as amended by CRR3. A large corporate would instead carry the foundation LGD of 40% (CRR Art. 161(1)(aa)). Counterparty exposure on the interest rate swap (notional EUR 12,600k) is measured separately under the bank's counterparty credit risk approach and is outside this table.

11. Outlook and re-rating triggers

Link the triggers to the early warning indicators in the annual credit review so that monitoring and rating stay aligned.

Set triggers that the monitoring team can observe without re-running the full analysis: covenant ratios from the compliance certificate, payment behaviour, rating agency actions on related entities, and corporate events. Define the outlook in the bank's own terms (for example, positive means at least a one-in-three chance of an upgrade within 12 to 18 months) and use it consistently across the portfolio. A positive or negative outlook that persists for more than two reviews without a rating change should be challenged.

12. Data quality and limitations

State whether the model was used within its approved scope and whether any input was outside the range of the development data. A rating assigned with data more than 15 months old, or from unaudited accounts where audited ones are required, needs a flag in the rating system and approval at the next level.

13. Rating history and performance tracking

Under IFRS 9, compare the current lifetime PD with the lifetime PD at initial recognition for the same remaining term to assess a significant increase in credit risk; the bank's criteria are in ECL Methodology (finance/ecl-methodology). The grade PDs in this file are one-year, through-the-cycle values, so they only indicate the direction. In the example the grade improved from FH-6 (0.85%) at origination to FH-5 (0.60%), which indicates Stage 1; the formal SICR test runs on point-in-time lifetime PDs in the ECL engine.

Retain every version of this file for the period the bank's record-keeping policy requires and at least as long as the data may be used for model development or validation. Rating histories feed default and migration statistics, PD back-testing and the override performance analysis, so missing or overwritten records weaken the whole rating system, not just one file.

14. Glossary and references

14.1 Glossary

14.2 References

Standard and licence note

Based on Regulation (EU) No 575/2013 as amended by Regulation (EU) 2024/1623 and on EBA guidelines EBA/GL/2017/16, EBA/GL/2016/07 and EBA/GL/2020/06 (EBA material may be reproduced with acknowledgement of the source; none is reproduced here). Article and paragraph numbers are cited and requirements are described in original wording. IFRS 9 is cited by name and section number only; this template is not affiliated with or endorsed by the EBA or the IFRS Foundation. The scorecard, weights, master scale, PDs, LGDs and override policy in the example are fictional illustrations, not regulatory values, except the cited PD and LGD floors. Fernhollow Bank, Corvid Commerce Group and every figure are fictional. This template is original text written for this collection. Check the current official versions of the cited texts before use. Template licence: MIT.