Introduction
The implementation of IFRS 9 has completely transformed how financial institutions conduct credit risk assessment and management practices. The past practice of banks using historical data to create provisions for credit risk has developed into a complete forward-looking process which needs advanced modeling abilities and accurate decision-making and effective governance.
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Organizations must fulfill more than just their IFRS 9 obligations in the present business climate which features economic instability and regulatory investigations and greater auditor requirements and stakeholder demands because they must show that their credit risk frameworks maintain their operational integrity and public accountability and organizational strength.
Our Credit Risk & IFRS 9 Advisory services provide support to banks NBFCs and financial institutions throughout the entire process of implementing and improving their Expected Credit Loss ECL systems. We collaborate with clients to develop effective SICR systems which improve their PD LGD and EAD modeling methods while incorporating future macroeconomic projections into their credit risk assessment process. In parallel, we support the design of structured management overlay frameworks to address emerging risks and model limitations, ensuring that outputs remain both relevant and defensible.
Our Service Offerings
IFRS 9 ECL Model Development & Enhancement
We support institutions in designing and refining Expected Credit Loss models that are aligned with regulatory expectations while remaining practical for operational use. This includes developing Probability of Default (PD), Loss Given Default (LGD), and Exposure at Default (EAD) models tailored to portfolio characteristics and data availability.
Where models are already in place, we assist in enhancing methodologies by incorporating forward-looking information, improving segmentation logic, and addressing performance gaps observed during model monitoring or audit reviews. Our approach ensures that models are not only statistically robust but also interpretable and aligned with internal risk management practices.
Independent Model Validation
Model validation is a critical pillar of IFRS 9 governance. We provide independent validation services that assess the conceptual soundness, methodological integrity, and performance of ECL models.
Our validation approach goes beyond technical testing. We assess the validity of our model assumptions, the need for overlays, and the alignment of results with both portfolio performance and economic conditions. Our examination includes governance frameworks together with documentation and change management processes to verify institutional readiness for regulatory and audit evaluation.
SICR Framework Design & Review
The assessment of Significant Increase in Credit Risk (SICR) represents a highly subjective process that requires extensive judgment under IFRS 9. Our team helps organizations develop and improve SICR frameworks which enable them to meet regulatory requirements while executing their business operations.
This process entails the assessment of quantitative thresholds together with qualitative indicators and backstop criteria which include days past due. The framework must maintain sufficient sensitivity to detect initial credit quality declines while preventing excessive fluctuations in credit risk assessment and unwanted credit assessment changes. Our team conducts back-testing and calibration methods to establish consistent and defendable results.
Macroeconomic & Management Overlay Framework
The integration of forward-looking macroeconomic data into ECL models represents an essential requirement which also presents significant challenges. Our team assists organizations in developing macroeconomic frameworks which establish connections between economic factors and credit risk assessment using variables such as GDP growth and inflation and unemployment rates.
We assist organizations in creating management overlay frameworks to address situations where model results do not completely reflect upcoming threats. The process establishes defined governance and documentation requirements which include justification procedures for overlays to maintain transparent and consistent auditing standards.
PD / LGD / EAD Methodology Review
IFRS 9 compliance requires organizations to execute accurate PD and LGD and EAD estimation. We conduct thorough assessments of these methodologies to determine their compliance with regulatory standards and industry norms. The review examines all components of model creation which includes data sources and methods of group division and procedures for accuracy testing and systems that track model effectiveness. The team finds all gaps and inconsistencies and model risk areas while they create practical solutions which enhance credit risk parameter control.
ECL Documentation & Audit Support
The documentation needs to achieve complete clarity and detail because it serves as proof of IFRS 9 compliance. We support institutions with documentation development and improvement work which describes model methods and assumptions and governance structures and validation systems.
Our organization assists institutions during their internal and external audit processes by providing support for audit inquiries and findings and for developing stronger control systems. We help institutions develop their ECL system through our support which prepares them for both regulatory assessments and audit testing.
Why Choose Us?
Our team brings extensive experience in credit risk modelling, IFRS 9 implementation, and regulatory advisory across diverse financial institutions. We understand credit risk frameworks because we possess technical knowledge and practical business experience. Our approach combines clear communication with rigorous standards and practical solutions which help institutions create compliance frameworks that maintain operational efficiency and clear visibility of their risk management capabilities in changing operational environments.
Frequently Asked Questions (FAQs)
How is Significant Increase in Credit Risk (SICR) actually determined under IFRS 9?
Typically, SICR is determined by comparing the change in lifetime Probability of Default (PD) since initial recognition. In practice, banks use quantitative measures, e.g., doubling of PD, as well as breaches of rating notch, in combination with qualitative measures, e.g., restructuring, sector stress. A general rule of thumb is 30 days past due (DPD).
What is the difference between 12-month ECL and Lifetime ECL in actual computation terms?
12-month ECL focuses on expected losses due to potential defaults in the following 12 months, whereas Lifetime ECL focuses on expected losses throughout the entire instrument life. The difference is in the horizon of Probability of Default (PD) applied, i.e., 12-month PD vs. lifetime PD, whereas LGD and EAD calculations remain the same.
How are forward-looking macroeconomic variables actually incorporated into ECL models?
Macroeconomic overlays are incorporated using a scenario-weighted model. Typically, 3-5 scenarios (base case, upside, and downside) are created, each with a probability assigned. GDP, inflation, unemployment, and interest rate variables, etc., are typically applied using regression/satellite models.
What methodologies are used to calculate Probability of Default (PD)?
PD can be estimated using through-the-cycle (TTC) or point-in-time (PIT) PD. IFRS 9 uses PIT PD estimates that may be produced using techniques such as logistic regression, transition matrices, or survival analysis.
How is Loss Given Default (LGD) adjusted under IFRS 9?
IFRS 9 adjusts LGD to take into account forward-looking recoveries, changes in collateral valuation, and economic downturn scenarios. Discounting is done using an effective interest rate (EIR), which allows for the computation of the present value of recoveries.
What is Exposure at Default (EAD) for revolving credit such as credit cards or overdrafts?
EAD comprises the amount already drawn plus expected future drawdowns using Credit Conversion Factors (CCF). Behavioral modeling is applied to estimate the utilization pattern up to the point of default.
How are Stage 1, Stage 2 and Stage 3 exposures operationally differentiated?
Stage 1: Performing assets – 12-month ECL calculation
Stage 2: SICR identification – Lifetime ECL calculation
Stage 3: Credit-impaired assets – Lifetime ECL + interest accrued on net amount
The movement from one stage to another is tracked using shifts in PD, DPD triggers, and credit events.
What is the process for multiple economic scenarios in the calculation of ECL?
Each of the scenarios is given a certain probability weight. For example, the Base scenario is 60%, the Downside is 30%, and the Upside is 10%. The ECL is then calculated for each of these scenarios to arrive at the final result.
What is the difference between write-off and provision under IFRS 9?
Provision represents the expected credit loss allowance, whereas write-off occurs when there is no reasonable expectation of repayment. Write-off reduces the gross carrying amount, whereas provision reduces the net carrying value.
What is the method of recognizing interest income for Stage 3 assets under IFRS 9?
The interest income is calculated using the net carrying amount instead of the gross exposure.
What are overlays? What is their application in ECL models?
Overlays represent management overlays that are applied when the model is not fully capturing the emerging risks that may occur. For example, overlays may be applied for geopolitical risks.
What is the validation process for IFRS 9 models?
The validation of IFRS 9 models is carried out through back testing of actual versus predicted defaults, sensitivity testing and benchmarking.
How is data quality ensured for IFRS 9 calculations?
Data is validated using reconciliation checks, completeness checks, as well as audit trails. When dealing with missing or inconsistent data, imputation methods or worst-case assumptions are employed.
What are some common implementation challenges in IFRS 9 ECL frameworks?
Some of the challenges that are faced include data availability issues, risk/finance system alignment, calibration under limited default histories, as well as using forward-looking data. Governance and documentation are also time-consuming.