Non-Performing Loan and Credit Impairment Audit Training Course

Course Introduction

Non-performing loans and credit impairment represent significant areas of financial, operational, regulatory, and reporting risk for banks and other lending institutions. Accurate identification of deteriorating credit exposures, appropriate classification of impaired assets, and reliable measurement of credit losses are essential to sound financial reporting and credit risk management. Non-Performing Loan and Credit Impairment Audit Training Course provides a structured methodology for auditing the processes used to identify, measure, monitor, provision for, and recover problem credit exposures.

Effective auditing of non-performing loans requires an understanding of the full credit lifecycle and the factors that indicate deterioration in borrower credit quality. Participants will examine delinquency indicators, default definitions, credit classifications, watchlists, restructuring, forbearance, collateral deterioration, borrower financial distress, and other indicators of increased credit risk. The course emphasizes how auditors can evaluate whether problem loans are identified consistently, classified appropriately, and supported by reliable evidence.

The program addresses credit impairment measurement and provisioning, including expected credit loss methodologies, staging, probability of default, loss given default, exposure at default, forward-looking information, macroeconomic assumptions, scenario weighting, and management overlays. Participants will explore how auditors can assess model governance, data quality, assumptions, calculations, validation, and management judgment. The course also considers how impairment results flow into financial statements, regulatory reporting, risk management, and portfolio-level decision-making.

Collateral and recovery information are important components of NPL assessment and impairment measurement. Participants will examine collateral valuation, realization assumptions, guarantees, recovery strategies, cash-flow forecasts, legal proceedings, restructuring arrangements, and recovery costs. Audit techniques will be used to evaluate whether expected recoveries are realistic, appropriately supported, and consistently incorporated into credit impairment calculations and loan classification decisions.

Technology and analytics can significantly strengthen NPL and impairment auditing by allowing auditors to examine entire loan populations rather than relying solely on traditional sampling. Participants will explore portfolio analytics, delinquency migration, roll-rate analysis, vintage analysis, concentration analysis, staging movements, provisioning trends, write-offs, recoveries, and model output testing. The program also considers emerging risks arising from automated credit systems, alternative data, artificial intelligence, changing economic conditions, and evolving credit risk models.

Throughout the program, participants will apply the concepts through practical exercises and an integrated NPL and credit impairment audit case study. The case study covers identification of problem loans, classification, staging, impairment calculations, collateral assessment, provisioning, write-offs, recoveries, restructuring, analytical testing, and audit reporting. Participants will develop a practical framework for assessing whether NPL management and credit impairment processes are accurate, well-controlled, consistently applied, and adequately supported by evidence.

Duration

10 days

Who Should Attend

• Internal auditors responsible for auditing credit portfolios, loan impairment, and non-performing loans.

• Credit risk professionals involved in monitoring problem loans, portfolio quality, and credit deterioration.

• Banking auditors reviewing credit classification, provisioning, impairment, and loan recovery processes.

• Finance professionals responsible for credit impairment accounting and financial reporting.

• Credit managers overseeing non-performing loan identification, restructuring, and recovery strategies.

• Risk managers responsible for expected credit loss frameworks, credit risk models, and portfolio monitoring.

• Financial controllers responsible for loan accounting, provisions, write-offs, and impairment reconciliations.

• Credit analysts evaluating borrower deterioration, restructuring, collateral, and recovery prospects.

• Loan recovery and collections professionals involved in managing distressed and non-performing exposures.

• Compliance professionals reviewing credit classification, provisioning, and regulatory reporting requirements.

• Forensic accountants investigating unusual impairment adjustments, write-offs, recoveries, or credit decisions.

• Audit managers supervising financial institution credit and impairment audits.

• Data analysts supporting loan portfolio monitoring, credit risk analytics, and impairment testing.

• Governance and assurance professionals reviewing credit risk controls and management estimates.

• Professional advisers and consultants supporting NPL management, impairment assessment, and credit risk assurance.

Course Objectives

• Develop a comprehensive understanding of non-performing loan identification, classification, monitoring, impairment, provisioning, recovery, and reporting processes.

• Assess whether loan classification and default identification procedures consistently reflect established credit policies, accounting requirements, and applicable regulatory expectations.

• Evaluate indicators of increased credit risk, borrower deterioration, delinquency, restructuring, forbearance, and other conditions associated with potential impairment.

• Apply audit procedures to expected credit loss methodologies, including staging, probability of default, loss given default, exposure at default, and forward-looking information.

• Assess the quality and reliability of data used in impairment models, including borrower information, historical loss data, collateral information, recovery records, and macroeconomic inputs.

• Evaluate the reasonableness of management assumptions, overlays, scenario weighting, forecasts, and other significant judgments affecting credit impairment calculations.

• Audit collateral valuations, guarantees, recovery forecasts, legal proceedings, and other credit risk mitigation information used in measuring expected recoveries.

• Use portfolio-level analytics to identify delinquency trends, migration patterns, concentration risks, unusual impairment movements, and potential classification inconsistencies.

• Evaluate controls over restructuring, refinancing, forbearance, write-offs, recoveries, and transfers between performing and non-performing loan categories.

• Identify potential manipulation or bias in NPL classification, provisioning, write-offs, recoveries, and impairment estimates and develop appropriate audit responses.

• Assess technology, model governance, automated credit monitoring, data interfaces, and emerging risks affecting NPL identification and impairment measurement.

• Complete an integrated NPL and credit impairment audit case involving portfolio analysis, classification testing, impairment assessment, evidence evaluation, and audit reporting.

Comprehensive Course Outline

Module 1: Foundations of Non-Performing Loans and Credit Impairment Auditing

• Understanding non-performing loans, credit deterioration, default, impairment, provisioning, write-offs, and recoveries.

• Relationship between credit risk management, loan classification, impairment accounting, financial reporting, and regulatory reporting.

• Key risks auditors should consider when evaluating NPL identification, measurement, monitoring, and recovery processes.

• Emerging developments in credit risk management, impairment methodologies, digital lending, and portfolio-level credit analytics.

Module 2: Loan Portfolio Classification and Default Identification

• Reviewing policies and criteria used to classify performing, watchlist, past-due, impaired, and non-performing credit exposures.

• Assessing quantitative and qualitative indicators of default, including delinquency, financial distress, covenant breaches, and restructuring.

• Testing whether classification changes occur promptly and consistently when credit risk deterioration becomes evident.

• Identifying classification inconsistencies, delayed recognition, inappropriate upgrades, and other weaknesses in problem loan identification.

Module 3: Credit Deterioration and Early Warning Indicators

• Identifying early warning indicators associated with borrower financial deterioration and increasing probability of default.

• Analyzing missed payments, declining cash flows, covenant breaches, credit score changes, adverse industry conditions, and other risk indicators.

• Evaluating watchlists, risk-rating migrations, borrower monitoring reports, and escalation processes for deteriorating exposures.

• Assessing whether early warning information is appropriately integrated into NPL classification, impairment assessment, and credit management decisions.

Module 4: Non-Performing Loan Identification and Audit Testing

• Designing audit procedures to test NPL identification across retail, SME, corporate, commercial, and specialized lending portfolios.

• Reconciling loan systems, delinquency reports, risk classifications, financial records, and regulatory reporting populations.

• Testing samples and full populations for overdue balances, default events, restructuring, and other classification triggers.

• Evaluating controls over NPL reporting, classification changes, management review, exception handling, and escalation.

Module 5: Expected Credit Loss and Impairment Frameworks

• Understanding expected credit loss concepts and their role in measuring credit impairment and financial reporting.

• Examining staging frameworks, significant increases in credit risk, lifetime versus shorter-horizon expected losses, and default considerations.

• Reviewing the relationship between impairment models, credit risk systems, accounting records, and financial statement reporting.

• Evaluating governance over impairment methodology changes, policy interpretation, implementation, and management judgment.

Module 6: Impairment Data, Models and Methodologies

• Assessing data inputs used in credit impairment models, including historical losses, defaults, exposures, recoveries, and borrower characteristics.

• Evaluating probability of default, loss given default, exposure at default, discounting, and other model components.

• Reviewing model segmentation, portfolio characteristics, historical observation periods, and data representativeness.

• Identifying model limitations, data gaps, implementation errors, inappropriate assumptions, and weaknesses in model documentation.

Module 7: Forward-Looking Information and Management Judgments

• Evaluating macroeconomic forecasts, economic scenarios, probability weighting, and other forward-looking information used in impairment estimates.

• Assessing management overlays, post-model adjustments, expert judgments, and other estimation techniques applied to credit loss calculations.

• Testing the consistency of assumptions with internal forecasts, external information, historical experience, and observable portfolio conditions.

• Evaluating governance over judgmental adjustments, approval processes, documentation, monitoring, and retrospective assessment.

Module 8: Collateral, Guarantees and Expected Recoveries

• Auditing collateral identification, valuation, ownership, enforceability, realization assumptions, and valuation frequency.

• Evaluating guarantees, insurance, security interests, and other credit risk mitigation arrangements supporting recovery estimates.

• Assessing expected recovery timing, legal costs, selling costs, collection expenses, and other factors affecting recoverable amounts.

• Identifying unsupported collateral values, outdated valuations, duplicate security, weak guarantees, and unrealistic recovery assumptions.

Module 9: Loan Restructuring, Forbearance and Modified Exposures

• Evaluating restructuring, refinancing, rescheduling, concessions, payment holidays, and other forms of borrower forbearance.

• Assessing whether modified loans are appropriately classified, monitored, measured, and included in impairment calculations.

• Identifying evergreening indicators, repeated restructurings, artificial cures, and other patterns that may obscure underlying credit deterioration.

• Reviewing approval, documentation, monitoring, and escalation controls for restructured and modified credit exposures.

Module 10: NPL Recovery, Write-Offs and Collections

• Auditing collection strategies, recovery forecasts, legal recovery processes, settlements, collateral realization, and cash recoveries.

• Evaluating write-off policies, approval authorities, documentation, accounting treatment, and continued recovery activities after write-off.

• Reconciling recoveries, write-offs, loan balances, collateral proceeds, and accounting records to identify inconsistencies.

• Assessing recovery performance, collection costs, recovery assumptions, and the reliability of information used in impairment estimates.

Module 11: Credit Impairment Analytics and Portfolio Monitoring

• Applying delinquency migration, roll-rate, vintage, cohort, concentration, and trend analysis to loan portfolio data.

• Comparing NPL ratios, impairment charges, coverage ratios, write-offs, recoveries, and provisioning trends across periods and portfolio segments.

• Identifying unusual movements in staging, impairment, default rates, recovery assumptions, and portfolio quality indicators.

• Using data analytics to identify individual exposures and portfolio segments requiring additional audit investigation.

Module 12: Fraud, Manipulation and Bias in NPL and Impairment Processes

• Identifying risks of delayed NPL recognition, inappropriate loan upgrades, unsupported restructuring, and manipulation of credit classifications.

• Examining potential management bias in impairment assumptions, overlays, recovery forecasts, collateral valuations, and write-off decisions.

• Analyzing unusual employee, branch, product, portfolio, or period-end patterns that may indicate inappropriate credit risk reporting.

• Developing audit procedures to investigate anomalies while distinguishing risk indicators from confirmed misconduct or reporting errors.

Module 13: Credit Impairment Controls, Governance and Model Validation

• Evaluating governance frameworks covering credit impairment methodology, model ownership, approval, validation, monitoring, and change management.

• Assessing controls over model inputs, calculations, staging decisions, manual adjustments, outputs, reconciliations, and financial reporting.

• Reviewing independent model validation, back-testing, performance monitoring, sensitivity analysis, and model limitations.

• Evaluating segregation of duties and accountability among credit risk, finance, model development, validation, internal audit, and senior management.

Module 14: Technology, Automation and Emerging Credit Risks

• Auditing automated NPL identification, credit monitoring systems, impairment engines, data interfaces, and technology-enabled risk processes.

• Evaluating system configurations, access controls, change management, data lineage, interfaces, and automated staging or classification rules.

• Assessing emerging risks from artificial intelligence, alternative data, digital lending, real-time credit monitoring, and automated impairment models.

• Addressing cybersecurity, data integrity, model drift, system resilience, third-party technology, and technology-driven credit risk challenges.

Module 15: Financial Reporting, Regulatory Reporting and Audit Findings

• Reconciling impairment calculations, NPL classifications, provisions, write-offs, recoveries, and financial reporting balances.

• Evaluating the presentation and disclosure of credit risk, impairment, provisioning, significant judgments, and estimation uncertainty.

• Assessing consistency between financial reporting, management information, regulatory returns, credit risk systems, and underlying loan records.

• Developing clear audit findings that explain the condition, root cause, risk impact, supporting evidence, and recommended corrective action.

Module 16: Integrated NPL and Credit Impairment Audit Case Study

• Analyzing a loan portfolio to identify NPLs, credit deterioration, staging movements, classification issues, and significant impairment risks.

• Testing selected impairment calculations, model inputs, collateral values, recovery assumptions, management overlays, and supporting documentation.

• Applying portfolio analytics to identify unusual movements, inconsistencies, concentration risks, and potential weaknesses requiring further audit work.

• Preparing an integrated audit report covering NPL classification, impairment measurement, control deficiencies, financial implications, and remediation actions.

Training Approach

This course will be delivered by our skilled trainers who have vast knowledge and experience as expert professionals in the fields. The course is taught in English and through a mix of theory, practical activities, group discussion and case studies. Course manuals and additional training materials will be provided to the participants upon completion of the training.

Tailor-Made Course

This course can also be tailor-made to meet organization requirement. For further inquiries, please contact us on: Email: training@upskilldevelopment.com Tel: +254 721 331 808

Training Venue 

The training will be held at our Upskill Training Centre. We also offer training for a group (at a discount of 10% to 50%) at requested location all over the world. The Onsite course fee covers the course tuition, training materials, two break refreshments, buffet lunch, airport transfers, Upskill gift package, and guided tour.

Visa application, travel expenses, dinners, accommodation, insurance, and other personal expenses are catered by the participant

Certification

Participants will be issued with Upskill certificate upon completion of this course.

Airport Pickup and Accommodation

Airport pickup and accommodation is arranged upon request. For booking contact our Training Coordinator through Email: training@upskilldevelopment.com, +254 721 331 808

Terms of Payment:

Unless otherwise agreed between the two parties’ payment of the course fee should be done 3 working days before commencement of the training so as to enable us to prepare better.