Moody's Analytics RiskCalc Credit Risk Assessment Training Course

Course overview

Private-company credit decisions often rely on incomplete financial statements, borrower-supplied forecasts and qualitative judgement. Risk managers, relationship managers and credit analysts need a defensible way to translate financial information into consistent default-risk measures, compare obligors across sectors and geographies, and explain why a borrower’s risk profile has changed. This is particularly important when setting approval limits, pricing loans, monitoring covenant deterioration, assigning internal risk grades or supporting expected credit loss analysis.

This five-day Moody’s Analytics RiskCalc Credit Risk Assessment Training Course develops practical capability in using RiskCalc to assess private-firm credit risk. Participants work through financial statement preparation, model inputs, Probability of Default (PD) interpretation, peer benchmarking, qualitative adjustments and risk-grade mapping. They learn how to distinguish model output from credit judgement; investigate results affected by leverage, liquidity, profitability, cash-flow weakness and data quality; and document a credit conclusion that can withstand review by credit committees, internal audit and model-risk stakeholders.

Instructor-led demonstrations are combined with guided RiskCalc exercises, borrower case files, financial-ratio analysis and credit-committee workshops. Participants use structured templates to assess a private-company borrower, test alternative financial scenarios, interpret changes in estimated default risk and prepare a concise credit-risk assessment pack. The final deliverable is a completed RiskCalc-based borrower assessment, including data assumptions, PD interpretation, risk drivers, proposed internal rating and recommended monitoring actions.

The course is designed for experienced finance and credit professionals who already work with lending, counterparty, portfolio or financial-risk decisions and need to apply Moody’s Analytics RiskCalc with greater consistency and analytical discipline.

Course objectives

By the end of this course, participants will be able to:

• Prepare borrower financial statements and input data for a RiskCalc assessment
• Generate and interpret Probability of Default estimates using Moody’s Analytics RiskCalc
• Analyse the financial ratios and risk drivers underlying a private-firm credit assessment
• Benchmark a borrower’s default risk against relevant industry and regional peer groups
• Test sensitivity of RiskCalc results to changes in leverage, liquidity, profitability and cash flow
• Map RiskCalc PD outputs to an internal risk-grade or master-scale framework
• Apply qualitative credit judgement and data-quality challenge alongside model results
• Produce a documented RiskCalc-based borrower credit assessment for credit-committee review

Benefits of attending

Target competencies

Who should attend

• Credit Analysts — who assess private-company borrowers and prepare approval recommendations
• Corporate Relationship Managers — who need to structure facilities and explain borrower risk to credit teams
• Credit Risk Managers — who oversee rating consistency, portfolio quality and monitoring triggers
• Commercial Lending Underwriters — who require evidence-based PD estimates for new and renewed facilities
• Portfolio Risk Analysts — who monitor concentrations, migrations and emerging deterioration across obligors
• IFRS 9 and Expected Credit Loss Analysts — who use borrower risk measures to support staging and impairment analysis

Requirements and prerequisites

Participants should have practical experience reviewing company financial statements, including income statements, balance sheets and cash-flow statements, and should understand core credit concepts such as leverage, liquidity, debt service capacity, covenants, default risk and internal borrower ratings. Familiarity with Microsoft Excel and basic financial-ratio calculation is assumed. Prior exposure to Moody’s Analytics RiskCalc is useful but not required; the course begins with navigation and workflow. Participants do not need programming skills, econometric modelling expertise or prior experience building Probability of Default models.

Training methodology

The programme uses short instructor-led technical sessions followed by guided work in Moody’s Analytics RiskCalc and Microsoft Excel. Participants analyse progressively more complex private-company borrower files, reconcile financial data, generate PD estimates, investigate risk drivers and compare alternative credit scenarios. Small-group credit-committee discussions require participants to defend a proposed risk grade, facility position and monitoring plan. Each participant completes an end-of-course application plan identifying how RiskCalc workflows, documentation standards and escalation triggers will be applied to their own borrower or portfolio responsibilities.

Course outline

Day 1: RiskCalc foundations and private-company credit assessment

• Private-firm default risk and the role of RiskCalc in the credit process
• RiskCalc model purpose, coverage and private-company data requirements
• Probability of Default concepts, rating horizons and percentile interpretation
• RiskCalc workspace navigation and borrower assessment workflow
• Financial statement components used in private-company risk analysis
• Core credit ratios for leverage, liquidity, profitability and coverage
• Model output versus analyst judgement and governance responsibilities

Workshop: Participants review a borrower case file, identify missing or inconsistent financial information, and create a structured data-readiness checklist for RiskCalc input.

Day 2: Financial data preparation and model input discipline

• Financial statement spreading and period-selection decisions
• Treatment of non-recurring items and exceptional income or expenses
• Normalisation of related-party balances, shareholder loans and intercompany debt
• Working-capital analysis and cash conversion indicators
• Inputting balance-sheet, income-statement and cash-flow data in RiskCalc
• Currency, accounting-standard and fiscal-year consistency checks
• Data-quality controls and documentation of analyst assumptions

Workshop: Participants prepare and enter normalised financial data for a private manufacturer, recording adjustments and data-quality exceptions in an analyst workpaper.

Day 3: Interpreting PD estimates and borrower risk drivers

• Generating RiskCalc Probability of Default estimates
• Reading borrower scorecards and risk-driver outputs
• Interpreting PD changes across reporting periods
• Peer benchmarking by industry, geography and company profile
• Connecting leverage and interest coverage to default-risk movement
• Analysing liquidity stress, cash-flow pressure and profitability decline
• Recognising model limitations, outliers and implausible outputs

Workshop: Participants compare two years of RiskCalc results for a distributor, isolate the drivers of PD migration, and prepare a one-page risk-driver narrative.

Day 4: Credit judgement, scenario analysis and risk grading

• Mapping PD estimates to internal master scales and risk grades
• Applying qualitative overlays within documented credit policy
• Assessing management quality, ownership structure and business-model risk
• Designing financial downside scenarios in Microsoft Excel
• Testing leverage, margin, sales and working-capital sensitivities
• Setting early-warning indicators and borrower monitoring triggers
• Linking risk grades to limits, covenants, pricing and review frequency

Workshop: Participants run downside scenarios for a leveraged services company and recommend an internal grade, covenant response and monitoring schedule.

Day 5: Credit decision documentation and portfolio application

• Structuring a RiskCalc-based credit assessment memorandum
• Explaining PD estimates to relationship managers and credit committees
• Documenting assumptions, overrides and model-use limitations
• Using RiskCalc results in annual reviews and renewal decisions
• Using borrower PD information for portfolio segmentation and migration monitoring
• RiskCalc evidence for IFRS 9 and Expected Credit Loss workflows
• Implementation planning for individual teams and credit processes

Workshop: Participants complete and present a credit-committee pack containing RiskCalc results, scenario evidence, proposed risk grade and borrower monitoring actions.

Tools & standards covered

Moody’s Analytics RiskCalc, Microsoft Excel, IFRS 9 Financial Instruments, Basel III

A typical training day

Live online deliveries follow the same structure in the East Africa Time zone, with shorter screen blocks and longer breaks.

What the fee includes

How you can take this course

Certification

Participants who complete the full five days receive the Skillset Development Certificate of Completion, stating the course title, course code, dates and delivery format — suitable for professional-development records and employer reimbursement.

Frequently asked questions