Bank Valuation and Financial Modelling Training Course

Duration 5 days 10 modules · 33 contact hours
Level Intermediate Certificate on completion
Who attends Equity Research Analysts, Corporate Finance Analysts and others
Fee from USD 1,100 KSh 95,000 for Kenyan organisations
Where 52 cities + online See dates by city
Next start 16 Nov 2026 Course code SD-BI-146

Before you join: Participants should be comfortable reading income statements, balance sheets and cash flow statements, and should have working experience with Excel formulas, linked worksheets and basic financial ratios.

Dates & prices

Two start dates a month in every city, and live online on weekdays or weekends. Fees are per participant; classroom fees include tuition, materials, lunch and refreshments, and the certificate.

Suggest a date or city

Showing the next six months. Later dates, other cities and private deliveries for your team are available on request.

Course overview

Banks cannot be valued reliably by applying a generic corporate model to reported earnings. Deposits are both customer funding and balance-sheet liabilities; loan growth consumes capital; expected credit losses can change earnings materially; and regulatory capital and liquidity requirements constrain dividend capacity. Analysts, finance teams and investment professionals need to connect these drivers before reaching a defensible estimate of value.

This course develops the bank-specific modelling and valuation skills used in equity research, corporate finance, credit analysis and strategic planning. Participants build forecast logic for loans, deposits, net interest income, fee income, operating costs, credit losses, capital ratios and dividend capacity. They apply IFRS 9 expected credit loss concepts, Basel III capital mechanics, comparable-company analysis, dividend discount models and residual income valuation. The course also addresses interest-rate sensitivity, asset quality, funding risk, sustainable return on equity and justified price-to-book multiples.

Teaching combines focused instructor briefings with bank financial statement analysis, worked modelling cases, group-based valuation reviews, scenario simulations and structured application planning. Participants use realistic assumptions from retail, corporate and universal banking settings, then test how changes in credit quality, interest rates, capital targets and growth affect valuation. They leave with a reusable bank valuation model structure, forecast schedules, valuation templates and a model review checklist suitable for adaptation to their own institution or coverage universe.

The course is suited to professionals who already work with financial statements or financial models and need to assess banks with greater technical discipline. It is particularly relevant where investment, lending, planning, transaction or regulatory decisions depend on credible bank forecasts and clearly explained valuation conclusions.

What you will be able to do

  • Build linked forecasts for loans, deposits, earnings, capital and dividends
  • Interpret bank financial statements using IFRS classification and disclosure requirements
  • Calculate expected credit losses using PD, LGD, EAD and staging assumptions
  • Model net interest income under changing yield curves and repricing assumptions
  • Forecast CET1 ratios, risk-weighted assets and regulatory capital headroom
  • Apply comparable-company, dividend discount and residual income valuation methods
  • Test valuation sensitivity to credit costs, interest rates, growth and cost of equity
  • Present a bank valuation conclusion with assumptions, risks and review evidence

Benefits of attending

For you

  • Produce defensible bank valuation ranges using multiple valuation methods
  • Identify the capital and credit assumptions driving bank share values
  • Build forecast schedules that reconcile earnings, balance sheets and regulatory capital
  • Challenge bank management forecasts using asset quality and funding indicators
  • Present valuation conclusions clearly to investment, credit and finance stakeholders

For your organisation

  • More consistent bank valuations across research, lending and transaction decisions
  • Improved challenge of assumptions behind growth, impairments and dividend forecasts
  • Stronger links between financial planning, capital management and shareholder value
  • Reduced model risk through clearer workbook controls and reconciliation checks
  • Better communication of credit, funding and interest-rate risks to decision makers

Course modules

10 modules over 5 days

Participants can identify the operating, regulatory and shareholder-return drivers that determine bank value.

  • Bank balance-sheet intermediation: deposits, loans, securities and contingent exposures
  • Interest income, fee income and risk costs traced to drivers
  • Universal, retail, corporate and investment bank business-model comparisons
  • Basel III capital, liquidity and risk-weighted asset constraints
  • Regulatory perimeter, consolidation and prudential reporting distinctions explained
  • Map management priorities to shareholder returns and valuation drivers

Participants can interpret bank financial statements and isolate items relevant to forecasting and valuation.

  • IFRS bank income statement: net interest, fees, impairments and tax
  • Classify amortised cost, FVOCI and FVTPL financial instruments
  • Reconcile reported equity, OCI movements and distributable reserves
  • Trace loan-loss provisions through profit, capital and book value
  • Read cash flow statements without treating deposits as ordinary working capital
  • Identify non-recurring items and accounting distortions in peer comparisons

Participants can construct integrated forecasts for a bank's balance sheet, income statement and key ratios.

  • Build loan, deposit and securities schedules from opening balances
  • Segment assets by product, geography, currency and risk grade
  • Forecast volume growth using macroeconomic, customer and management assumptions
  • Model yield curves, repricing gaps and asset-liability spread assumptions
  • Project fee income, operating expenses and cost-to-income ratios
  • Use scenario drivers to connect forecasts across linked schedules
  • Establish audit checks for balance-sheet balancing and formula integrity

Participants can forecast loan-loss provisions using IFRS 9 staging and expected credit loss drivers.

  • IFRS 9 staging: Stage 1, Stage 2 and credit-impaired exposures
  • Calculate expected credit losses from PD, LGD and EAD assumptions
  • Translate macroeconomic scenarios into probability-weighted impairment forecasts
  • Separate charge-offs, recoveries, write-backs and provision movements within forecasts
  • Assess non-performing loan ratios, coverage and vintage indicators
  • Stress credit costs under recession, unemployment and collateral-price shocks

Participants can assess how prudential requirements affect growth, distributions and bank equity value.

  • Calculate CET1, Tier 1 and total capital ratios
  • Derive risk-weighted assets using credit, market and operational risk inputs
  • Link retained earnings, dividends and capital issuance to CET1 forecasts
  • Interpret Common Equity Tier 1 buffers and management headroom
  • Compare Liquidity Coverage Ratio and Net Stable Funding Ratio mechanics
  • Assess dividend capacity against regulatory minima and internal capital targets

Participants can model net interest income and assess earnings sensitivity to interest-rate movements.

  • Construct net interest income from average balances, yields and costs
  • Measure net interest margin, spread and deposit beta movements
  • Model fixed-rate and floating-rate repricing under interest-rate scenarios
  • Analyse gap reports, duration exposure and basis-risk limitations
  • Forecast treasury income, hedging effects and securities portfolio returns
  • Reconcile interest-rate sensitivity disclosures with modelled earnings outcomes

Participants can select and apply valuation methods appropriate to bank capital and distribution economics.

  • Select valuation methods consistent with bank capital and distribution economics
  • Apply price-to-book and price-to-earnings multiples using comparable banks
  • Normalise peer metrics for profitability, risk, growth and capital differences
  • Calculate residual income from book value, return on equity and cost equity
  • Build dividend discount models from payout and capital requirements
  • Triangulate market, income and franchise-value evidence into valuation ranges

Participants can estimate sustainable bank returns and test their implications for valuation multiples and terminal value.

  • Estimate cost of equity using CAPM, beta, risk-free rate and premium
  • Distinguish reported return on equity from sustainable return on equity
  • Forecast payout ratios from earnings, growth and target capital
  • Test price-to-book justified multiples using return and growth assumptions
  • Analyse sensitivity to terminal growth, cost of equity and ROE
  • Explain why enterprise-value DCF requires adaptation for deposit-taking banks

Participants can structure, audit and document a transparent bank valuation model.

  • Structure workbook inputs, calculations, outputs and review controls
  • Apply consistent sign conventions, units, dates and formula architecture
  • Create linked forecast schedules for assets, funding, capital and earnings
  • Use data tables for valuation sensitivities and scenario comparison
  • Audit circularity, hardcodes, broken links and balance-sheet reconciliation
  • Document assumptions, sources, version control and model limitations

Participants can communicate a bank valuation conclusion and plan its use in a workplace assignment.

  • Translate model outputs into an investment or credit committee narrative
  • Present base, upside and downside valuation ranges with key assumptions
  • Separate market price movements from fundamental value-driver changes
  • Frame risks around asset quality, funding, capital and interest rates
  • Prepare challenge responses for governance, audit and senior management review
  • Draft a workplace application plan for a bank valuation assignment

Exercises and examples are adapted to each cohort's sectors and roles.

What you take back to work

  1. Linked bank financial model template
  2. IFRS 9 impairment forecast schedule
  3. Regulatory capital and dividend capacity template
  4. Net interest income sensitivity model
  5. Bank valuation methods comparison sheet
  6. Bank model review checklist

Who should attend

  • Equity Research Analysts — value listed banks and defend investment recommendations
  • Corporate Finance Analysts — assess bank transactions, strategic options and shareholder value
  • Credit Analysts — connect borrower performance, capital strength and funding risk
  • Bank Finance Managers — improve planning models, earnings forecasts and capital projections
  • Investment Banking Associates — prepare bank valuations for M&A and capital markets work
  • Risk and Treasury Professionals — interpret interest-rate, liquidity and capital effects on earnings

Skills and tools covered

Bank financial modellingCredit loss forecastingCapital ratio analysisInterest income modellingBank equity valuationModel audit controls

Tools and standards

IFRS 9, Basel III, Capital Asset Pricing Model (CAPM), Residual income model

How the course runs

Training methodology

The course uses short technical briefings followed by worked bank cases, financial statement reviews, group exercises and model-building simulations. Participants analyse retail, corporate and universal bank data, translating operating assumptions into linked earnings, capital and valuation outputs. Instructor feedback focuses on forecast logic, accounting treatment, capital constraints and model controls. Group discussions compare alternative valuation methods and challenge key assumptions. Each participant completes an application plan identifying how the methods, templates and review checks will be used in their work.

Requirements and prerequisites

Participants should be comfortable reading income statements, balance sheets and cash flow statements, and should have working experience with Excel formulas, linked worksheets and basic financial ratios. Prior exposure to corporate valuation, banking products, credit analysis, budgeting or financial planning is useful. The course assumes confidence with percentage calculations, discounted valuation concepts and financial statement terminology. Participants do not need prior experience building bank models, programming, advanced econometrics, regulatory reporting systems or specialist valuation software.

A typical training day

08:30 – 10:30First session
10:30 – 10:45Refreshment break
10:45 – 12:30Second session
12:30 – 13:30Lunch and networking
13:30 – 15:00Third session
15:00 – 15:15Refreshment break
15:15 – 16:30Workshop and daily review

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

What the fee includes

  • Instruction by a practitioner facilitator
  • Full course workbook and materials
  • Exercise files, templates and case studies
  • Refreshments and lunch on classroom deliveries
  • Certificate of completion
  • Post-course application plan

Frequently asked questions

Participants should be able to read financial statements and use Excel for linked calculations and financial ratios. Prior banking or valuation experience is useful, but previous bank modelling experience is not required.

Participants should bring a laptop with Excel or equivalent spreadsheet software for classroom delivery. Course materials and case data are provided, and participants may bring non-confidential examples of modelling questions from their work.

The course suits equity research, corporate finance, credit, treasury, risk and bank finance professionals. It also fits managers who review bank forecasts, valuation papers or capital plans prepared by others.

The course focuses on issues specific to deposit-taking institutions, including regulatory capital, expected credit losses, net interest margins, funding and dividend constraints. Generic enterprise-value DCF methods are considered, but adapted critically for bank economics.

Participants can adapt the model structure and checklists to bank forecasts, lending assessments, investment cases, planning cycles and transaction analysis. The methods support both building models and reviewing assumptions prepared by colleagues or management teams.

Each training day runs from 08:30 to 16:30 and provides about 6.5 contact hours. The five days progress from bank financial statements and forecast drivers through credit, capital, valuation, model review and communication.

Questions about this course?

Ask about dates, fees, group bookings or running it for your team. Our training team replies by email.

Ask on WhatsApp info@skillsetdevelopment.com

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