Bank and FIG Modeling

Developed for FIG-focused investment bankers, equity research analysts and corporate finance teams at banks, the bank modeling program guides trainees through a bank’s financial statements, unique drivers, and regulatory framework. Trainees then build a fully integrated financial statement model, a residual income (RI) model, and a dividend discount model (DDM) using Valley National Bank as a case study.

Provider: Wall Street Prep
Difficulty: Very difficult
Rating: 4

What You Will Learn

Building a bank forecast model, Building a bank valuation model

Couse structure

Section One: Building a bank forecast model

  • Build an advanced bank forecast model, projecting asset and liability balances, interest rates and spreads for key assets and liabilities, using industry best practices
  • Learn to effectively forecast the loan portfolio, investment securities, and deposits
  • Understand the modeling and forecasting of allowances for loan losses and net charge offs (NCOs)
  • Model regulatory constraints and analyze effects on leverage, capital ratios, and profitability
  • Forecast net interest income (NII), asset yields, funding costs and interest earning assets (IEA) and liabilities (IBL) using an approach that takes into account typical disclosure gaps, is internally consistent, and avoids common modeling pitfalls
  • Learn common forecast approaches for the non-interest income and expenses such as fees, and compensation
  • Identify the most appropriate “plugs” in a bank model to ensure the model balances, and address circular reference issues in the model

Section Two: Building a bank valuation model

  • Using the results derived from the forecast model, build a residual (excess returns) income model
  • Build an adjusted dividend discount model using the prevailing beset practices for banks (not the same as non-banks)
  • Analyze how regulatory capital constraints effect valuation
  • Develop assumptions about return on equity (ROE), risk weight assets (RWA), cost of equity, and minimal capital ratio that are internally consistent for a multiple stage model
  • Compare the other valuation approaches such as comps and DCF and identify strengths and limitations of each approach

Additional recognition

This program is eligible for 35 PD credit hours as granted by CFA Institute.


The course is self-paced and anyone is welcome to enroll. It does not assume a prior background in Bank and FIG Modeling. However, those who select this course should possess knowledge in:

  • Accounting: The program assumes a basic introductory knowledge of accounting (e.g. interaction of balance sheet, cash flow, and income statement). Students with no prior background in Accounting should take the Accounting Crash Course (included in this package).
  • Corporate Finance: Although general exposure to corporate finance is helpful, it is not required.
  • Excel: Basic introductory Excel knowledge is highly recommended. Students with limited or no experience using Excel should take the Excel Crash Course (included in this package)