Banking: how the sector works
how a bank works and makes money: deposits, lending, net interest margin, the balance sheet, regulation (Basel, deposit insurance), and the retail vs corporate vs investment banking split.
This block builds the foundational fluency every banking professional needs before specializing. You will trace how banks originate, fund, and distribute financial products across retail, commercial, and investment banking lines, understanding where value is created and captured. You will map the competitive landscape, from universal banks and neobanks to fintech disruptors and payment networks, and see how power and margin shift across the chain. You will learn the regulatory architecture, Basel III, Dodd-Frank, and their practical compliance demands. Finally, you will master the numbers: market sizes, capital ratios, benchmarks, and the quick calculations bankers run daily. Together these modules give you the vocabulary, structure, and judgment to operate credibly in banking conversations.
What you'll master
- Explain the end-to-end banking value chain from deposit-taking and underwriting to distribution and risk management
- Identify major players, their competitive positioning, and how margin is distributed between incumbents, challengers, and intermediaries
- Interpret core banking regulations and explain what compliance obligations they impose on daily operations
- Perform standard sector calculations such as net interest margin, capital adequacy, and cost-to-income ratio, and run basic due diligence checks
Key terms
Modules
Covers how banks generate profit and the structure of their business across retail, corporate, and investment banking.
Explores the competing players, margin pools, and battles for the customer interface in banking.
Covers the regulators, capital rules, and compliance duties that constrain how banks operate.
Provides the key figures, jargon, and benchmarks used to size and assess banks.
Latest articles
Recent articles from the blog that apply to Banking.
- FinanceKKR flags AI concentration risk: what the credit binge means for bank NPL ratios nowKKR's warning about overexposure to AI-related borrowing is not just a private credit concern. For bank CFOs managing credit portfolios, it reopens a familiar and uncomfortable set of questions about NPL ratios, coverage adequacy, and whether today's cost of risk accurately prices tomorrow's defaults.
- AISR 11-7 still bites, and gradient boosting just made the wound worseSR 11-7 was written for logistic regression, but banks are now deploying gradient boosting, neural networks, and foundation model-powered scoring into production. This piece unpacks what explainability actually means under the guidance, why examiners are pushing harder on it in 2026, and where the governance frameworks genuinely break down.
- Finance$800mn at an $8bn floor: what Airtel Money's London IPO demands from an African fintech CFOAirtel Money is preparing to file prospectus documents for what could be one of London's largest listings in recent years, targeting $800mn in proceeds at a valuation of $8bn to $9bn. The preparation required to reach that point tells CFOs more about IPO readiness than any generic checklist.
- DataThree pipeline design decisions that determine whether your AML model survives its first regulatory examinationMost fintech fraud and KYC/AML pipelines fail not because the models are weak but because the data architecture cannot defend itself under examination. This playbook walks through the design sequence that keeps you compliant, explainable, and operationally credible when regulators arrive.
- FinanceRevolut's dual listing play and what it signals for fintech CFOsRevolut is preparing to list simultaneously in New York and London, a structural choice that reveals as much about equity story architecture as it does about exchange selection. For CFOs in high-growth fintech, the decisions behind that choice are worth studying carefully.
- AIBuilding credit decisioning models that survive fair-lending scrutinyAI-driven credit models can cut decisioning time and expand credit access, but a single fair-lending violation can trigger enforcement actions that dwarf any efficiency gain. This playbook shows banking AI leaders how to build, document, and defend models that hold up when the OCC, CFPB, or DOJ come knocking.