Course Guide
A practical, ready-to-adapt guide for anyone designing or refreshing an Asset Liability Management course. Inside: course positioning, constructively aligned intended learning outcomes, twelve core concepts with teaching notes, a 12-session structure, applied simulations, recommended readings, verified cases and assessment briefs.
teach Asset Liability Management as a named or closely related course
sessions as the most common course-design model
taught at undergraduate level
taught at postgraduate level (levels overlap)
offered as core; the rest elective
include an applied or simulation-based component
Asset Liability Management sits where treasury, risk, banking, fixed income and regulation meet. That makes it an unusually strong course for teaching trade-offs rather than isolated techniques.
How well this course prepares students for six role families, scored out of 10. Indicative, based on how directly the concepts map to each path - not a placement statistic.
Debt Financing is the closest available applied fit. It is mapped to the point where students already understand funding structure, maturity and risk trade-offs, and is positioned explicitly as a financing exercise rather than a dedicated ALM simulation.
This guide is for professors, lecturers, module leaders, unit convenors, instructors of record and programme directors designing or refreshing Asset Liability Management, bank treasury, financial institutions risk, liquidity risk or balance-sheet management teaching. It is globally portable across course, module and unit terminology and can be used as the basis for course ownership, credit approval, intended learning outcomes and assurance-of-learning evidence.
It is best suited to final-year undergraduate, MSc Finance, MSc Banking, MBA, EMBA and executive education cohorts. The course assumes students can read a balance sheet and work with basic time value of money and fixed-income concepts, but it does not require them to arrive with professional treasury systems or advanced stochastic modelling experience.
An Asset Liability Management course teaches students to manage a financial institution as an interdependent balance sheet. The course begins with the ALM mandate and ALCO governance, then moves through repricing and net interest income, duration and economic value, behavioural optionality, liquidity gaps, funding strategy, regulatory buffers, hedging, funds transfer pricing and stress testing before ending with integrated ALCO decision-making. A bank-led structure is the most practical spine, while a dedicated session on insurance and pension ALM broadens the matching logic beyond deposits and loans.
The course is applied because the important outputs are decisions, not definitions. Students should be able to decide whether a funding plan is stable, whether a duration gap is acceptable, whether a hedge solves the right problem, which management action is credible in stress, and how an ALCO should trade near-term earnings against economic value, liquidity, capital and strategic flexibility. The strongest teaching repeatedly distinguishes contractual from behavioural maturity, liquidity from solvency, and model precision from decision quality.
A one-screen planning view for a course-approval form, module descriptor or syllabus refresh. The detailed teaching logic sits in the sections below.
Planning area | Suggested approach |
|---|---|
Best fit | Final-year undergraduate, MSc Finance or Banking, MBA, EMBA and executive education. It also fits specialist bank treasury, financial risk management and financial institutions courses. |
Typical length | 10, 12 or 14 teaching sessions, with 12 as the standard model. Roughly 24-36 contact hours plus independent preparation and assessment, producing about 150-180 notional learning hours in a full semester elective. |
Course role | Usually a specialist elective or advanced unit within banking, finance, treasury or risk management. It can also serve as an integrative capstone where students must reconcile multiple balance-sheet constraints. |
Useful prerequisites | Introductory finance, financial statements, time value of money and basic fixed income. A short refresher on bonds, duration and bank balance sheets is enough for mixed cohorts. |
Main student output | An ALCO recommendation supported by NII and EVE analysis, a liquidity and funding plan, stress results, hedge logic and explicit assumptions. |
Best assessment fit | One group applied output carrying most of the summative weight plus an individual assumptions note, reflection or short oral defence that produces attributable evidence. Most courses use two assessment points rather than every format listed below. |
Best simulation fit | Debt Financing after funding strategy and liability design. It is the closest available fit because students negotiate pricing, maturity, repayment, seniority, security and covenants, but it should be described as applied financing rather than dedicated ALM. |
These intended learning outcomes use assessable verbs and constructive alignment: each is tied to a calculation, memo, committee decision or defence that can produce evidence for course review. Bloom's taxonomy is used once as a design check, with most credit placed on analysis, evaluation and defensible judgement rather than recall.
Outcomes 1 and 2 establish the vocabulary and balance-sheet map. Outcomes 3 to 9 build the analytical toolkit. Outcome 10 is the integrative capability and should carry substantial assessment weight.
The sequence reflects patterns commonly seen in Ivy League and leading global business-school courses on banking, financial institutions, fixed income, risk management and closely related finance modules. It is a course-design pattern rather than a claim that every leading school teaches ALM in the same way: establish the balance-sheet foundations, build the measurement tools, move into funding and hedging decisions, then close with stress, governance and integration.
There are twelve core concepts in this Asset Liability Management course:
Each concept is written for lecturers and includes the central teaching question, suggested coverage, assessable outcomes, a runnable case-style example with figures, likely student difficulty, a quick check and an accurate note on where an applied simulation or alternative teaching activity fits.
The alignment map below follows the balance-sheet decision cycle rather than treating ALM as a collection of independent ratios. Each stage produces formative evidence that can later be assembled into the summative ALCO decision.
Stage of ALM work | Principal concepts | Expected student output |
|---|---|---|
Set the ALM mandate | ALM scope, balance-sheet economics and ALCO governance (1) | Balance-sheet map, risk appetite and committee decision rights |
Measure rate exposure | Repricing, NII, duration, EVE and behavioural optionality (2-4) | NII and EVE shock pack with an assumptions note |
Secure liquidity and funding | Liquidity ladders, survival horizon, deposits and wholesale funding (5-6) | Liquidity dashboard and funding plan |
Work inside constraints | LCR, NSFR, capital, leverage and risk appetite (7) | Buffer and capacity decision note |
Transform and price risk | Hedging, FTP and product economics (8-9) | Hedge recommendation and product pricing memo |
Test resilience | Stress testing, contingency funding and recovery actions (10) | Scenario results, management actions and trigger framework |
Extend matching logic | Insurance, pensions and LDI (11) | Liability-matching recommendation with collateral plan |
Make the integrated decision | ALCO governance, model risk and board communication (12) | Summative ALCO memo plus individual oral or assumptions defence |
Models support balance-sheet judgement. They do not make the ALCO decision. Credit the quality of assumptions, recognition of missing information, treatment of second-order effects and ability to explain why the recommendation would change under a different scenario.
The architecture works across final-year undergraduate, MSc, MBA and executive education. What changes is scaffolding, data completeness and tolerance for ambiguity. Do not remove duration, liquidity or behavioural assumptions simply because they look advanced. Instead, simplify the dataset for undergraduates and increase the decision ambiguity for postgraduate cohorts.
At undergraduate level, students should see the mechanics and the direction of effects. At MSc, MBA and executive level, they should defend modelling choices, handle contradictory metrics and decide what the committee should do when no option is dominant. The same 24-36 contact-hour structure can therefore serve multiple levels while notional hours, reading load and independent modelling are adjusted locally.
Course design area | Undergraduate version | Postgraduate / MBA / executive version |
|---|---|---|
Course emphasis | Build the bank balance sheet, repricing, duration, liquidity and funding logic clearly before asking for integration. | Move faster into behavioural assumptions, multi-factor stress, hedging policy, model risk and committee challenge. |
Quantitative depth | Use transparent gap, duration, EVE and liquidity calculations with supplied data. | Use fuller scenario sets, curve shocks, optionality, DV01, transfer-pricing and sensitivity analysis. |
Scaffolding | Provide templates for gap tables, ALCO memos and stress dashboards. | Provide incomplete evidence and require students to decide what needs verification. |
Regulation | Teach the purpose and interaction of LCR, NSFR and capital buffers. | Add jurisdictional implementation, management buffers, outlier tests and supervisory challenge. |
Cross-sector ALM | Use one pension or insurer example to illustrate matching. | Add collateral liquidity, LDI leverage, solvency constraints and model governance. |
Student activity | Guided calculations, short committee exercises and structured cases. | Open-ended ALCO packs, simulation debriefs, model defence and board-style challenge. |
Assessment | Reward correct concept use, transparent calculations and clear explanation. | Reward judgement quality, assumption defence, trade-off analysis and response to challenge. |
Simulation use | Use Debt Financing as a guided liability-structure exercise after the funding topic. | Use the same activity as evidence for a funding memo, then require students to translate financing terms into ALM implications. |
The sequence follows a balance-sheet lifecycle: define the mandate, measure interest-rate exposure, model behaviour, secure liquidity and funding, work within regulatory constraints, hedge and price risk, test resilience, then make an integrated ALCO decision. The design can be taught weekly, in intensive blocks or in blended format.
The design principle worth keeping if you change nothing else: every session should leave a markable output. That makes the final ALCO recommendation an assembly of prior work rather than a sudden capstone disconnected from the teaching.
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Indicative 12-session Asset Liability Management course arc. Use alongside the detailed syllabus table below.
Session | Topic | Teaching focus | Student activity | Best-fitting simulation, where relevant | Assessment or output |
|---|---|---|---|---|---|
1 | ALM foundations and ALCO governance | Map the bank balance sheet, maturity transformation, profitability, risk appetite and committee governance. | Students build a balance-sheet risk map and write three proposed ALCO limits. | Risk map and ALCO mandate note. | |
2 | Yield curve, repricing gaps and NII | Measure rate-sensitive assets and liabilities, deposit beta, basis risk and one-year earnings sensitivity. | Teams build a repricing ladder and test two curve shocks. | NII sensitivity pack with assumptions. | |
3 | Duration, convexity and EVE | Move from earnings to economic value using duration gap, DV01 and EVE sensitivity. | Students calculate a simplified duration gap and compare NII versus EVE signals. | EVE shock note and hedge question. | |
4 | Behavioural optionality and deposits | Model non-maturity deposits, deposit beta, decay, prepayment and embedded options. | Students compare three behavioural models and recommend an overlay. | Behavioural assumption governance note. | |
5 | Liquidity risk and survival horizon | Build cash-flow ladders, assess HQLA, haircuts, collateral and usable liquidity. | Teams calculate a 30-day cumulative gap and survival horizon under stress. | Liquidity dashboard and action list. | |
6 | Funding strategy and liability design | Compare deposit, secured and unsecured wholesale funding, maturity, pricing and concentration. | Students design a funding plan, then negotiate the financing package in an applied exercise. | Funding strategy memo and simulation debrief. | |
7 | LCR, NSFR, capital and leverage constraints | Show how prudential ratios and management buffers constrain growth and ALM actions. | Students compare three balance-sheet actions against multiple buffers. | Buffer and capacity decision note. | |
8 | Interest-rate hedging and securities | Use swaps, securities and natural hedges to reshape NII and EVE exposure, with basis and collateral risk. | Teams size a simple hedge and explain residual risks. | Hedge recommendation. | |
9 | Funds transfer pricing and product economics | Allocate term, liquidity and optionality costs back to business lines and product pricing. | Students reprice a loan using matched-maturity FTP and a liquidity premium. | Product pricing and profitability note. | |
10 | Stress testing and contingency funding | Combine rates, deposit outflows, market haircuts and capital pressure; test management actions. | Teams run an integrated stress and build a contingency response sequence. | Stress report and contingency funding plan. | |
11 | Insurance, pension ALM and LDI | Extend duration matching, immunisation and collateral liquidity to long-dated liabilities. | Students design a matching strategy for a pension or insurer case. | Liability-matching recommendation. | |
12 | Integrated ALCO capstone | Bring NII, EVE, liquidity, funding, capital, FTP, stress and model risk into one committee decision. | Teams defend a board-ready recommendation and identify reversal triggers. | Summative ALCO memo plus individual defence. |
Asset Liability Management is a decision-led subject. Students can learn repricing gaps, duration, LCR, funding concentration and hedging mechanics from lectures and models, but the discipline becomes real when they must commit to a funding or risk decision with competing objectives and incomplete information.
There is no dedicated bank or insurance ALM simulation in the current Finsimco portfolio. The strongest available fit is Debt Financing because it turns liability structure into a negotiated package of amount, pricing, maturity, repayment, seniority, security and covenants. Use it narrowly and honestly: as an applied financing exercise within the funding part of the course, followed by an ALM debrief that translates the agreed terms into maturity, liquidity and balance-sheet implications.
There is also an accreditation argument for applied work. Experiential learning can provide evidence that students can apply and evaluate rather than only recall. The platform records what each team decided, the terms they agreed and comparative outcomes across groups. That evidence supports your academic judgement; it does not replace it, and it does not establish which individual student made which argument.
If you need the accreditation language itself, what AACSB and AMBA say about simulations sets it out.
Teaching format | What it does well | Limitation | Best use in this course |
|---|---|---|---|
Traditional case study | Provides a rich balance-sheet situation, exhibits and a defined decision question. | Students can discuss the answer without committing to a live counterparty position. | Best for IRRBB, liquidity stress, LDI, model assumptions and ALCO governance. |
Simulation | Places students in roles where they must analyse evidence, negotiate terms and commit to a complete financing package. | The available simulation is financing-focused, not a direct model of bank or insurance ALM. | Best after funding strategy, where the lecturer can debrief maturity, pricing, protection and liability structure. |
For this course, use one simulation well rather than forcing several weak fits. Debt Financing belongs after students understand funding stability, maturity, pricing and concentration, and before they move fully into regulatory constraints and hedge design.
Course point | Simulation | How to use it | Why it fits |
|---|---|---|---|
After Session 6: funding strategy and liability design | Run it as the applied financing exercise, then require students to translate the negotiated package into funding, maturity and resilience implications. | Students must balance amount, pricing, maturity, repayment, seniority, security, guarantees and covenants as one package, which is close to the liability-side trade-offs ALM must govern. |
AI can accelerate first drafts of gap tables, duration explanations, regulatory summaries, hedge ratios, stress scenarios and ALCO memos. That makes surface polish less useful as an assessment signal. In ALM, the most defensible response is to move credit toward data selection, assumptions, model limitations, scenario coherence, management-action feasibility and the ability to defend a decision under questioning.
A practical permitted-use policy is clearer than a vague ban: students may use AI for structure, coding assistance, checking and drafting where local rules allow it, but use must be declared; data and regulatory claims must be verified against approved sources; and students remain responsible for every assumption and recommendation. A model, memo or dashboard that the student cannot explain should not receive the same credit as work they can defend.
The strongest teaching opportunity is model risk. AI makes it easier to create plausible outputs and therefore more important to ask who chose the behavioural assumptions, what evidence supports them and what happens outside the modelled range. ALM is well suited to assessment designs where students are asked to defend a live recommendation rather than submit a polished document in isolation.
Teaching area | AI implication | Lecturer response |
|---|---|---|
Gap and duration models | AI can write formulas and explain duration mechanics quickly. | Require students to validate cash-flow buckets, conventions and sign logic, then defend the model under a changed assumption. |
Deposit behaviour | AI can suggest deposit betas or decay assumptions without evidence. | Require a source, back-test logic, regime explanation and an explicit uncertainty range. |
Liquidity stress | AI can produce generic stress scenarios. | Credit internally coherent scenarios, time-to-cash and management-action feasibility rather than severity words. |
Regulation | AI can summarise Basel or EBA text but may mix dates, jurisdictions or standards. | Require students to cite the current primary source and state what is global standard versus local implementation. |
Hedging | AI can calculate a hedge ratio but may ignore basis, collateral or accounting. | Assess the hedge objective, residual risk and liquidity consequence. |
ALCO memos | AI can draft polished committee papers. | Shift credit toward assumption choice, missing evidence, live defence, reversal triggers and decision logs. |
Core textbook: Bank Asset and Liability Management, The Hong Kong Institute of Bankers, Wiley, 2018. This is the closest single-textbook fit because it is organised around profitability, ALCO, balance-sheet management, liquidity and interest-rate risk rather than treating ALM as a short chapter inside a general investments text.
Alternative textbook: The Principles of Banking, 2nd edition, Moorad Choudhry, Wiley, 2022. This is broader and more current, making it useful when the course sits inside bank management, treasury, risk or financial institutions teaching.
The twelve fictional cases in the Concept Details are licence-free seminar exercises with enough data to run as written. For a longer assessed case or current institutional context, use these two verified real cases.
Bank ALM case
Board of Governors of the Federal Reserve System, 2023.
Why it fits: Use for interest-rate risk, securities duration, deposit concentration, liquidity stress, hedge decisions and governance.
Best placement: Best after Sessions 4-5 or as the integrated stress case in Session 10.
Assessment fit: ALCO post-mortem, risk-limit redesign or individual memo on which management action should have happened earlier.
Pension / LDI case
Gabor Pinter, Bank of England Staff Working Paper No. 1,019, 2023.
Why it fits: Use for liability-driven investment, repo and swap exposures, collateral calls, forced gilt sales and market-liquidity feedback loops.
Best placement: Best in Session 11.
Assessment fit: Liability-matching recommendation, collateral buffer design or board note on how to retain the hedge while reducing liquidity fragility.
Best placement: Session 3, after students have already built a repricing ladder and before behavioural optionality is taught in depth.
Session aim: move students from calculating rate sensitivity to making one defensible ALCO decision while recognising that NII and EVE can point in different directions.
Session stage | Time | Teaching purpose | Lecturer approach | Student output |
|---|---|---|---|---|
Pre-class preparation | Before class | Give students the minimum technical base before class time is used for judgement. | Assign the core textbook IRR chapter, a one-page duration refresher and a simplified balance sheet. | One-page note identifying two NII risks and two EVE risks. |
Opening frame | 10 minutes | Set the central question: what does a +150bp shock do to earnings and economic value? | Introduce the bank, its funding mix and the ALCO decision that follows the analysis. | Students state their initial directional view. |
Mini-lecture | 20 minutes | Connect repricing, deposit beta, duration and EVE. | Review repricing buckets, NII sensitivity, modified duration, DV01 and EVE at a conceptual level. | Students can distinguish one-year earnings risk from full-horizon value risk. |
Repricing analysis | 25 minutes | Move from definitions to a first earnings estimate. | Teams build the cumulative gap and test deposit beta at 30% and 60%. | NII shock range with two assumptions. |
Duration and EVE analysis | 30 minutes | Show why the same balance sheet can look different under a value lens. | Provide asset and liability duration, then require a duration-gap and approximate EVE calculation. | EVE sensitivity and explanation of the main driver. |
ALCO challenge | 30 minutes | Force a decision rather than a calculation dump. | Teams choose one action: hedge with swaps, extend funding, shorten asset duration or accept the exposure within limits. | Three-slide ALCO recommendation with one rejected alternative. |
Committee defence | 25 minutes | Test whether students can defend assumptions under pressure. | Challenge the deposit beta, duration assumption, hedge objective and residual liquidity risk. | Oral defence and revised recommendation if needed. |
Debrief | 20 minutes | Connect outputs to the course language. | Ask which metric changed the decision, which assumption was most fragile and what evidence would change the hedge. | Individual reflection on the difference between model output and ALCO judgement. |
Why this session matters: it is the moment students stop seeing Asset Liability Management as a set of independent formulas. They see that the same rate move can improve near-term earnings, damage economic value and change the best hedge depending on assumptions about deposits and the management horizon.
Because the intended learning outcomes reward judgement rather than recall, assessment should ask students to recommend and defend rather than describe. A common defensible design is a group applied output carrying most of the summative weight plus an individual component that creates attributable evidence, subject to local regulations and moderation practice.
Publish criteria that explicitly reward assumption quality, identification of missing information, treatment of downside and recognition of model limits. If the course uses group work, create individual evidence through an assumptions note, reflection or oral defence so free-riding is visible before marks are challenged. The eight formats below are a menu, not a requirement to use all eight.
Assessment format | How it works |
|---|---|
ALCO recommendation memo | Teams analyse a balance-sheet pack and recommend actions across NII, EVE, liquidity, funding and capital. |
Repricing and NII model plus assumptions note | Students build or interpret a gap model, then defend deposit beta, repricing and growth assumptions. |
Duration and EVE risk report | Students calculate duration gap and EVE sensitivity and recommend whether the exposure should be hedged or retained. |
Liquidity and funding plan | Students build a cash-flow ladder, survival horizon and funding-diversification plan with explicit trigger points. |
FTP and product-pricing note | Students decompose product margin using matched-maturity FTP and explain how liquidity or optionality costs change the commercial decision. |
Stress test and contingency funding plan | Students design a coherent stress, identify the first binding constraint and prioritise executable management actions. |
Cross-sector ALM case | Students design a simplified asset-liability matching strategy for an insurer or pension scheme and address collateral liquidity. |
Individual oral defence | A 10-15 minute viva in which students defend assumptions, explain model limits and identify what would change their recommendation. |
The strongest ALM courses repeatedly ask students to reconcile earnings, value, liquidity, funding and capital under uncertainty. The table below highlights design choices that weaken that integration and the better approach for each.
Common mistake | Why it weakens the course | Better approach |
|---|---|---|
Turning ALM into a ratio course | Students can define LCR, duration and gap measures without learning how to make a balance-sheet decision. | Require every technical topic to end in an ALCO action, limit choice or recommendation. |
Teaching only NII sensitivity | Students miss economic-value risk in long-dated fixed-rate assets and liabilities. | Use NII and EVE together and ask why they can move in opposite directions. |
Using contractual maturity for behavioural products | Non-maturity deposits and prepayments make the balance sheet look more stable than it may be. | Teach deposit beta, decay, core balances, prepayment and model uncertainty explicitly. |
Treating liquidity and solvency as separate worlds | The 2023 banking failures show how unrealised losses, runnable funding and usable liquidity can interact. | Use combined scenarios that connect market value, funding outflows and capital headroom. |
Teaching LCR and NSFR as definitions | Students memorise ratios without seeing how they constrain growth, funding and buffers. | Give them a proposed balance-sheet action and ask which constraint binds first. |
Assuming a hedge removes risk | Students ignore basis, collateral, counterparty, accounting and liquidity effects. | Require a residual-risk statement and collateral plan with every hedge recommendation. |
Using one average cost of funds | Product profitability is distorted and business lines can receive hidden term or liquidity subsidies. | Introduce matched-maturity FTP and make students trace the effect into pricing decisions. |
Stress testing without management actions | The scenario becomes a numerical spectacle rather than a decision process. | Score the feasibility, timing and signalling cost of each management action. |
Forcing simulations into weak topics | Students may remember the game but not the ALM mechanism. | Use Debt Financing only where liability structure genuinely fits, and use cases or models elsewhere. |
Assessing only the polished group memo | AI use and free-riding can make the artefact a weak signal of individual learning. | Add an assumptions note, sampled oral defence or live ALCO challenge that produces individual evidence. |
For banking systems, financial intermediation, market structure, regulation and the institutional context around balance-sheet management.
For market, credit, liquidity and enterprise risk frameworks that connect directly to ALM measurement, limits and governance.
For yield curves, duration, convexity, bond valuation and interest-rate risk concepts used throughout Asset Liability Management.
For capital structure, funding choices, debt capacity and firm-level financing decisions that complement the liability side of ALM.
Use after funding strategy to apply pricing, maturity, repayment, covenant and financing-structure trade-offs.
Use selectively for asset-side risk analysis, diversification and return-risk trade-offs that complement the course's balance-sheet perspective.
Use these options to explore the teaching materials, speak with the team, or see how the simulations would fit into your course.
Start
A practical introduction for lecturers running a simulation for the first time.
Operate
See the lecturer workflow for setup, delivery, dashboards, debriefs and student support.
During the call, we can: