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Asset and Liability Management (ALM) Training

Master Dynamic Balance Sheet Optimization and Take Control of Financial Strategy

Learn how to build a mathematical model optimization model for balance sheet management — empowering you to tackle critical financial decisions prospectively and holistically, across multiple scenarios at once.

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What You’ll Learn?

Project the Balance Sheet

Simulate future balance sheet structures in a coordinated and automated framework.

Forecast the Income Statement

Model key income drivers while ensuring consistency with balance sheet projections.

Optimize Funding Strategies

Design and implement funding strategies that align with risk and return objectives.

Enhance Liquidity Management

Develop a systematic approach to maintaining liquidity resilience under different scenarios.

Optimize IRRBB Management

Integrate interest rate risk management into a coherent and automated decision-making process.

Run Integrated Stress Tests

Assess risk exposure dynamically, ensuring all components interact consistently under stress.

The Most Hands-On ALM Training on the Market!

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On-Demand Videos

Learn at your own pace with high-quality, structured lessons available anytime.

All Code Available

Get full access to the model’s source code to practice, modify, and apply.

Lifetime Access

Revisit course materials anytime to reinforce learning and stay ahead.

Hands-On

Build and work directly with real ALM & optimization models for practical mastery.

One-On-One Sessions

Get personalized guidance to deepen your understanding and solve challenges.

Networking

Connect with peers and industry experts to exchange insights and grow your network.

Who should attend this course?

Treasury Managers

Optimize funding, liquidity, and balance sheet strategies with data-driven insights.

FP&A Managers

Improve financial planning with scenario-based balance sheet and income forecasting.

ALM & IRRBB Modelers

Build advanced models to manage interest rate risk and optimize financial decisions.

Risk Managers

Strengthen risk management frameworks with integrated stress testing and sensitivity analysis.

ALCO Members

Make informed strategic decisions with a forward-looking, optimized approach to ALM.

ALM Software Developers

Gain hands-on experience building sophisticated ALM and optimization tools.

Consultors

Enhance strategic decision-making by mastering ALM to optimize risk management, liquidity, and balance sheet efficiency.

Banking professionals

Improve risk management and regulatory compliance by mastering ALM to optimize balance sheet strategies and interest rate risk.

Auditors

Strengthen risk assessment and regulatory oversight by mastering ALM to evaluate balance sheet stability and interest rate risk exposure.

Certificate

Boost Your Career with Our Exclusive Certificate

Showcase your expertise in Treasury and ALM with a certificate that highlights your hands-on skills and deep understanding of balance sheet optimization.

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Meet our instructors

Lucas Processi

Author of "ALM & Balance Sheet Optimization - A Mathematical Approach to Banking"

Lucas Processi is an engineer and financial expert specializing in market risk management and balance sheet optimization. He holds a Bachelor’s in Production Engineering from UFF and a Master’s in Economics and Finance from FGV. As a market risk manager at BNDES and a co-founder of Financial Risk Academy, Lucas shares his expertise in ALM, financial instrument pricing, and quantitative finance. His extensive experience in the banking sector also includes consulting on software development and mathematical programming, with a focus on balance sheet optimization.

Diogo Gobira

Author of "ALM & Balance Sheet Optimization - A Mathematical Approach to Banking"

Diogo Gobira is a finance professional and entrepreneur with deep expertise in ALM and balance sheet optimization. He holds a Master of Science in Mathematical Finance from IMPA and has worked as a Market Risk and Quantitative Modelling Manager at BNDES. Diogo is proficient in areas like portfolio optimization, IRRBB, FTP, and integrated risk management, with a focus on practical applications in balance sheet management. He co-founded Financial Risk Academy, specializing in advanced training and consulting for ALM and balance sheet optimization. Diogo also teaches Strategic ALM in the BTRM Certification.

Learn from the Authors of a Landmark Book

ALM Modeling & Balance Sheet Optimization

This course is taught by Diogo Gobira and Lucas Processi, authors of ALM Modeling & Balance Sheet Optimization – A Mathematical Approach to Banking, part of the prestigious Moorad Choudhry Global Banking Series.

“A marvellous and practically valuable exposition of the asset-liability management discipline in sound, and robust, scientific terms. A most welcome addition to the financial markets literature, deserving of the widest possible readership. Bravo!”

Professor Moorad Choudhry, Author, The Principles of Banking
Buy a copy
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Course Objectives

Strategic Asset-Liability Management (ALM) can improve banks performance, but its implementation is far from trivial. This advanced program will teach you how to create a balance optimization model using dynamic programming and showcase its power with various concrete examples in liquidity management and capital optimization tasks, financial statement and funding mix projections, funding and hedging instrument-level prescriptions, and more.

Course Syllabus

1

Week 1: Introduction

We begin the course by contextualizing the role of a modern treasury in banks and explaining how the imperatives of the Strategic ALM concept naturally emerge as a response to the problems of lack of coordination between assets and liabilities. Finally, we discuss how Mathematical Optimization can assist in the practical implementation of such concepts.

2

Week 2: ALM Model Architecture

In this module, we take a first overview exploring the main layers of an ALM and balance sheet optimization solution, highlighting the main challenges in implementing each of them. We will have a first, still conceptual, contact with the main inputs of the model, ETLs, contract modeling, reconciliation, and mathematical modeling. Finally, we briefly discuss optimization processes, reporting, and data integration.

3

Week 3: Mathematical Programming

In this module, students will have their first contact with code examples to recapitulate and apply the main concepts of mathematical programming and optimization. In particular, we will explore examples of use in asset management areas, cash flow matching, OTC procurement, and finally some introductory examples of dynamic programming under uncertainty that will help lay the foundation for the balance model.

4

Week 4: Contract Modeling

In this module, we will revisit the notions of scenario, trajectories, and contracts, as well as implement a library of functions for calculating prices, accruals, cash flows, as well as risk and sensitivity measures such as DV01, CR01, Delta NII, Delta EVE, etc. Finally, we will have our first contact with liquidity risk measures, which will help us encode LCR-style constraints later in the course.

5

Week 5: ETLs

In this important module, we will show how to extract, transform, and convert ledger account data, contracts, and positions to the internal format of the balance optimization model. Next, we will do the same for different business assumptions, discussing the importance of standardizing and validating data, ensuring that optimization occurs on solid and consistent bases.

6

Week 6: Model Building - Foundations

At this stage, we will create our first balance model! We will define model control and state variables, set up state variable dynamics, add basic accounting rules as well as constraints to calculate the income statement. Next, we will run the model for the very first time to then export our first optimized projections.

7

Week 7: Model Building - Business Rules

Here, we reach the heart of the modeling process. To give realism to the model by adding a wide variety of business rules to the model, such as growth targets, basic assets and liabilities profiling, market limits for investing and issuing, risk targets for IRRBB, DV01, FX, and Liquidity. We'll also discuss how to equip the model with a set of constraints to reconcile optimization with phenomena such as deposits withdrawals, loans lrepayments, loans defaults, and allowance for credit losses and their respective models.

8

Week 8: Reporting and Troubleshooting

In this module, we will discuss how to navigate, export, and transform the raw results of the model to build understandable balance, income, and cash flow statements with different levels of granularity. We will also create reports with optimal prescriptions for funding and hedging strategies, for example. Finally, we will discuss a series of specific troubleshooting strategies for mathematical programming.

9

Week 9: Optimization & Use Cases

With the complete model in hand, we can now discuss specific use cases in investment, funding, hedging, and profitability areas. At this stage, we expect the participation of students who will be called upon to use curiosity and propose debates and challenges.

10

Week 10: Going Stochastic

Now it's time to take a step further by equipping the model with the ability to perform optimizations not only for deterministic trajectories but also under uncertainty. We will show how to code this in Julia and SDDP, how to generate scenarios for the most typical risk factors, as well as create reports and probabilistic projections for different balance and income accounts.

11

Week 11: Final Use Case & Conclusions

To conclude, in this module we will wrap up everything that has been presented, and share what we see as the main trends and challenges in the area of balance optimization, as well as some research topics that can help leverage our knowledge area even further.

Testimonials

I can’t speak highly enough of my experience in taking Diogo and Lucas’ course on ALM modelling balance sheet optimization. I discovered the course through hearing about the book that they had published on the topic, and after a discussion with Diogo I was very excited to sign up.

The course has certainly exceeded my expectations, providing me with not only a stronger understanding of the balance sheet and optimization process but a strong foundation in coding using Julia. The course is very well structured to ensure that students with various levels of experience in balance sheet management, mathematics and coding can follow along. Any time I was faced with a challenge during the course the lecturers were there to assist me. Diogo was even kind enough to take his time to assist me with a financial modelling question that was not directly related to the course material.

Annette Black
Shane Dolan
Senior Manager, Group Treasury - Commonwealth Bank

Diogo Gobira and Lucas Processi have put together a wonderful course presenting a fresh take on ALM and optimization of the balance sheet. I've been taking the course since February.

For too long, the industry has suffered from poorly written software. I honestly believe the material presented in this course will eventually lead to new software in this space. Maybe it will be commercial software. Maybe it will be open source software. It doesn't matter. By taking this course, you'll have a leg up on the rest of the job market when that new software becomes available.

Even if you're not interested in seeing new software for this space, the course is still useful. It takes a dive into the world of ALM from a highly mathematical point-of-view. At minimum, such an approach is sure to broaden your ALM intuition.

Brent Ritterbeck
Brent Ritterbeck
ALM Expert

I joined the course and no doubt in saying that it is one of the best courses in ALM and Balance Sheet Optimization. The course curriculum is very structured and highly practical oriented, codes are very simple and straight forward understand very well.

Diogo and Lucas has worked very hard to streamline the course. It starts from the scratch i.e. after introduction, it covers Model Architecture to Mathematical Programming, to Contracts Modelling to ETL to Model Building then defining Business Rules and finally trouble shooting and report generation.

Given Diogo’s and Lucas’s rich industry experience, they provided us with real-world examples during whole programme. As a risk management professional, I will recommend it to everyone who is working in or interested in building her/his career in ALM, Liquidity Risk, IRRBB and/or Risk Analytics.

Annette Black
Kumar Ravi
Director - Risk Analytics at Solytics Partners

I can’t speak highly enough of my experience in taking Diogo and Lucas’ course on ALM modelling balance sheet optimization. I discovered the course through hearing about the book that they had published on the topic, and after a discussion with Diogo I was very excited to sign up.

The course has certainly exceeded my expectations, providing me with not only a stronger understanding of the balance sheet and optimization process but a strong foundation in coding using Julia. The course is very well structured to ensure that students with various levels of experience in balance sheet management, mathematics and coding can follow along. Any time I was faced with a challenge during the course the lecturers were there to assist me. Diogo was even kind enough to take his time to assist me with a financial modelling question that was not directly related to the course material.

Shane Dolan
Shane Dolan
Senior Manager, Group Treasury - Commonwealth Bank

Diogo Gobira and Lucas Processi have put together a wonderful course presenting a fresh take on ALM and optimization of the balance sheet. I've been taking the course since February.

For too long, the industry has suffered from poorly written software. I honestly believe the material presented in this course will eventually lead to new software in this space. Maybe it will be commercial software. Maybe it will be open source software. It doesn't matter. By taking this course, you'll have a leg up on the rest of the job market when that new software becomes available.

Even if you're not interested in seeing new software for this space, the course is still useful. It takes a dive into the world of ALM from a highly mathematical point-of-view. At minimum, such an approach is sure to broaden your ALM intuition.

Brent Ritterbeck
Brent Ritterbeck
ALM Expert

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The classes are recorded, but live sessions are offered at significant milestones in the course, tailored to each cohort.

Approximately 40 hours of recorded lessons, organized into short and medium-duration videos.

Students have one year of access to the platform to complete the training.

Basic knowledge in finance and an interest in learning programming. Advanced programming knowledge is not required to follow the lessons and use case studies.

All codes used will be provided to students for personal and institutional use. However, distribution to third parties on the internet is not permitted.

Students can ask questions and share with their cohort through the forums in each lesson. For more specific queries, teachers can also be accessed via direct message.

Click me to watch video!
40+

Hands on classes

+20

Pratical examples like IRRBB, Liquidity Risk, Capital Ratios and much more

+300

Students did our ALM courses since 2017

Why ALM is the Key to Your Financial Career?

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ALM: The Core of Every Financial Institution

ALM professionals are essential for managing risk, liquidity, and capital, making them central to the stability and growth of financial institutions.

The Growing Demand for ALM Professionals

The demand for ALM experts has grown by 20% in the last 5 years, with continuous upward trends expected in the coming years.

A Promising Career Path in Financial Strategy

With evolving regulations, ALM professionals are increasingly vital for strategic decisions, often seeing 10-15% salary growth each year.

High Earning Potential in ALM

Senior ALM roles in large banks offer compensation packages ranging from $120,000 to $250,000 annually, reflecting the value of these professionals.

Secure Your Future with a Career in ALM

With job openings for ALM professionals expected to rise by 25% in the next decade, this career offers long-term stability and growth.

ALM Enhances Your Strategic Insight

By mastering ALM, professionals gain a deeper understanding of a company's financial health, positioning them as key contributors to decision-making and long-term success.

Worldwide community

Our students come from all over the world, representing all five continents, diverse cultures, and unique backgrounds. This global community brings a rich exchange of perspectives, making the learning experience even more dynamic and enriching. No matter where you're from, you'll be part of an international network of professionals, all united by a passion for mastering ALM and financial optimization

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Our Articles

Check out some of our articles in the ALM topic and more.

Long-Term Interest Rate Simulations Using PCA and Hidden Markov Models

When dealing with medium- and long-term balance sheet simulations, we need to pay special attention to the scenarios we use to feed the simulations. This is because, over such time horizons, the economy and markets can go through different regimes, which in turn affect not only the levels but also the volatility of risk factors. Thus, it is important to have a scenario generation model capable of representing the existence of such regimes and the probabilities of transitions between them. In my view, one very useful class of models for representing this type of dynamics is the so-called HMM (Hidden Markov Models)..

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Integrating Behavioral Models with Balance Sheet Optimization Models in Banks

In the realm of banking, integrating behavioral models (BMs) with balance sheet optimization (BSO) models represents a sophisticated approach to enhancing financial performance and risk management. This process involves several key components and steps to ensure seamless integration and effective optimization.

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Strategic FTP & Price Optimization - The Last Mile of Hyperpersonalization In Banks

In the last week, I had the opportunity to attend the largest banking technology event in Latin America, called FEBRABAN TECH 2024. The organization was incredible, with numerous booths from banks and vendors of various sizes and niches, and a wide variety of interesting presentations. It became very clear that the buzzword of the moment is hyperpersonalization. In the realm of artificial intelligence, this translates to the use of advanced schemes for grouping "similar" customers, allowing future actions—whether in service, marketing, or sales—to be optimized through increasing customization.

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Strategic FTP :: Implementing Balance Sheet Steering Using an Optimization Model

Strategic ALM concerns the idea of addressing the asset and liability management problem in a bank proactively, influencing the generation of assets and liabilities in a coordinated manner, as opposed to the traditional approach where the ALM unit basically acts after the fact, with the balance sheet format being built somewhat accidentally based on decisions made by different business areas in a silo-oriented approach.

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Balance Sheet Simulation Approaches - A Culinary Metaphor

When we go to a restaurant, we order a dish, and we don't dictate how the dish should be made. Well, there are people who like to order their steak more well-done than recommended by the chef, and almost always, this ends in disaster! So, you might wonder if when managing your treasury, you should take on the role of the customer or the chef.

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Improving IRRBB Management Through a Balance Sheet Optimization Model

At this exact moment, your bank's balance sheet is (almost) still. And this is precisely the greatest deficiency of traditional ALM management tools: staticity. As an ALM manager, when looking at your bank's balance sheet, it should - at least appear to be - moving. In other words, you need to create this optical illusion to understand what lies ahead.

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We offer discounts for self-financed individuals, companies, and group trainings.

Individual (Self-Financed)

We offer a discounted price for self-financed individuals to support their career growth, making our ALM course more accessible.
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Individual (Business)

For company-sponsored individuals, our pricing reflects the added value of professional development, ensuring businesses invest in top-tier ALM training.
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Group Discounts

We offer group discounts to support teams in enhancing their ALM expertise together, making high-quality training more accessible and cost-effective.
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