Our new book is out for preorder! We have been working hard to get this book out, and we are thrilled to finally share it with you. While the book comes out in December 2025, you can already go through the labs! Find them here. A preliminary Table of Contents, Figures and Algorithms can be found here.

The book summarizes close to a decade of experience in applying deep learning to banking problems, with a focus on risk management. We are proud to have written a book structured for both academic and professional use. Our target is data scientists developing models, risk managers evaluating them, regulators shaping policy, and graduate students preparing for a career in financial technology. We assume you have a background in data science, but we guide you through the specific nuances of applying deep learning in the high-stakes environment of banking.

What’s Inside?

We wanted to create a single resource that bridges the gap between cutting-edge theory and the practical realities of banking. The book provides:

• A Comprehensive Toolkit: Dive deep into the essential deep learning architectures—from Convolutional Neural Networks (CNNs) for image analysis to Transformers for text and Graph Neural Networks (GNNs) for understanding financial contagion.
• Real-World Case Studies: Each chapter is grounded in practical applications, using real data to demonstrate how these models can be applied to solve core banking challenges like mortgage default prediction, behavioral scoring, and risk analysis. We are proud to have received special permission from Freddie Mac to use their Single Family Loan Dataset for our book. We also use Fed speeches, network data, LiDAR, and a long list of alternative data for the book. All case studies are done on real data, with direct application to banking practice.
• Focus on Trust and Compliance: The book dedicates significant attention to the critical themes of fairness, accountability, explainability, and the ever-evolving regulatory landscape, including frameworks like the EU AI Act and regulators worldwide.
• Hands-On Learning: Every case study is accompanied by language-agnostic algorithms in the book, so it will never go out of fashion, and always up-to-date labs are available on the book’s companion website. This allows you to not just read about the models but to build and experiment with them yourself. You can try these right now!

Our goal was to create the book we wished we had: a single, unified resource that covers the data, the algorithms, and the business environment of AI in financial services. We believe that responsible AI can drive innovation and growth in banking, and this book is designed to give you the tools to build solutions that are safe, profitable, and productive. Interested? Preorder it now!

I was on the CBC News‘ Weekend Business Panel this Saturday, speaking about three topics:

1. The Canada Post Strike: The company is in dismal financial status, with seven years of losses, each year beating the next. The company wants to turn more into an Amazon-like delivery service, with contractors delivering parcels over the weekend, while the union wishes for their members to get paid overtime for these deliveries. Both of these requirements are unrealistic. Canada Post functions in a highly competitive environment, one where labour laws are many times overlooked. A solution must come via rethinking what is as modern post service that reaches rural and urban Canadians, possibly some reforms to the labour code to protect delivery workers across companies and provide a level playing field, and a more lean, efficient post office that delivers services as Canadian need them. Otherwise, the crown corporation is, in my opinion, doomed.

2. The GST holiday and the $200 incentive: This is a terrible policy. At best, it displaces consumption and reduces the fiscal arks with limited economic impact. At worst, it compounds an inflationary environment given the promised increased expenses by the incoming US president. If the latter occurs, then the BoC will react and either stay further rate cuts or, in a more extreme situation, increase the interest rate, eliminating any impact. This is a populist measure that has, sadly, proven quite popular by Doug Ford’s similar measures.

3. The latest inflation numbers: They were squarely in the BoC’s estimates, so nothing serious here. I do believe that the BoC hast to be cautious about the future. Donald Trump’s protectionist and expansionary policies may lead to an even weaker CAD, thus the risk of importing inflation in the future is high. The BoC must be thinking carefully whether they can keep cutting the interest rate or should they wait to see the impact of Trudeau’s, Ford’s and Trump’s policies.

Give it a watch below! This is my last panel of the year. I come back live on January 18th.

I am recruiting up to two new Ph.D. students for entry September 2025. I am running a shorter recruiting cycle this year given the new constraints on international students (Deadline: December 2nd, 2024!). The ad below:

Ph.D. Position in Banking Analytics – Department of Statistical and Actuarial Sciences, Western University

The Banking Analytics Lab at Western University invites applications for a fully funded Ph.D. position focusing on financial contagion in corporate and consumer credit risk. This cutting-edge research project aims to understand and model the interconnected nature of credit risk across different sectors of the economy, with direct applications in banking and financial regulation.

Position Details:
– Full funding guaranteed for four years.
– Annual stipend of CAD$30,000.
– Direct collaboration opportunities with major banks and regulatory bodies.
– Access to unique datasets and computing resources, plus annual funds for travelling and expenses.

The successful candidate will:
– Develop novel methodologies for analyzing financial contagion using deep learning techniques in consumer retail, small business lending, and/or corporate lending.
– Work at the intersection of machine learning, statistics, and banking over real, challenging datasets solving problems at the forefront of modern banking.
– Contribute to both academic research and practical applications.
– Engage with industry partners and regulatory bodies.

Required Qualifications:
– Master’s degree in Statistics, Operations Research, Computer Science, Economics, or related fields.
– Strong quantitative and programming skills. Python programming and knowledge of modern methods (pytorch, polars, spark, arrow, duckdb) is a strong plus.
– Excellent written and verbal communication abilities.
– Demonstrated interest in banking and financial applications.

Application Process:
1. Submit your CV and academic transcripts by December 2nd, 2024 to cbravoro@uwo.ca. Please mention your GRE scores and TOEFL/IELTS or similar tests, if available.
2. Selected candidates will be invited for interviews that same week.
3. Successful interviewees will be invited to submit a formal application to Western University.
4. Final acceptance will be determined by the Graduate Affairs Committee.

To apply or for more information, please contact me at cbravoro@uwo.ca.

The Banking Analytics Lab values diversity and encourages applications from all qualified individuals, including women, members of visible minorities, Indigenous peoples, and persons with disabilities. This position is available to anyone, worldwide.

At least one of these positions will be cosupervised by Dr. María Óskarsdóttir at Southampton University. The job post is below:

https://lnkd.in/gZ92cxaZ