In this interview, Professor Saud Almahdi shares how he has applied analytics throughout his career, from his research in financial engineering to his work at Wells Fargo, and what students can expect from the USC Master of Science in Applied Analytics program.
Among the topics discussed are:
– How analytics supports portfolio optimization and data-driven decision-making in finance.
– The growing role of AI and reinforcement learning in financial applications.
– How MSAA students learn to approach complex business challenges through an analytics lens.
At what point did you realize you preferred applied analytics over other areas of finance?
I first became interested in applied analytics when I was pursuing my Master’s in Financial Engineering. I learned about applied analytics in the financial field, more specifically, its application in financial markets. When I started my PhD, machine learning was a very hot research topic. When I was looking for a research topic, the application of machine learning in finance triggered my interest. That is when I decided to focus on the applied analytics area.
How have you been able to apply your research to your work at Wells Fargo?
At Wells Fargo, I worked on developing the backtesting algorithm and software program. My PhD training helped me a lot with the ability to understand the algorithm that was used at the time, improve on it, and extend it to other asset classes.
How have your graduate degrees helped you succeed?
Developing my collaboration and critical thinking skills has definitely helped. For example, I was assigned to a research project with a team to investigate how machine learning algorithms could be applied to option pricing. It was a great collaborative effort that included a lot of research. The team was split into smaller groups, where each group was responsible for researching an area and presenting the findings to the rest of the team. Additionally, on a day-to-day basis, we have the ‘business as usual’ tasks, and we have other ad hoc tasks. Most of the ad hoc requests are problems that require critical thinking to solve.
How have you observed applied analytics improve decision-making in finance?
One example is in portfolio management. In portfolio management, there are many approaches to optimizing the portfolio weight selection and rebalancing. That optimization is heavily dependent on applied analytics, where we have to use historical data to optimize and rebalance our portfolio. An example would be the mean-variance portfolio optimization method. It is a classical approach that depends on analytics and optimization.
With strong analytics, we can make an informed decision and use empirical evidence. Without analytics, the decision-making process would heavily rely on personal opinions, which is not efficient and might not be feasible if the problem is new.
What is one of the most memorable projects you have worked on?
I would say my research paper during my PhD, where I focused on reinforcement learning for portfolio optimization, is one of the most memorable projects I’ve worked on. I was working on two parts that I was passionate about: AI and decision support systems.
Where does applied analytics create the greatest value in financial institutions today? How do you see the intersection of applied analytics and finance evolving?
I think applied analytics is critical for the financial sector. As dependency on data increases, so does the need for quantitative models to explain the decision-making process. Currently, in the financial sector, applied analytics is having an impact on quantitative and qualitative models. I think this will continue to evolve as our data expands. The decision-making process will be heavily supported by applied analytics. If we look at the number of Fintech companies, we can see that the use of applied analytics keeps increasing as data science, analytics, and technology are expanding into financial applications, and I think this is very exciting.
What skills do you think are necessary for students aspiring to enter the fields of applied
analytics and AI?
I think software development and some statistics can go a long way. But also being able to keep up with the latest trends in the field is crucial. Willingness to learn and keeping an open mind are essential.
What can students expect from your classes?
In my courses, I try to encourage students to have discussions about actual business problems and how to approach them from an applied analytics perspective. We usually discuss problems that are within their domain of knowledge and expertise. I hope that through my classes, students can develop a thinking process where they approach a business problem from an analytics perspective, factor in their domain knowledge, and create innovative solutions.
Can you share a piece of advice that has been particularly valuable to you throughout your career?
Specializing in one topic is better than having general knowledge about many topics. Once you have specialized in one area for some time, you can switch and learn something new.
What do you enjoy doing outside of work?
I like to travel and see new places and landmarks. I like playing different sports even when I am not particularly good at them.
Learn more about Professor Almahdi on his faculty page.
Learn more about the online MS in Applied Analytics program.