Interview With Jad Abou-Maarouf, Chief Data Officer, Fulton Bank

Interview With Jad Abou-Maarouf, Chief Data Officer, Fulton Bank

Often, when we talk about data we think about the bits and bytes, the aspects of storage, and processes and methods for manipulating that data to provide the value we are looking for. However, it’s easy to forget that behind the data are often people that the data represents. For example, iIn the banking industry, the data represents the savings, expenditures, loans, credit, and operating capital that individuals, companies, and organizations of all types depend on for their daily existence. 

Chief data officers (CDOs), the new must-have role in today’s organizations, know that they must be effective with data to provide benefit to the organization. Savvy CDOs also know that they must be good stewards of that data so that the organization can continue to be a trusted, well-regarded, and valued part of their customer’s daily lives. In recent years, CDOs have had to grapple with aspects of data security, privacy, and transparency. However, the best CDOs know that they also need to consider the many human aspects of data to ensure they have the trust and best interests of their customers in mind.

Jad Abou-Maarouf, Chief Data Officer at Fulton Bank, a regional mid-atlantic bank, shares his insights and experiences on a recent AI Today Podcast episode. He’s also sharing his insights at the upcoming Data for AI Week virtual conference. In an interview for this article, he shares some of his insights into how banks can consider the human side of data.

As a Chief Data Officer, what is the scope of your activities around data collection, data engineering, data governance, and data management?

Jad Abou-Maarouf: I always joke about this and how everyone associates the data office with anything with the word data attached to it! I think that is a great thing but the reality of what we are trying to accomplish is to change the mindset around the ownership of data. We are surrounded by data. We are generating and consuming it at every moment for and through our customers, employees, products, services, interactions etc.

The main scope for me and for my team is to help our colleagues understand the value of the information that they are interacting with. We are working to change the mindset of the people –both the ones who generate data and also those who consume the data insights. At the end of the day, our success is in the evolution of the organization’s culture around data not by building a data pipeline, collecting data or facilitating governance processes but by having a community of people who believe in the importance of the data and its impact on what they do on a daily basis.

In a highly regulated industry such as banking, what can be some of the challenges when it comes to data?

Jad: In a regulated environment, such as the banking industry, change is constant, and much of it comes in the form of new regulations aimed at protecting the customer. With these new regulations, the obstacle to overcome is the constant evolution of the industry and the need for investment to accommodate these changes. On the data side of the business, we have the role of supporting not only the new regulations but we see it as an opportunity to evolve our data practices to support other areas in the business. Recently, many of us in this industry worked to support the implementation of the Current Expected Credit Losses (CECL), a new credit loss accounting standard (model) that was issued by the Financial Accounting Standards Board (FASB).  As we were doing so, we had the opportunity to influence many organizational functions’ mindsets and practices around data. Really, the biggest opportunity in this space is getting ahead of the curve by  anticipating and setting our data processes and capabilities to enable us to respond in a nimble, proactive matter and, in some cases, help shape the future of public policy.

What data considerations need to be in place for AI and ML projects?

Jad: In the world of AI, ML, and Robotics data governance and data quality become table stakes. The speed of moving data and allowing the analytical or robotics models to make decisions becomes exponential and with it comes the speed of making good or bad decisions. With manual processes you had more time to react to quality problems, but as you invest in implementing AI, ML or Robotics, the movement of data and generating of decisions becomes so automated that doesn’t give you the appropriate time to react. This is why it is important to equip your processes with the appropriate controls and governance. Just imagine allowing a person to do free-form entry on loan information without the appropriate validation while, behind the scenes, you invested in placing many robotics processes to optimize the operation. By entering data without validating it first, you enabled and propagated the wrong information across the organizations in a fairly rapid speed. This causes high risk and expensive problems to solve.

One other foundational area is the investment in curating your business domain entities like customer, employees, product, collaterals etc. The more services and processes you can put up front to enrich these critical domains with quality data, the better results to support the training and operation of your ML and AI. These entities are the hubs of your business and with relationships and interactions you will bring them together to life to form your identity as an organization. So if you haven’t begun working on this yet, now is the time to start.

You have some interesting perspectives on the human-side of data. Can you elaborate on this?

Jad: When I talk to HR, for example, we talk not about “employees,” but about “people”  — who have emotions, personal experiences, challenges and evolutions. Companies want to connect with their team members and their customers, to develop a certain level of trust with them. We in the data world want to do the same. We want to impact people’s experience in a positive way. The question then becomes “How can data improve the human experience?” This question applies to both our employees and our customers. With employees, we have to create a data vision to strive for and allow them to evolve. At the same time, we want to provide them with experiences and value from that data by creating mutual respect and relationships worth investing in. On the customer side, the products and services we offer are embedded in their day-to-day life events from the moment they celebrate the birth of a child or new business idea. 

From that day forward, the difference we make on their emotions, experiences and being there when they need us will make a difference that would directly impact them. The support of data should go beyond informing and supporting the customer’s journey through their digital experience to understanding the customers physiographic profiles, enabling our employees to focus the moments they are spending with the customers on building lasting relationships and having the conversations that matter.  Finally, we need to treat the customers’ data as we treat their financial assets, by respecting their data use preferences, educating them on how data is being used based on regulatory requirements or other purposes and empowering them to be in control.

How are you taking a holistic approach to data and focus on people, process, and technology?

Jad: In every transformation journey that I had the opportunity to lead, people always came first;  through data vision, mission and strategy, we worked to  bring them together to evolve and focus on putting the right processes and technology in place to enable our business strategy. The people that you have in your data organization need to be influencers and change agents. They are on a mission to bring the organization along the journey and the discussion always starts with the problems that we need to solve and opportunities to impact our customers and the business.  

What are some interesting insights you’ve discovered when it comes to data in the banking industry?

Jad: What excites me about the data and the insights in the banking industry is the level of positive impact we can make on people’s lives. If you think about it, your bank is with you on a daily basis. We have the unique relationship with our customers that allows us to be present in the big moments of their lives such as purchasing a home, buying a new car or even getting groceries .  If you are a business customer, we are with you to hear about your dreams and aspirations and help enable you to make them reality. We strive to make these interactions positive ones. During the Covid-19 pandemic, with many of our activities focused on helping our customers cope financially, we spent a lot of time on the SBA’s Paycheck Protection Program (PPP), loan deferral, mortgage forbearance.  During this time, the most interesting insights I received were through the stories that I heard from my customer-facing colleagues in the front lines.  They shared stories of how through data and insights we enabled them to create moments with their customers; they could focus on having the simple but meaningful conversations to better understand each customer’s unique needs because they had data at their fingertips.

What AI technologies are you most looking forward to in the coming years?

Jad: Beside the AI and ML capabilities that are impacting the customer and employee experience, I am excited about the use of these capabilities in the data and analytics space to help us optimize the work we do in the data world focusing on quality automation, business entities and domain data curation and resolutions, analytics and visualization automation etc. These capabilities are going to enable us to redeploy our resources and investments to new opportunities in the data and analytics space and will allow us to increase the role data plays in the organization and in influencing the human experience.

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