Gregory Brooks was recently named vice president of business intelligence for BankNewport. He previously served as assistant vice president of business intelligence for the bank for three years. He has a bachelor’s degree in computer information science and accounting from Rhode Island College and an MBA from Worcester Polytechnic Institute.
PBN: What are your top three priorities for enhancing data science and artificial intelligence for BankNewport?
BROOKS: One of BankNewport’s top priorities is to continue to create a data-driven culture. This requires decision-makers and their teams to change the way they approach problems and develop strategies. Groups with subject matter experts who are knowledgeable in their fields but also possess the skills to analyze data and derive insights have the most success. This decentralized model is becoming easier to achieve with the significant advancements data analysis tools have made. Teams can ask the right questions, arrive at answers faster and ultimately determine if the problem may be something more suited for a data science initiative.
The bank’s second priority is to continue to build out our data warehouse/lake. The amount of data produced every day is staggering, but capturing it all is of utmost importance. We try our best to understand, capture and catalog all of the data feeds that are available to us. The more data points available to inform our decision, the better.
Our third priority is focused on evaluating opportunities across the bank to determine where to spend our time and resources. The investment required for some initiatives forces us to be selective and only focus on those with the most significant benefit.
PBN: How has data analytics and AI changed the banking experience on the back end? What about for customers?
BROOKS: In the back-office automation, software and reporting enhancements have been made to reduce manual touch points and monitoring efforts. A bank can significantly reduce its risk of exposure by gaining a deeper understanding of its current and potential customers using big data and analytics.
From a customer standpoint, the bank is able to provide better service on all fronts. Machine-learning capabilities can be used to identify when a customer is unhappy or may have had a negative experience and can correct an issue. Customers benefit from enhanced fraud alerting and account safeguards that AI enables.
PBN: What are the biggest challenges facing banks regarding data analytics and AI?
BROOKS: For those starting out, the task of creating and funding a data analytics program may appear confusing and challenging. There is no one-size-fits-all approach. Careful consideration regarding resources and the challenges you are trying to solve should be determined first. Starting small and building on quick wins helps to build trust in the insights and in the investment of others.
Today, the data analytics and AI space have become very crowded with hundreds of vendors competing for business. It is more important than ever to vet each potential solution to make sure it delivers on what is promised and that they are the right partner for you.
In the banking space, data sensitivity is another significant factor. Customers provide personal information that must be protected. As we begin to explore and understand more about the customer, the goal is to provide quality services and products that are best suited for their needs.
The last challenge for many financial institutions is to leverage the insights derived yet remain in compliance. The ultimate goal of any model focused on customer acquisition or cross-sell is to determine the best opportunity. We must take the output and ensure that we are providing everyone with equal opportunities and offers.
PBN: How has/will BankNewport’s investment in data science and AI give it a leg up on competitors?
BROOKS: Many financial institutions today are working towards the same goals, among them increasing deposits, strengthening customer relationships to acquire new business, streamlining operations and reducing risk exposure. By leveraging advanced analytics and AI, BankNewport hopes to identify opportunities that would not have been visible otherwise and gain a better understanding of why, in turn increasing the return of every dollar that we spend.
I believe, like many other strategic advantages, the gap between the haves and have-nots will close over time. Some of these methodologies will be embedded into tools focused on operations/compliance to enable the use of robotic process automation to reduce decision and processing time. Others will be integrated into customer relationship management to create hyper-targeted promotions and recommendation engines that use transaction and demographic information to look beyond credit scores and assets. Focusing on the data science component will reduce the legwork of developing, testing, deploying and training a model in a production environment.
PBN: What do you think is the biggest misconception when it comes to data and AI in the banking world?
BROOKS: Many will see this as a magic bullet that will be plug and play. As I mentioned previously, an organization needs to adjust the way they think about data and feel comfortable using it to make decisions. Data science is a job for a small group of people. A number of experts have stated that the most successful data science efforts are based on a team approach. Having a strong supporting cast of subject matter experts, data experts and analysts make it all work that much smoother.
The AI field is changing so quickly that continued investment will always be needed. As the “internet of things” continues to develop, more data points will become available, analytics will continue to evolve and businesses should be ready to adapt as required. It is a very fascinating time to be in the field, and I cannot wait to see what is coming down the pike in the next couple of years.
Nancy Lavin is a staff writer for PBN. Contact her at Lavin@pbn.com.
