Tech-Exec 18 - Brent Wilke Brochure

B R E N T W I L K E

BANKING ON TECHNOLOGY

WE TALK TO BRENT WILKE, CHIEF DATA OFFICER AT FIRST BANK, ABOUT THE IMPORTANCE OF DATA AND ANALYTICS IN THE ONGOING SUCCESS OF HIS ORGANISATION, AND THE POTENTIAL FOR TECHNOLOGICAL CHANGE.

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in Motion (RIM). Now most technology companies have offices there including Arctic Wolf, Google, Microsoft, SAP, and Oracle.

I’m the Chief Data Officer for First Bank, a North Carolina based bank with 118 branches throughout North and South Carolina.

I started working before I even graduated at Manulife Financial as a programmer and I did mostly application coding. I realised quickly that I wanted to do and learn more and my manager asked me if I wanted to take over an analytic reporting role. I accepted and I never looked back. I’ve been in analytics since then, so I have seen the change in analytics over the past several decades.

I manage services such as Data Presentation, Data Integration, and Data Management.

I’ve also been given oversight of all databases inside the company. I’m currently working on MDM for customer critical data elements and migrating to one data ecosystem.

We will be working on Data Governance in the near future.

My previous role was Data Management Director for Heartland Financial, with very similar activities. As Chief Data Officer I have some added responsibility around security and leadership.

I obtained my Master of Science from the University of St. Thomas in Minnesota with strength in Data Management. I learned so much in this program which really led into my future roles including data engineer, data modeller, data architect, ETC, and I began to increase my roles and responsibilities over time.

I received my undergraduate degree in Waterloo, Ontario, Canada – dubbed Silicon Valley North. And when I was getting my education there were a lot of the technology organisations just starting to take off such as NCR, Teradata, Blackberry, Research

My past certainly influences my current work as I know how to do things the ‘old’ way, as well as the ‘new’ way. But theory behind analytics and AI has not really changed; the software and applications have just been enhanced.

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Can you tell us about your current role, and your previous experiences in data and technology?

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Where does data and analytics sit in the organisational hierarchy now?

Adoption of data and analytics is really based on leadership agreeing that analytics is just as important, not just data itself. This is very important to an organisation. Without this leadership support, data analytics will not flourish at an organisation.

At my predecessor companies, when new leadership would emerge I found that in some cases they weren’t as interested in data analytics and didn’t want to grow it as much.

Therefore, it started to decline. My present company is very interested in data and analytics, calling it the backbone of how to grow, manage, and enhance the business.

Inside US banking, there’s an organisation called Mid-Size Bank Coalition of America (MBCA). Both my predecessor and my current company are members of this organisation.

They have meetings with different layers of leadership: CEOs, CFOs, CIOs, ETC. MBCA has presented topics about Data Governance and Analytics along with many other topics.

Both companies have presented or talked and have listened to others’ perspective on data

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analytics with peers. First Bank’s executive leadership always comes back to The Data Team with new ideas from the MBCA that feed into our current strategy of one data ecosystem and creating a customer golden record.

In my current role, you must deliver Return on Investment (ROI) for building data items. I try to show that what my team is doing and what we’re supporting, what items we’re doing with AI or machine learning, all have ROI. In many cases, the CDO must think financially as well, to prove the ROI and work within a budget. I worked for one company where my group was a total chargeback, so I had to watch every penny, because I was being charged from the parent company for everything we were doing. Understanding Budget, P&L, and ROI are very important.

When it comes to internal and external usage of data and management of data, I don’t think it’s a discussion about big data, data mesh, ETC. But more about how data is consumed, ROI, and producing outcomes to support the strategic direction. Internally, it’s about automating several data processes and data

integration to reduce manual labour.

So far, the data team has produced a number of those outcomes.

An example is that we took ‘decision tree’ – a ‘low hanging fruit’ type of artificial intelligence – and started pushing that out in the organisation. There are processes where staff would get data externally and they’d have to make manual decisions about what they wanted to do with this data. We were able to take a number of manual business processes and convert them to ‘decision tree’ where they became an automated function.

You must look at your whole organisation internally and say, “Where’s all the data analytics systems, where is data being moved, and what are the expenses for these activities?” Once you know this you can decide how many data ecosystems you need based on company size and business needs. You then plan to reduce data movement and data ecosystems. This then reduces your vendor expenses and your expenses in training, staffing, etc. If you have four data ecosystems, you have four different answers across the organisation. You want to migrate to one data ecosystem, if possible, and one data answer.

The primary goal for a CDO is to assist the organisation to be proactive with your customers and the business. Proactively seeking information about and interpreting your collective customer interactions with your organisation. In the banking industry, I would suggest segmenting your customers into groups, and then manage the customer interaction as they move around these segments. For example, you want to track if customers shift from one segment to another segment, then locate what caused the segment

movement. Recognise the movement right away and be proactive by reaching out to the customer and discuss with them “the movement in the segment”. Many companies have a hard time figuring this out but to me that’s the driver for ROI of a Data Team.

This is not about analytic software, tools, big data, data mesh, all that stuff. It’s how you’re consuming and using data to be proactive in your organisation.

Before you can migrate your customers into segments your technology has to understand, manage and maintain your customers. To do this your organisation requires a Customer Golden Record for each unique customer.

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A Decision tree works like that game Plinko, where you have a whole bunch of pegs, you drop a little puck down and it jumps around to the bottom, but with the Decision Tree process you plan how the ‘business functions/ puck’ reaches the bottom. The first one we built saved the company one to two hours a day of a financial staff member. After fully implementing this process we achieved ROI in about 2 months.

“I know how to do things the ‘old’ way, as well as the ‘new’. But not a lot has changed – it’s just the tools that have.”

First Bank is working with NC Based FLUREE and their AI Functions to create the Customer Golden Record. The Record is the prime identifier to manage the Customer’s Critical Data Elements (CDE) such as customers contact details, customer type, customer identifiers, etc. Once you have that customer CDEs managed you can then proceed to create and administer Customer Segmentation, Customer Householding and Super Householding, ETC. This business need; surrounding Customer CDE data, is the prime backbone to any CDO/ Business strategy.

What about your own data and analytics journey?

The biggest key moment for me was when I started digging in further in my second role 125

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P H O T O: K ELLY S I K K E M A

in the United States at UnitedHealth Group (INGENIX – now Optum Health), a huge healthcare company. I didn’t have the total healthcare experience, but they were looking to grow in healthcare analytics, and I had some experience in data management/ analytics. The company wanted to build its first data warehouse, so I was doing the analysis work with business partners, as well as technology to build an Enterprise Data Warehouse for Ingenix.

The basic concepts I had to understand are data, information, knowledge, and wisdom (DIKW). If you understand what they do, how they work together and what your position is on those four things, then you’ve beaten most of your battle for a CDO. It’s not the data mesh, big data, or other data buzzwords.

It is your responsibility within the four levels of DIKW. My current role is producing data and information, taking raw data and applying information to that data to make it useful to the organisation. The business then applies this knowledge and wisdom to the Data/ Information. That’s the big trick I learned: talk to the business on the Knowledge and Wisdom they need to run the business then locate the Data and applied Information to meet the Knowledge

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“I’ve also worked with companies that say they’re data-driven, but unfortunately, it’s just talk; more like discussion points for stockholders to think something’s going on.” and Wisdom they requested.

How important is recruitment and talent to your ongoing success?

When I first came on board at First Bank, I performed a Data Maturity assessment to provide information about where the concerns and ‘holes’ were in the bank’s growth with

P H O T O: L I N K E DI N S A L E S S OLU T IO N

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P H O T O: B R O O K E C A GL E

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data. With that outcome I realised the bank did not have any team members with advanced knowledge in Data Integration and Data Management (such as Data Engineers) and started to work on recruiting external team members. I usually prefer to find internal staff with the “Data DNA/geekiness”. My current structure is 30% external and 70% transfers internally. Some entire teams were moved to the Data Team. Other staff I found within the organisation. I think corporate knowledge and internal data geekiness is like gold to a Data Team. They bring huge internal knowledge and existing relationships to the group. The new external team members share their advanced knowledge with the entire team and we all win.

One part of my role as a hiring manager is that when we find good candidates for a role I then discuss the techy stuff with the candidate and learn a bit about their background but ultimately the candidate meets the team and the team helps make the decision based on team culture dynamics.

A strong culture and a data geek team is very important to me, to be successful for my team’s goals. And that’s how I’ve done it when I manage any groups. Technically I am the “boss” but that’s just my nickname, I’m here to be a guide, coach, and mentor.

How do you approach leadership with your team and across First Bank?

I’ll never take a data leadership role without the executive leadership being an advocate for the role and need.

Each member of the data team is accountable and they own something. Many of my peers own everything and then people just work for them. I make sure to delegate things to my team. For example, someone may be in charge of our data integration, they figure it out, how

it’s going to work, etc. If a request comes up, they manage the full scope. I generally have someone who is assigned as a Gatekeeper.

This person manages the intake that comes to the data team and builds a whole process around it, determining Lines of Business and finding a Data Delegate within each LoB. With this process we can stay in-tune with what each Line of Business needs to support their strategy and goals.

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Finding the right person isn’t always finding the right technology person. I can teach someone technology; I can’t teach them culture. I’m a big advocate for finding data and talent internally first, before I go outside.

“The basic concepts you must understand is data, information, knowledge, and wisdom. If you understand what they do, how they work and what your position is on those four things, then you’ve beaten most of your battle.”

In today’s world, what we would consider “DOERS” want to own and be responsible for something, they don’t want to just be told what to do every day. They want to own and manage something in the organisation.

Therefore, I am sure to delegate items that I am accountable for to my team members in order for them to take ownership.

The number one thing I must work on is being the leader for data culture change. My actual job is not Chief Data Officer. My job is data culture change officer, whatever you want to call it. I work with the organisation to enhance the consumption and usage of data across the bank’s Line of Businesses.

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Tell us about the Blue Ocean Strategy and how you apply it to your role.

The Blue Ocean Strategy is a strategy to take a leap for a company to do something new or innovate in existing business activity. Examples are RIM (Blackberry), Uber, Marvel, Nintendo (Wii), Casella Winery’s Yellow Tail, Netflix.

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To explain further, you’ve got this red ocean; a feeding frenzy of business, like banking or healthcare in the U.S. Then you want to come up with a strategy to make the competition irrelevant, and allow differentiation and low cost to coexist.

How do you stand out? You do something new that gives you a blue ocean. The concept is you take analytics, thoughts, and brain power to capture what could place you into that blue ocean. There’s actually a whole book written about this subject. There’s another term/idea for it – White Space, which precedes Blue Ocean. This concept is value innovation – pursuit of differential and low-cost ways. Part of it could be not finding a new activity but finding a new way.

Take Uber as a concept. The Taxi industry had not changed for centuries and this was the process to allow someone to go from point A to point B that did not have a car.

Uber invented a new approach to the movement of people.

Creating blue oceans takes technology, innovation, analytics, and a business concept to test all those things out. I am focusing on being proactive with our Customers and will be a migration to that Blue Ocean.

What is the future of banking?

In the U.S., we have about three/four predominant companies that manage banking cores, and they have all these ‘wrappers, services, options’ around what they can do. They want to sell you all these services and options where everything is from their company. This process needs to change so that all that they do is the bank core transactions. A customer puts $10 into their account, the core runs all our processes to 130

match the $10, throws out a transaction, and passes it over to finance. And that is it.

Everything else is run by an API, a plug-andplay with the other types of vendors that do that activity. So, we still have your core for banking; but, all your other business functions – such as analytics, treasury, finance, account opening, lending - are now an interaction with some other vendor via an API. If you want to do your treasury option, another vendor does that, and it’s just going to be via an API feeding back and forth.

Your online banking might be another vendor, perhaps they have two or three for different types of online banking and that’s another API back and forth. But these are all APIs, core’s in the middle, and all these activities you want to go to different vendors and swap them in and out as you need them. Some banks may be doing that, but that’s the future state.

Then something a little different – banks building their own Banking as a Service (BaaS). Yes, some banks have not survived developing a BaaS function. BUT, for example, there is a small bank in Iowa (17 Branches/$2B assets) that built Banking as a Service to interact with FinTechs and other organisations. This allows them to sell differently to customers across the U.S. backed by this bank’s secure processes.

This bank has 17 branches but is rated as the 40th largest bank in the US by number of accounts. They now sell their business across the U.S. through their BaaS and they have other organisations using it. They did the reverse function of a Fintech. They didn’t have Fintech go buy a bank; they went and built their own BaaS and allowed other organisations and Fintech to consume their BaaS. Think of them as an Amazon for other banks, they are the conduit to sell a product.

It’s really a neat concept.

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