Thank you so much for joining us in this interview series. Can you share with us the backstory about what brought you to your specific career path?
Growing up, I watched my dad found multiple data and insight-driven martech companies. Being a curious teenager at the time, I always asked him questions about them. Then, at my first-year college orientation, the person sitting beside me was on his laptop looking through a Google Analytics dashboard for his dad’s landscaping business. We started discussing the data and how he could find growth opportunities for his dad’s company, then together created a marketing and development agency to take a data science approach to growing local businesses. We built a number of algorithms for analyzing how people interacted on the site, what the sticking points for conversions were, what caused people to convert, and what traits led or didn’t lead to conversions.
Then COVID hit, and we pivoted to digitizing traditional brick-and-mortar businesses, which gave us access to even more insights and points of optimization for our customers. At the time, I had been researching intent platforms and had become curious about how this same analysis could be leveraged on third-party sites. This led to me joining Truent and helping to launch exactly that: an intent platform built on real-world data and interactions surrounding how banks buy.
What do you think makes your company stand out? Can you share a story?
Other solutions out there fall in one of two buckets: they are either generalized to support a wide array of industries, or they are focused on deriving insights from individual interactions on their site and from their sales activity. By focusing only on how banks and credit unions buy, we can build an AI product that understands the complexities, problems, solutions, and key interactions unique to a specific product or service.
For example, a potential journey for a bank buying a new Risk Management Software could be something like this: in January, a fraud manager at the bank is having trouble generating a report in their current platform. A week later, the Chief Compliance Officer gets an annual audit back saying they aren’t effectively measuring their risk. The Chief Risk Officer then tasks the Director of Consumer Risk to find a consultant to help them fix the issue. The Director of Consumer Risk does some internal research and decides on three options.
The team shares these options with their vendor procurement team and settles on a consultant. Two months later, the bank is again researching how to generate their needed reports. Finally, the bank starts looking for alternatives to its current solution. They settle on two potential replacements and internally gather all the research. The thing is — their current contract isn’t up for 12 months, and they go dark for the next six and still haven’t talked to the vendor.
Our product-specific buyer journey understands all of these interactions and builds a graphical representation of it that enables us to understand the true leading indicators for potential deals.
You are a successful business leader. Which three character traits do you think were most instrumental to your success? Can you please share a story or example for each?
Focused Adaptability: When navigating the challenges of a fast-growing startup, being focused yet adaptable has been instrumental to my success. The ability to adapt quickly as a startup leader is part of the job when you’re in a landscape that is constantly evolving. However, I put one caveat on that: your adaptations need to remain goal-oriented and concentrated on furthering the core mission or objective. We live in a world where innovations that might be a cool idea but don’t align with where we want to go are popping up all around us. In my knowledge management system, I use a template to brainstorm an idea and understand how it connects to other goals. The first question in that template is “How does this move closer to my objective?” If I can’t answer that question in 30 seconds, that idea is likely an “Attention Blackhole”. It will consume time and resources without advancing the mission.
Be a constant learner: The ethos of being a constant learner and instilling this value in our team has been foundational to Truent’s culture and success. In a field as dynamic as AI and Financial Services, the learning curve is steep and unending. I like to think of learning a subject not as a path but as interconnected nodes of knowledge, where being able to learn something is about understanding the connection and relationship between other things, rather than simply reciting meaning. If you can do this as a leader and get your team on board, you can foster an environment where innovation and creativity are at the forefront.
Resilience: In startups, you have to be able to bounce back after you get knocked down. You have to always remind yourself that if the road was smooth, everyone would be doing what you’re doing. My grandpa has this saying he recites anytime something bad happens: “Stand up, and take another step.” When faced with a challenge or roadblock, you can’t sit there and dwell on it. You have to be able to stand back up and figure out a path forward. This helps foster good morale in rocky times and encourages your team to focus on solutions rather than over-stressing about being wrong. This mindset has enabled my team to maintain our momentum and continue pushing the boundaries of what’s possible, even in the face of adversity.
Can you explain how AI is disrupting your industry? Is this disruption hurting or helping your bottom line?
It doesn’t matter the industry — AI is disrupting everything. For financial services and fintech, it is leveling the playing field. Small companies are generally able to adopt and leverage new technologies faster than larger ones. AI is not an exception: we’re seeing smaller players create artificial scale and do more with less. This hurts the bottom line of companies who refuse to adopt it, and helps the ones who do.
Which specific AI technology has had the most significant impact on your industry?
I’ll answer this in two ways: what has already had the biggest impact, and what will.
To date, the accessibility and tooling around AI have made it easier than ever for a company made up of employees with no AI experience to roll out their own AI offering. If you look back 3–4 years ago, you had to hire specialized engineers and set up expensive infrastructure to build something far less sophisticated than the tools we’re seeing today. Now, people with little to no experience in computer science deploy AI tools to help them in their day-to-day lives.
If I look forward to what will have the largest impact on the industry, it has to be the creation of a Financial Services-specific LLM. The combination of this and domain-specific ontologies will open the doors for a whole new wave of advancements in the industry.
Can you share a pivotal moment when you recognized the profound impact AI would have on your sector?
When OpenAI launched GPT-2 back in 2019, it was clear that the years to follow would see generative AI making an unprecedented impact across all industries. At the time, there were a plethora of formidable challenges that would have to be solved for Financial Services to fully embrace AI. Most have been solved, but others haven’t.
How are you preparing your workforce for the integration of AI, and what skills do you believe will be most valuable in an AI-enhanced future?
For companies to get the most out of AI, it has to be leveraged by every one of their employees. The biggest hurdle is going to be convincing your team that AI isn’t replacing them — but instead enabling them to do their job more efficiently.
What are the biggest challenges in upskilling your workforce for an AI-centric future?
Continuing from above — I explain it like this: if someone offered to tackle your least favorite, most time-consuming tasks faster than you’d be able to yourself, you’d let them help! That’s the mindset you have to encourage your team to adopt. AI is a high-powered, efficient assistant we should all be taking advantage of.
What ethical considerations does AI introduce into your industry, and how are you tackling these concerns?
In the financial services industry, transparency and explainability are going to be an ethical issue that has to be solved. Financial services are highly regulated and have to document how and why they came to make decisions. Many AI systems, particularly those based on deep learning, operate as “black boxes,” making it difficult to understand how they arrive at certain choices. This can create a moral conundrum where an employee is trying to use AI to do their job better, but they don’t have the context as to why the AI outputs what it outputs. This makes documenting how you arrived at a decision almost impossible. To combat this, we are building experiences that demystify what the AI is doing and provide fact-based explanations at the core of all of our AI products.
What are your “Five Things You Need To Do, If AI Is Disrupting Your Industry”?
- Educate the entire leadership team. Everyone on the team needs to understand the current state of AI and how the company can leverage it. If there isn’t alignment at the top it can make fostering the usage of AI throughout the company challenging. At Truent, I put together a short deck on how generative AI works, what it does well, and what it does poorly. We then created a Slack channel for the leadership team where we share articles on AI advancements and add commentary on how it impacts us. This gets every department thinking about it.
- Get your employees on board with using AI. This is a must for making sure you aren’t lagging behind the competition. The important thing is showing them best practices in such a way that it humanizes using these tools and the need for doing so. In the past, I’ve done this by pulling up ChatGPT and asking it questions in the middle of planning meetings when we’re stumped by generating new ideas. This demonstrates vulnerability and an acceptance that AI can fill in the gaps where we need it to.
- Identify the most time-consuming tasks your employees perform and highlight how AI can streamline them. If an employee is spending five hours a week on a task that AI can complete in just two, you gain an incredible amount of time back. These savings help further innovation and growth. We once had to pull data from ten different systems and synthesize it into a single summarizing report for a customer. Analyzing each report required a full hour from three different team members, but within half an hour of adjusting prompts in ChatGPT, we were able to come up with a solution that took one person only 15 minutes.
- Figure out ways your current product offering can be enhanced by adding AI features. This is the easiest way to start making your product stand out in the market and can increase usability and retention. I find the easiest way to do this is to look at what tasks users spend a lot of time on in your product and find a way that AI can make it easier. This creates immediate value for everyday users.
- Lastly and most importantly, you need to think about the ways AI could make your product obsolete. If there are core functionalities or value propositions that could someday be completely replaced with AI solutions, your company needs to be the one that develops that solution. You can’t sit back and wait for it to happen, and you can’t be naive in thinking it won’t happen. There is likely someone out there trying to do that exact thing already — and as a company you need to ensure that you’re at the forefront of this development, or risk losing your competitive edge.
What are the most common misconceptions about AI within your industry, and how do you address them?
There’s no shortage of low-quality or general solutions out there that can create a perception that AI is bad and generates false outputs. If you build a specialized solution, using specialized data, and create ample guardrails, you can eliminate this risk in 99.9% of outputs.
Can you please give us your favorite “Life Lesson Quote”? Do you have a story about how that was relevant in your life?
I think Walt Disney’s quote, “The way to get started is to quit talking and begin doing,” has been a key one for me. It’s easy to get stuck in analysis paralysis (i.e. having so much data to inform your decision that you aren’t able to make one at all), but at a startup in the age of AI, we can’t afford to lag. We need to move fast and with purpose. This is something that I try to live by, and when we have an idea that might have some legs, the next thing I do is figure out how I can quickly put together a prototype to validate it. This can create a snowball effect and get things moving more quickly.
Off-topic, but I’m curious. As someone steering the ship, what thoughts or concerns often keep you awake at night? How do those thoughts influence your daily decision-making process?
For me, it’s often the feeling of “what we are missing”. We live in a fast-moving world where new innovations come out every single day. It’s easy to miss or overlook something that could have a profound impact on your company, so we have to do a little more research when making a decision. There are a couple of things that I have found to help this. The first is having a system for taking and processing new information, which will help you organize it and keep track of the direction things are headed. The second is building a team that embodies the idea of continuous learning. This enables you to delegate and create subject matter experts on the cutting edge of AI in their respective fields.
You are a person of great influence. If you could start a movement that would bring the most amount of good to the most amount of people, what would that be? You never know what your idea can trigger.
I would create a movement on banking local. Community banks and credit unions are the backbone of local economies, and they’re the primary source of investment in local businesses. Over the next couple years, it’s projected that 30% of these financial institutions will close their doors or be acquired. This will cause fewer mom-and-pop businesses to emerge. With fewer banks and fewer local businesses, large corporations will thrive and consumer choice will dwindle, creating an even bigger hurdle for new entities.
How can our readers further follow you online?
You can connect with me on LinkedIn, where I am starting a series called Bridging AI. I’ll post weekly articles designed to bridge the gap between technical and non-technical audiences, and focus on how the application of AI solves business challenges. The series offers dual reading perspectives: one tailored for non-technical individuals that illustrates how AI can be applied to solve the problem, and the other focused on technical implementation and how to make sure it addresses specific business needs.
Thank you for the time you spent sharing these fantastic insights. We wish you only continued success in your great work!