Ron Shriberg on AI, Risk & the Future of Financial Services | Ep 1235

Summary

The Digital Executive Podcast – Episode Summary

Episode: Ron Shriberg on AI, Risk & the Future of Financial Services | Ep 1235
Date: April 19, 2026
Guest: Ron Shriberg (Business Development Leader, New Rocket; Ex-KPMG Senior Director, ServiceNow Financial Services)
Host: Brian (Coruzant Technologies)

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Episode Overview

In this episode, Brian sits down with Ron Shriberg, a seasoned executive with over 20 years serving Fortune 100 clients, to discuss how artificial intelligence, risk, and cybersecurity are converging to transform the banking, financial services, and insurance sectors. Ron shares formative career experiences, explores immediate and practical AI applications, and outlines how integrating AI and cybersecurity will define the industry’s future.

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Key Discussion Points & Insights

1. Foundational Experiences and the Roots of Change Resistance

(02:16–06:01)

• Ron recounts an early-career story:
  • Attempted to modernize Boston’s fire department call box technology, replacing a 145-year-old analog system.
  • Faced intense skepticism, technical setbacks, and visible age bias from senior fire officials.
  • Persistence paid off: after three attempts (one ending in actual flames), ultimately succeeded.

Key Takeaway:

• Even entrenched organizations will adopt breakthrough technologies, but only after resistance is overcome through persistence, demonstration, and a focus on tangible improvement.

“The desire to enhance our lives and our experiences through technological adoption is far greater a force than the fear of change.”
— Ron Shriberg (05:55)

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2. The Reality of AI-Driven Transformation in Financial Services

(06:49–08:24)

• Big opportunity: It’s not just about more technology, but about better workflows.
  • Focus is on reducing friction in business processes, not just piling on tools.
  • Modernization means end-to-end transformation, not adding isolated solutions.
• Four Key Themes:
  1. AI should scale human judgment, but not bypass accountability—keep humans in the loop for decisions.
  2. Risk and compliance now offer strategic advantage—not just regulatory overhead; continuous tech controls reduce cost and boost transparency.
  3. Good data and governance decide whether AI is a multiplier or a liability.
  4. Treat AI as an enterprise capability, not a series of isolated pilots. Winners will formalize AI integration; laggards will be stuck experimenting.

“The goal isn’t necessarily more technology...it’s about fewer breaks in how work gets done.”
— Ron Shriberg (06:55)

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3. Where AI Delivers Value and Where to Be Cautious

(09:12–11:01)

• Immediate AI Value in Financial Services:

  • Augments staff, strengthens compliance, improves operational efficiency.
  • High-impact use cases:
    • Fraud and anti-money laundering (AML) augmentation
    • Back-office automation
    • Employee productivity tools (e.g., Copilot, ChatGPT)
  • Works best where data is strong and regulatory needs are clear.

• Caution Required:

  • Autonomously-operating AI, especially in:
    • Credit decisions
    • Customer-facing generative AI
    • Decentralized AI pilots
  • Risks of increased regulatory scrutiny, reputational harm, fairness issues, ambiguous accountability.

“Financial services need to be more cautious in the areas where AI operates autonomously…these can introduce heightened regulatory, reputational and fairness risks, often with unclear accountability.”
— Ron Shriberg (09:52)

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4. The Convergence of AI, Cybersecurity, and Enterprise Platforms: The Next Decade

(11:43–13:38)

Ron outlines five observations for the future of financial services:

1. Banks of the Future:

   • Will run on “intelligent, secure platforms,” not on siloed apps.
   • Integration of AI, cybersecurity, and enterprise tech becomes foundational.

2. Embedded AI Value:

   • AI’s real benefits show when integrated into operations, not as experimental add-ons.
   • Scaling judgment and control is much more valuable than scattered pilots.

3. Cybersecurity as a Continuous Control:

   • Security, identity, and resilience must be designed into platforms, not bolted on.
   • Reacting after issues arise is a losing proposition.

4. Trust Through Governance and Explainability:

   • Data transparency and clear explanations of AI decisions will drive trust.
   • Reputation alone is no longer enough for stakeholder confidence.

5. Operating Model Transformation:

   • The shift is not just technical but strategic.
   • Institutions aligning AI, security, and platforms under solid governance will outpace competitors.

“The future bank is going to run on intelligent, secure platforms, and definitely not disconnected applications...This is an operating model transformation disguised as a technology shift.”
— Ron Shriberg (11:48, 13:23)

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Notable Quotes

• “Human nature leans us towards adopting technology, no matter the perceived resistance.”
  — Ron Shriberg (05:36)

• “AI creates value when it scales judgment, not when it bypasses accountability.”
  — Ron Shriberg (07:05)

• “Without trusted data lineage and ownership, AI cannot safely scale, no matter how advanced the models are.”
  — Ron Shriberg (08:03)

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Memorable Moments

• Ron’s early-career fiasco involving smoke and flames in a municipal fire lab is both humorous and telling about the adoption challenges of new technology. (04:17–06:01)
• Emphasis on governance and explainability emerges as a through-line, linking AI adoption, regulatory confidence, and future competitiveness. (11:43–13:38)

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Timestamps for Important Segments

• Ron’s Fire Department Story: 02:44–06:01
• Big transformation opportunities in financial services: 06:49–08:24
• Where AI delivers value vs. where to be cautious: 09:12–11:01
• The next decade – convergence of AI, Cyber, & enterprise: 11:43–13:38

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Conclusion

Ron Shriberg’s insights stress that the real wins in financial services come from thoughtfully integrating AI and cybersecurity into the very DNA of organizations—emphasizing human accountability, strong governance, and end-to-end operational transformation. Risk, once a compliance headache, is becoming a strategic asset for those moving thoughtfully into the future.

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For listeners interested in the evolving intersection of AI, risk, and financial platforms, this episode is a succinct, insight-rich primer—with practical lessons on navigating real-world obstacles and seizing long-term opportunities.

Transcript

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[Brian (Podcast Host)]

Technologies, home of the Digital Executive Podcast. Do you work in emerging tech? Working on something innovative? Maybe an entrepreneur? Apply to be a guest at www.corazon.com brand welcome to the Digital Executive today's guest is Ron Schreiberg. Ron Schreiberg, a seasoned business development leader with over two decades of experience serving Fortune 100 clients in technology adoption. With a focus on the convergence of cybersecurity, risk it, asset management, HR and AI, Ron is leveraging his expertise in driving strategic initiatives, building C suite relationships, and delivering innovative AI first client solutions to enhance New Rocket's offerings in the banking, financial services and insurance Rectors. Previously, for 13 years as Senior Director, ServiceNow Financial Services at KPMG, Ron developed and implemented client solutions that drove efficiency, automation and risk avoidance for Fortune 100 clients. Well, good afternoon Ron. Welcome to the show.

[Ron Schreiberg (Guest)]

Thank you, Brian. Really appreciate you having me today.

[Brian (Podcast Host)]

Absolutely, my friend. I appreciate it as well. You're hailing out of New York City, I'm in Kansas City, so we're just an hour apart, but sometimes it' hard to make these things work. So I really appreciate that. And Ron, if you don't mind jumping into your first question, You've spent over two decades working with Fortune 100 clients across cybersecurity, risk IT, and now AI driven solutions. What key experiences shaped your journey to where you're at today?

[Ron Schreiberg (Guest)]

Well Brian, I have a very unique story I wanted to share as kind of a backdrop, and it happened very early in my career. I was working for a family business in the field of electrical contracting and I just won a contract with the municipality within the City of Boston. See, I wanted to substitute some specified equipment that saved cost and improved experience. I was challenged with, you know, the substitution of a digital street corner call box equivalent for what they called as an analog gamewell system that had actually been in use for roughly 145 years since the early 1850s. And in order for me to receive approval consideration, it required months long submissions of documentation, schematics and design reviews. And once all that was completed, I was finally invited to begin the testing phase. And now, mind you, I'm in my 20s and the testing was to be done in the City Department lab among some of the most senior fire department

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[Ron Schreiberg (Guest)]

Well, the testing part proved the most challenging for me and as they say, third time's the charm. And it took all three tests to finally get it to work. The first test was met with the fire leaders gathering around with audible laughter and dismissive content. Well, I plug everything in, I flip the switch, smoke, then fire. Actual flames. They offer me a goodbye chuckle as I packed up the equipment. And as I leave, I ask, I'll be back if you'll have me some re engineering. Several weeks later I returned for a second test and fewer leaders gathered this time, but the same antics persisted as they did during the first. Again, I plug everything in, I flip the switch. This time just smoke. To be fair, I learned from the first test. I disconnected power before reaching flashpoint. Let's just say this wasn't the sort of result you wanted when presenting to the second oldest fire department in the United States. I was up against a mountain of resistance from age bias, perceived knowledge deficit, and unproven digital technology to replace an analog technology. Again, I packed up in defeat and unsure. But I asked, I'll be back if you will have me. And really, what I learned from that valuable experience was that human nature leans us towards adopting technology. No matter the perceived resistance, technical challenges, or even the grumpy attitude of a soon to retire fire chief turned fire lab leader. The reason for this is really the desire to enhance our lives and our experiences through technological adoption is far greater a force than the fear of change.

[Brian (Podcast Host)]

Wow, amazing story. And it goes to show your persistence. Obviously working in a small family business and you go to a municipality like the city of Boston and when you're replacing antiquated equipment like that, you're under a lot of pressure to make things work. And, and I just appreciate your story of being vulnerable, telling it how it was, or your early 20s and up against some very senior folks that had a lot of experience, at least in the fire protection area. And it was, it was challenging. So I appreciate the story of the backstory on it, honestly. And Ron, at New Rocket, you're focused on delivering AI first solutions in banking, financial services and insurance. What are the biggest transformation opportunities you see in these industries right now?

[Ron Schreiberg (Guest)]

Yeah, that's a great question. Thank you, Brian. Really the biggest opportunities I see is that the goal isn't necessarily more technology, so to speak, in business terms, it's really about fewer breaks in how work gets done. So modernizing end to end workflows, not adding point solutions where cost reduction, speed and control actually show up. And so there are really four themes I see. One is AI creates value when it scales judgment, not when it bypasses accountability. And so we prioritize AI that augments decision makers in risk operations and services while keeping humans responsible for the outcomes. The second is risk and compliance are really becoming strategic advantages, not just regulatory obligations. And so continuous technology enabled controls reduce cost, they improve transparency and, and ultimately strengthen the regulator confidence. Third is the data and governance determine whether AI becomes a multiplier or a liability. And without trusted data lineage and ownership, AI cannot safely scale no matter how advanced the models are. And lastly, fourth, this is an operating model transformation, not a series of pilots. So organizations that treat AI as a governed enterprise capability will really pull ahead. And those that don't are going to stay stuck in experimentation mode.

[Brian (Podcast Host)]

Thank you, I appreciate that. And you're absolutely right. I've been in technology a long time and we see a lot of people, I've been asked, well, just throw more technology at it, that's going to be the solution. And it's not always the solution. You talked about that. Really, in some cases it's more efficient processes.

[Ron Schreiberg (Guest)]

But you did talk about how you

[Brian (Podcast Host)]

are leveraging AI and some of that research, risk and compliance, looking at controls, et cetera. But at the end of the day you got to have that human and a loop loop. And ultimately that human needs to be there for that final decision to make sure everything is correct. Because at the end of the day, humans are responsible for the outcomes here. So I appreciate that. And Ron, AI is rapidly being adopted across financial services. Where do you see AI delivering the most immediate value and where should organizations be more cautious?

[Ron Schreiberg (Guest)]

Yeah, so what we're seeing is really AI is delivering near term value and financial services where it augments people, strengthens the control functions and improves operational efficiencies. The fastest and the most defensible returns are coming from risk and compliance, as I mentioned before, especially in the areas of fraud and AML augmentation, also back office automation and employee productivity tools. Right. We see this with Copilot and the use of ChatGPT and other models, but these are the use case cases that are leveraging the existing data sets, really helping preserve human oversight and align well with regulatory expectations. And so by contrast, right. Financial services need to be more cautious in the areas where AI operates autonomously, so directly impacts customers or scales without strong data and governance foundations. And I might give you an example in terms of like autonomous credit decisions, customer facing generative AI and even decentralized AI pilots introduce heightened regulatory, reputational and fairness risks, often without unclear accountability. And so as mentioned earlier, the bottom line is that financial services organizations that create AI as a governed enterprise capability rather than a collective of pilots that are going to realize measurable value today, those that don't, that do, move too aggressively in autonomous or customer facing use cases. Without strong governance explainability and data readiness, risk regulatory scrutiny will be increased, slow adoption and erosion of trust among stakeholders like customers and shareholders. So that's, that's kind of where, where we're seeing it.

[Brian (Podcast Host)]

Thank you. And I, I do love this. I talk to people from all across the spectrum about AI and, and I love getting into this. Here is risk compliance financial services. But you did talk about AI being really augmenting humans now in financial services, which is great. And the biggest concern you're seeing is in the fraud and compliance area. And I think AI can certainly augment humans to do even a better job. Again, human in a loop always, of course. So again, I appreciate your insights. And Ron, as we look ahead to the future, how do you see the convergence of AI, cybersecurity and enterprise platforms shaping the future of financial services maybe over the next decade?

[Ron Schreiberg (Guest)]

Yeah, I think, you know, we're clearly at a precipice of AI. Definitely beyond hype and pilots enterprises are finding real value in the use cases. The ones we've mentioned about now think of AI as a fuel for acceleration. Right. The speed at which cybersecurity enterprise platforms are moving is Already astonishing. I think I'd leave you with five observations on this and that is the future bank is going to run on intelligent secure platforms and definitely not disconnected applications. That's to say, AI, cybersecurity and enterprise platforms are converging to become the core operating foundation of the institution. The second would be AI creating advantages when it's embedded in how we operate, not bolted on as experiments. And the true value is going to come from scaling judgment and control access across the enterprise, not in isolated pilots. Thirdly, I would say cybersecurity is no longer just defense, it's become a continuous control layer built into every workflow. So security, identity and resilience must be designed into the enterprise platform, not added after the fact. We've seen that in the past decade and the challenges that have resulted. Fourth, the trust will be engineered through data governance and explainability, not just brand reputation. And as AI becomes pervasive, transparency and accountability are just as critical as innovation. I'll leave you lastly with a fifth thought, which is this is an operating model transformation disguised as technology shift. Financial services organizations that align AI, security and enterprise platforms under strong governance are going to move faster, manage risk better, and outperform their peers.

[Brian (Podcast Host)]

Thank you, really appreciate that.

[Ron Schreiberg (Guest)]

Dash AI.

[Brian (Podcast Host)]

There's so many different use cases today that it's already been applied and are

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[Ron Schreiberg (Guest)]

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[Brian (Podcast Host)]

is being applied in some of these last couple industries and I talked about that on another podcast. I won't go into that. But beyond hype and pilots, I agree with you. AI is, I think almost mainstream people are trying to get their, their, their mind wrapped around it in some organizations, but it's certainly going to be a game changer. But you did talk a little bit about cyber and I think that's an important, important point to point out here is these because these platforms are being so interconnected, as you mentioned, I think being connected as a one operating system of your organization, you've got to deploy cyber and AI more in those control areas. Control points to be proactive against cyber risks and intrusion. So I I appreciate, again, your insights today. And Ron, it was such a pleasure having you on today, and I look forward to speaking with you real soon.

[Ron Schreiberg (Guest)]

Thank you so much, Brian. Really appreciated the opportunity. Have a wonderful day.

[Brian (Podcast Host)]

Bye for now.

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