From Friction to Collaboration: The Future of Payment Integrity

Summary

Podcast Summary: From Friction to Collaboration—The Future of Payment Integrity

Becker’s Healthcare Podcast – December 10, 2025
Guest: Brian Berkowitz, Chief Product Officer, Lyric
Host: Lucas Voss

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Episode Overview

This episode explores the escalating challenges and emerging solutions for payment integrity in healthcare. Brian Berkowitz of Lyric shares insights on how technological advances, particularly in AI and blockchain, are transforming a traditionally adversarial process into one focused on trust, transparency, and collaboration between payers and providers. Key themes include the concept of “trusted intelligence zones,” the potential to reduce administrative burden, and predictions for the evolution of healthcare data integrity in 2026 and beyond.

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Key Discussion Points & Insights

1. The Current Payment Integrity Landscape

• Theme: The healthcare landscape is marked by mistrust, competition, and fragmentation in the payment process.

• Brian compares the current environment to “an arms race,” with both health plans and providers rapidly deploying AI solutions to outmaneuver each other, resulting in increased silos rather than collaboration.

• Quote:

  "If we look back at history, most arms races at their core are fueled by a lack of trust."
  — Brian Berkowitz [02:31]

• Both sides worry about being disadvantaged, leading to duplicated systems, fragmented models of truth, and worsened administrative burdens.

2. The Need for Trust and Systemness

• System Fragmentation: Proliferation of proprietary AI tools exacerbates fragmentation, undermining trust and alignment.
• Impact:
  • Duplicated work
  • Increased administrative overhead
  • Distracting from the core mission: delivering better and more affordable care
• Brian suggests technology is now mature enough to “create trust by design,” utilizing AI, blockchain, and privacy technologies.

3. Trusted Intelligence Zones (TIZ)

• Definition: A secure, neutral digital environment where payers and providers can access the same, validated insights in real time, without giving up control of their proprietary data.

• Key Features:

  • AI-driven mediation
  • Blockchain accountability
  • Privacy-centric governance
  • Transparency and verifiability of every decision

• Quote:

  "Almost think of it as a digital trust fabric where instead of both sides sending files and data back and forth and debating whose data is right ... everyone's getting to see the same validated insights in real time."
  — Brian Berkowitz [05:08]

• Goal: Build fairness and traceability into the architecture of payment integrity systems, moving from adversarial audits to collaboration.

4. AI’s Role in Payment Integrity and Administrative Burden

• Traditional Approach: Retrospective, manual audits detecting payment errors after the fact—inefficient and tension-laden.
• Modern Shift:
  • AI enables proactive detection, flagging issues earlier, often at the point of care.
  • Reduces need for audits and appeals, lowering friction while improving transparency and education.
• Quote:

  "We're shifting towards more of a world where we can detect more before the issue even happens and get it to happen even closer to the point of care ... reducing a lot of the administrative back and forth."
  — Brian Berkowitz [07:14]

• Outcome: Fewer manual processes, greater consistency in outcomes, and human focus redirected to the most complex issues.

5. Building Alignment for a Collaborative Future

• Alignment & Data Accuracy: As healthcare becomes more data-driven, alignment between payers and providers is crucial for scale.

• 2026 Predictions:

  • Convergence of policy (data liquidity/interoperability), widespread provider adoption of AI, and increasing consumer/employer demand for transparency.
  • Regulatory push makes standardized data sharing a requirement.

• Quote:

  "2026 is shaping up to me to be a big year for healthcare ... these trends are going to push for a lot more required collaboration across the ecosystem."
  — Brian Berkowitz [09:54]

• Data Collaboration: Essential for building shared intelligence and solving the trust challenge.

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Notable Quotes & Memorable Moments

• On AI arms race:

  "Each side is starting to build their own tools, they're using their own data models, and they're really defining their own definition of truth, which instead of building bridges ... is really starting to build more silos ... fueling even more mistrust."
  — Brian Berkowitz [02:31]

• On the North Star for Lyric:

  "Accuracy to us builds alignment and alignment is really what's required to get trust. And when trust exists, simplicity really follows from that."
  — Brian Berkowitz [00:33]

• On the next chapter for healthcare tech:

  "We spent years building automation that is fast, efficient and scalable. But this next chapter is all going to be about what's accountable, explainable, and fair."
  — Brian Berkowitz [12:17]

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Timestamps for Important Segments

• 00:00–00:33 – Introductions & Brian’s background
• 01:57 – Trust as the foundation for payment integrity
• 02:31–04:48 – AI adoption as an arms race and its unintended consequences
• 05:08–06:44 – Introduction and explanation of “trusted intelligence zones”
• 07:14–09:14 – How AI reduces administrative burden and creates equitable payment outcomes
• 09:54–11:59 – 2026 outlook: collaboration, regulatory trends, and data liquidity
• 12:17–13:08 – Closing thoughts on trust, safety, and the future of accountability in healthcare

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Conclusion

Brian Berkowitz makes a compelling case for shifting the payment integrity paradigm from one of mistrust and friction to a future grounded in technological trust, shared data intelligence, and system-wide collaboration. As AI and interoperability become requirements, he stresses that sustainable innovation will depend on building fairness, transparency, and, above all, trust into every transaction and relationship within healthcare.

“The true leaders aren't going to be the ones with the flashiest AI tools. They're going to be the ones who are really designing their ecosystems to have that trust and accountability into what they're doing.”
— Brian Berkowitz [12:17]

Transcript

[A]

Hi everyone, this is Lucas Voss with Becker's Healthcare. Thanks so much for tuning in to the Becker's Healthcare podcast series. It's fantastic to have you. Great topic today, certainly timely. We're talking about the future of payment integrity. And joining me for today's discussion, I'm very excited to have him on is Brian Berkowitz, Chief Product Officer at Lyric. Brian, thanks so much for being here today. It's great to have you.

[B]

Absolutely. Thanks for having me on.

[A]

I want to start off with introductions for those that might not know you yet. At least if you want to just tell us a little bit about yourself and your work in healthcare.

[B]

Yeah, absolutely. So I would say I've spent most of my career really focusing on the intersection of technology, healthcare operations and innovation. So I started early in my career predominantly focused on how I could support health grant health plans in their growth journey. But over time I really started to see how much growth was hampered by just the high level of misalignment and administrative friction in the healthcare system. So that experience has really drawn me a little bit more towards building systems that make healthcare really work the way it should, which to me is more transparent, more predictable and more efficient. Earlier today I lead our product organization, which means I spend most of my time really thinking about how AI and data can simplify the complexity across the payment ecosystem. Our goal at Lyric is to turn really what used to be more of a adversarial, audit and recovery driven part of the industry into one that's powered a little bit more by shared intelligence and trust across the payer and plan dynamic. So for Lyric, our North Star is pretty simple, I would say. Accuracy to us builds alignment and alignment is really what's required to get trust. And when trust exists, simplicity really follows from that. And that is our goal at Lyric is to simplify the business of care.

[A]

I'm sure we'll talk about that trust here in a little bit too. I think that's an important conversation to have. In the context of our conversation today. You choose a very fitting image, at least in my opinion, to describe today's healthcare tech landscape. You sort of compared it to a battleground with organizations really arms racing to deploy AI driven innovation. There's so much happening, it's so busy. From your perspective today, what's fueling all of this competition and how is it shaping the experience for both organizations and patients?

[B]

Yeah, absolutely. I mean, to me it really does feel like an arms race. And if we look, look back at history, most arms races at their core are Fueled by a lack of trust. And I don't think anybody would ever say that the relationship between a health plan and a provider, the word trust does not come to mind very often. So we really see this and hear this a lot from our customers. Health plans and providers are both very worried that the other is going to get the upper hand when it comes to the payment ecosystem and process. So they're both trying to add more and more to their arsenal to keep up with that. And currently health plans, providers, startups, everyone is trying to do that in an AI first way. So very exciting the adoption of AI, but the way it's being done is really starting to fragment the landscape a lot more. So each side is starting to build their own tools, they're using their own data models, and they're really defining their own definition of truth, which instead of building bridges, which we'll talk about, is really starting to build more silos across, you know, what's already a very fragmented system. So what comes of all of that is a lot of duplicated work, added administrative burden, and both kind of go back and forth with their new and different tools and then really is just fueling even more mistrust than was was already there. And all of that is distracting from really what the core of healthcare should be, which is delivering better, more affordable care for patients. But I think, we really think we're at a turning point where technology has now matured enough that we can actually start creating trust by design. And so what I mean by that is if we think about advances in AI, blockchain and different privacy preserving computation, it's really making it so we can build a system that can almost create trust in the technology itself versus across the human component of that. And that's going to be really important when we think about two sides that inherently don't trust each other and how we could build it into a more sustainable framework. So that's really what we're looking forward to, is how technology could enforce fairness automatically and really become a foundation for greater collaboration in the industry.

[A]

I want to touch on the systemness that you mentioned earlier here and your point that you just made, because again, you've also sort of pioneered a concept called trusted intelligence zones, which is by its very nature a concept, a system. Can you walk us a little bit through what that means for you and why it's important to where we are today?

[B]

Definitely, yeah. So to us, a trusted intelligence zone really by definition is a secure, neutral layer where health plans and providers can collaborate more without giving up Control of what's important to them, which is typically their data, is a very important part of that. So what it does is it combines AI driven mediation with blockchain accountability and really privacy driven governance to make every decision transparent and verifiable by both sides. So almost think of it as a digital trust fabric where instead of both sides sending files and data back and forth and debating whose data is right and then, you know, back and forth more on that, everyone's getting to see the same validated insights in real time without over having to overshare their proprietary information, which is really going to be critical to any sort of success when two sides aren't inherently trusting each other. So really what we're trying to get to is where fairness is literally built into the architecture of the technology and every transaction is traceable, every model, every model is explainable and everyone is really operating within the same guardrails that they get to be part of the design when they build it. So this is really going to hopefully turn an arms race into more of a collaborative environment. Because right now trust is really what's stopping us from really achieving what we could in the, in the world of simplification.

[A]

Yeah. And it also, you mentioned silos earlier in the conversation. It can help eliminate those silos to be a little bit more effective. And at the end of the day, again, that's a lot of the conversations around AI are being used to. How, how are we strengthening payment integrity and transparency? Right. And then also, obviously administrative burden is such a big part of this conversation. How is it helping reduce administrative burden and create more consistent and then also equitable payment outcomes across the industry? When we talk about a. Yeah, we.

[B]

See AI as completely redefining payment integrity. So if you think about traditional payment integrity as it's defined, really what it was was finding a lot of inaccuracies after payment was already processed through very manual retrospective audits that often created a lot of tension between health plans and providers. And now we're shifting towards more of a world where we can detect more before the issue even happens and get it to happen even closer to the point of care, really simplifying the process for everyone that's involved and reducing a lot of the administrative back and forth that's really been created by the way the process was defined. So at Lyric, what we're trying to do is build AI that works hand in hand with the human expertise that is critical to this industry. With our models being able to flag really almost in real time, coding inconsistencies Predict certain denials earlier in the process and then surface anomalies to create more of that transparency and education between health plans and providers. And what that means is overall, hopefully fewer audits, fewer appeals and far less friction between both sides ultimately still getting to a very similar outcome. So we think it will bring a lot more consistency to the way payment integrity is done. So if you think about it, AI can be a lot more consistent than different human, different companies, etc, trying to apply similar types of standards. And then lastly, we just think it will be able to reduce the number of manual touch points. So we're freeing people to focus on the most complex issues versus having them repeatedly do kind of the low hanging fruit which is what the industry has traditionally focused on because of the constraints of, of humans.

[A]

Yeah, absolutely. One thing that we, we touched on again is the trust piece. What we haven't touched on yet is, is alignment. Right. I think we've talked about it a little bit here, how important alignment is across, across organizations, across stakeholders, to be able to really operationalize this and scale it. Certainly as we're seeing this happen as healthcare becomes more data driven again, accuracy, alignment between payers and providers is very critical. Specifically when you're looking to 2026 and probably also beyond what are some of the biggest opportunities to build more collaboration and trust across the ecosystem.

[B]

Yeah, I think 2026 is shaping up to me to be a big year for healthcare. And why I say that is kind of three big forces that I see that will start to converge a bit more. So the first is really around policy and what's being called data liquidity. So we are really seeing from a regulatory perspective a really hard push for interoperability and transparency, which means standardizing data is no longer optional, it's almost going to become a requirement. And this is by far the most tech forward administration we have seen in a long time, and that's helping drive a lot of that. Second is really what we've already started to see from providers, which is an adoption of AI into everything that's being done. And a lot of that's due to headwinds, financial pressures, et cetera. But providers have taken a far quicker path to adopting AI in both clinical usage as well as rev cycle. And then third, we're starting to see it's always been there, but another heightened area where both consumers and employers are demanding a lot more clarity in where their money's going and why and how it's being used. And they want to have answers to that in a lot faster way. So really, we see that these trends are going to push for a lot more required collaboration across the ecosystem and to make things work. And so we think this is now the time for really creating that, that data collaboration to drive shared intelligence. And that's really going to be, to me, the most important of, of 20 trend of 26. So, you know, when, when we can get that data and get that intelligence, then we can start addressing the trust problem, which if we don't get there, we're always going to be constrained. And, and so I really think that's going to be the biggest part of 26.

[A]

Certainly a lot to consider for organizations. Brian, it's so great to have you on. So many great insights here and again, so many things to think about for organizations. I want to turn the floor over to you here as we close out. Anything else that we didn't touch on that you want to mention that might be important for our audience?

[B]

No, I think just the last point I'd close with is, and just reiterating, really, we think trust and safety are the next frontier of innovation. So as people are out there thinking about that, you know, we spent years building automation that is fast, efficient and scalable. But this next chapter is all going to be about what's accountable, explainable, and fair. So, you know, when we talk this time next year, the true leaders aren't going to be the ones with the flashiest AI tools. They're going to be the ones who are really designing their ecosystems to have that trust and accountability into what they're doing. And that's, that's kind of the, the path we're taking at Lyric as well. So I think that's the last piece I close with is as people continue to adopt AI, don't forget that trust and safety component is going to be critical and especially in healthcare.

[A]

And I'm certainly looking forward to having this conversation again in 2026 to see where we're at.

Brian, it's, it's so great to have you. Thanks so much for being here and all of your insights.

[B]

Absolutely. I enjoyed it.

[A]

And we also want to thank our podcast sponsor, Lyric. You can tune into more podcasts from Becker's Healthcare by visiting our podcast [e-mail].