PiTech Solutions Podcast

PiTech Solutions
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The PiTech Solutions Podcast delivers expert insights at the intersection of banking, government, and emerging technology. With CMMI Level 3 certification, ISO credentials, and an 11-year track record with Fortune 500 financial institutions, PiTech brings government-proven methodologies to help regional banks compete, comply, and transform. Tune in for conversations on AI, cloud strategy, data analytics, and the future of financial services technology.

  1. 3d ago

    Capital Markets: AI Governance, Surveillance and Tokenization | PiTech Solutions Podcast

    Capital Markets: AI Governance, Surveillance and Tokenization This week Mike and Laura turn to capital markets, where artificial intelligence is reshaping regulation, trading surveillance, and market infrastructure all at once. From a new global supervisory framework to a live tokenization deal announced this week, the episode covers where oversight stands and where it is headed next. The hosts open with the International Organization of Securities Commissions, which published its Supervisory Toolkit for AI Use in Capital Markets in May 2026. Built around three layers of risk areas, oversight tools, and monitoring indicators, the toolkit gives securities regulators a working framework for governing traditional machine learning, generative AI, and emerging agentic systems. Next, Mike and Laura look at what AI surveillance looks like in practice, using Nasdaq's own results from an eight month pilot with Saudi Arabia's Capital Markets Authority, where AI powered anomaly detection sharply improved pump and dump scheme identification. That surveillance technology now reaches thousands of financial services clients and the large majority of the world's most systemically important banks. The conversation then turns to Nasdaq's newly announced investment in Payward, the parent company of Kraken, deepening a tokenized equities partnership with a planned launch date in 2027. The hosts discuss why exchange operators are increasingly pairing product innovation with surveillance infrastructure rather than treating them as separate tracks. The episode closes with FINRA's 2026 Annual Regulatory Oversight Report, which finds member firms adopting generative AI mainly for efficiency gains while flagging real risks around autonomous AI agents and the difficulty of auditing multi step decisions. To learn more about PiTech Solutions and how we help regulated industry leaders navigate technology change, visit us at pitechsol.com. #CapitalMarkets #ArtificialIntelligence #RegTech #FinancialServices #MarketSurveillance

  2. Sep 4

    Banking - Regulators Leave the AI Rulebook Blank | PiTech Solutions Podcast

    Banking - Regulators Leave the AI Rulebook Blank | PiTech Solutions Podcast Banks are running artificial intelligence at enormous scale. Federal regulators have just gone out of their way to say that the newest and most powerful category of that technology sits outside their model risk rulebook. This week Mike and Laura unpack that tension and what it means for anyone accountable for governance in a regulated institution. AI at production scale. Bank of America reports more than three hundred approved AI and machine learning use cases, including one hundred fourteen live generative AI use cases with thirty four fully deployed. On the second quarter earnings call, CEO Brian Moynihan said more than two hundred thousand employees use AI enabled capabilities generating over four hundred thousand prompts daily, as reported by Banking Dive and CIO Dive. Jamie Dimon put JPMorgan Chase at almost one thousand AI use cases, and Jane Fraser said nearly nine out of ten Citigroup employees are using the bank's AI tools. The deliberate carve out. On April 17, 2026 the OCC, the Federal Reserve Board and the FDIC jointly issued revised interagency guidance on model risk management, superseding the 2011 guidance. The revised guidance states that generative AI and agentic AI models are novel and rapidly evolving and are not within its scope. The agencies said they plan to issue a request for information addressing model risk management generally and considering, in particular, banks' use of AI. The guidance is expected to be most relevant to banking organizations with over $30 billion in total assets, and the OCC was explicit that it sets no enforceable standards and that non compliance will not result in supervisory criticism. Supervision follows the same logic. On August 27, 2026 the OCC and the FDIC issued a final rule establishing a uniform definition of unsafe or unsound practice, directing examiners to prioritize material financial risks over policies, process and documentation, and setting a uniform standard for Matters Requiring Attention. An MRA now requires a practice contrary to generally accepted standards of prudent operation that could materially harm the bank's financial condition or present a material risk of loss to the Deposit Insurance Fund, or an actual violation of law. And a new competitor. In August 2026 the FDIC approved the deposit insurance application for Augustus National Bank, a proposed national bank in Dallas, Texas built to serve digital asset companies, artificial intelligence companies, technology companies, high net worth individuals and international financial institutions, with a tier one leverage ratio condition of no less than ten percent through its first three years. The through line: discretion has moved back to the institution. An empty rulebook is not permission. It is an invitation to write the standard yourself and be ready to show your work. To learn more about PiTech Solutions and how we help regulated institutions build governance that holds up under examination, visit pitechsol.com. #BankingAI #ModelRiskManagement #RegTech #AIGovernance #FinancialServices

  3. Aug 28

    FinTech - Stablecoin Rulemaking, Tokenised Deposits and the AI Governance Gap | PiTech Solutions Podcast

    FinTech - Stablecoin Rulemaking, Tokenised Deposits and the AI Governance Gap Three stories this week, three different corners of financial technology, and underneath all of them the same theme: the plumbing of the industry is being rebuilt while the rulebook for that plumbing is still being written. For executives in regulated institutions, that combination is the whole strategic problem, and this episode works through what to do about it. Mike and Laura open on the biggest regulatory development of the month. On August 17, 2026 the U.S. Department of the Treasury issued a Notice of Proposed Rulemaking implementing section 3 of the GENIUS Act, published the next day in the Federal Register with a comment period running to October 19, 2026. The hosts walk the two-stage timeline that matters to a board: licensing requirements expected to take effect January 18, 2027, and then a second, later gate under proposed section 1523.3(a) beginning July 18, 2028, after which digital asset service providers may not offer or sell a payment stablecoin to someone in the United States unless it came from a permitted issuer or a qualifying foreign one. As Laura puts it, that is a supply chain question rather than a legal department question, and it needs a running control rather than an annual attestation. The second story is the plumbing in the most literal sense. On August 19, 2026 Standard Chartered and HSBC executed the first live tokenised deposit transaction on Swift's blockchain-based ledger, with seventeen banks from six continents preparing to pilot live transactions on the shared ledger. The hosts dig into why Swift's own framing matters most: this is an orchestration layer that lets funds move overnight and on weekends before final settlement completes through existing systems. It is an availability play built on top of correspondent banking, not a replacement for it, and Laura explains why that design choice is exactly what distinguishes it from a decade of bank blockchain consortia that quietly wound down. The third story shifts register. On August 19, 2026 Stripe announced it agreed to acquire OpenRouter, a routing layer that Stripe's own announcement says helps businesses route and optimize token usage across more than four hundred models from more than eighty providers. Bloomberg reported a price of more than seven billion dollars, though Stripe published no purchase price and declined to comment on the figure. The hosts argue the thesis is metering rather than modeling, and trace the second-order consequence for regulated institutions: if models are selected dynamically per request, model risk documentation has to describe a policy rather than a model. That bridges to the segment the hosts flag as the most valuable in the episode. On April 17, 2026 the OCC, in coordination with the Federal Reserve Board and the FDIC, issued updated model risk management guidance that explicitly states generative AI and agentic AI models are not within its scope, with a request for information on bank AI use still to come. Laura is blunt about what that means: the absence of guidance is not the absence of accountability, and no examiner will accept "it was out of scope" when a generative system misfires in a credit decision or a fraud queue. She lays out three concrete moves for a chief risk officer, and explains why agentic systems in particular have quietly crossed the line from model risk into operational risk. To learn more about PiTech Solutions and how we help institutions in regulated industries navigate exactly this kind of change, visit us at pitechsol.com. #FinTech #Stablecoins #TokenizedDeposits #AIGovernance #RegulatoryCompliance

  4. Aug 21

    Health and Life Sciences - Generative AI at the FDA and Europe's New Clock | PiTech Solutions Podcast

    Health and Life Sciences - Generative AI at the FDA and Europe's New Clock | PiTech Solutions Podcast Four developments landed in health and life sciences that every executive in a regulated industry should have on their desk this week. Mike and Laura walk through what changed, what it means operationally, and what belongs on your Monday morning agenda. The through line: AI in this sector has moved out of the pilot phase and into the phase where it is governed, financed, and accountable. The FDA opens the generative AI question. On August 18, 2026, the FDA announced it is seeking public feedback to inform its regulatory approach for generative AI enabled medical devices, issuing a discussion paper and opening a public comment period under docket FDA-2026-N-7874, with comments due by October 19, 2026. Acting FDA Commissioner Kyle Diamantas, CDRH Director Michelle Tarver, and Digital Health Center of Excellence Director Rick Abramson all went on the record the same day. Context matters here: the FDA said in January 2025 that it had already authorized more than 1,000 AI enabled devices through established premarket pathways. This is not an agency meeting AI for the first time. It is an agency confronting a class of model that breaks the assumptions its existing pathways were built on. Europe resets the clock, not the obligation. The EU AI Omnibus entered into force on July 27, 2026, following the Commission's proposal of the Digital Omnibus package on November 19, 2025. Obligations for high risk AI systems listed in Annex III now apply from December 2, 2027, and obligations for high risk AI embedded in physical products under Annex I now apply from August 2, 2028. Laura makes the case that a longer deadline is not a lighter obligation, and that compliance programs which go quiet when a date slips pay for it later in compressed, expensive remediation. Regulators converge before they legislate. On January 14, 2026, the European Medicines Agency and the FDA published a joint document, the Guiding Principles of Good AI Practice in Drug Development, setting out ten principles. European Commissioner for Health and Animal Welfare Oliver Varhelyi described them as a first step of a renewed EU and US cooperation. Shared vocabulary before shared rules is the right order of operations, and mapping your AI governance against those ten principles now, while it is voluntary, is the cheapest version of that work you will ever do. Capital follows conviction. In early August 2026, Pathos AI announced a global licensing agreement with Alphamab Oncology for JSKN016, a first in class TROP2/HER3 bispecific antibody drug conjugate, granting Pathos AI exclusive rights outside mainland China, Hong Kong, Macau and Taiwan. Terms are US$125 million upfront and up to US$2,093 million in milestone payments, and the Pathos AI clinical stage pipeline now includes four assets. The notable part is not the size of the check but its direction: an AI company taking clinical asset risk directly rather than selling software to the companies that carry it. PiTech Solutions helps leaders in banking, insurance, healthcare, and life sciences turn regulatory pressure into durable operating advantage. To learn more, visit pitechsol.com. #HealthTech #LifeSciences #AIGovernance #DigitalHealth #RegulatoryCompliance

  5. Aug 14

    Healthcare - Medicare Pays for AI While Regulators Limit It | PiTech Solutions Podcast

    Healthcare: Medicare Pays for AI While Regulators Limit It American healthcare is doing two opposite things at once. Washington is funneling record dollars into AI enabled technology at the bedside, and at the same time federal and state regulators are writing rules that strip AI of the authority to decide anything about a patient. In this episode, Mike and Laura unpack what that split means for executives in regulated industries. The WISeR Model. The CMS Innovation Center's WISeR Model runs for six performance years, from January 1, 2026 through December 31, 2031, across New Jersey, Ohio, Oklahoma, Texas, Arizona and Washington. CMS describes it as leveraging enhanced technologies such as artificial intelligence and machine learning alongside human clinical review, testing AI assisted prior authorization for 13 medical services deemed low value or vulnerable to fraud, waste, abuse or misuse. Critically, CMS states that all recommendations for non payment are determined by appropriately licensed clinicians. The model survived a Senate resolution of disapproval on July 16, 2026 by a party line vote of 46 to 50. The money side. In the FY 2027 Inpatient Prospective Payment System final rule, CMS finalized a 2.3 percent payment rate increase and expects hospital payments to rise by roughly $2.1 billion overall. Within that, CMS estimates additional payments for inpatient cases involving new medical technologies will increase by approximately $779 million, primarily driven by new approvals for New Technology Add on Payments. STAT News reported on August 13, 2026 that a record number of AI devices qualified for those payments this year, and that researchers warn the incentive could drive overuse. Because add on payments last only two or three years after a technology reaches market, any business case built on them is a two to three year business case. The states are moving faster than Washington. Washington's SB 5395 (effective June 11, 2026), Iowa's HF 2635 (effective July 1, 2026), Colorado's HB 1139 (effective January 1, 2027) and Alabama's SB 63 (effective October 1, 2026) all converge on the same principle: AI may assist, but it cannot be the sole basis for denying, delaying or modifying care. Alabama goes further and requires insurers to disclose when AI was used in the review process, turning a transparency rule into an audit trail engineering requirement. What the industry actually asked for. Responding to an HHS request for information on AI in healthcare, stakeholders asked for coordination of AI strategy across agencies, implementation and governance support, and evaluation and benchmarking tools. HHS deputy chief AI officer Arman Sharma named the coordination problem plainly: "Too often in government, the right hand doesn't talk to the left hand." Dr. Rick Abramson, director of the FDA's Digital Health Center of Excellence, framed the pace gap: "It's been said that technology evolves on a scale of weeks to months, while regulation evolves on a scale of months to years." The takeaways generalize well past healthcare: treat human in the loop as a compliance primitive rather than a feature, never build a business case on a bridge payment, and build the audit trail before disclosure rules force you to retrofit one. Healthcare is simply early. Banking, insurance and capital markets are next. To learn more about how PiTech Solutions helps enterprises in regulated industries build, govern and scale AI, visit pitechsol.com. #HealthcareAI #RegulatoryCompliance #DigitalTransformation #MedicareInnovation #AIGovernance

  6. Aug 7

    Insurance - AI Governance Becomes Examinable, and Claims Delivers the Return | PiTech Solutions Podcast

    Insurance - AI Governance Becomes Examinable, and Claims Delivers the Return Insurance has crossed a line this year. The question is no longer whether AI works in a carrier environment. It is whether your organization can operate it responsibly, prove that it did, and rebuild the process around it. Mike and Laura unpack the week's most consequential developments for insurance executives and explain why the carriers separating themselves are not the ones with the most advanced models. The pilot to production gap is now visible in the financials. Organizations that have fully integrated AI into operational workflows are nearly four times more likely to report revenue growth than those still piloting, at fifty eight percent versus fifteen percent. Yet seventy nine percent of organizations report adoption challenges, a double digit increase over the prior year. The tooling improved. Legacy infrastructure, fragmented data, and organizational readiness did not. Claims is where the measurable return lives. AI powered claims automation is delivering thirty to forty percent cost reductions per claim, and BCG research shows AI enabled carriers cutting claim resolution time by seventy five percent, from thirty days to seven and a half. Laura argues the cycle time number matters more than the cost number, because a claim that closes in seven days does not become a complaint, does not attract an attorney, and does not sit on the books accruing reserve uncertainty. Governance stopped being aspirational. At least twenty four states plus the District of Columbia have now adopted the NAIC Model Bulletin or substantially similar guidance. The development that changes the character of the obligation is the NAIC AI Systems Evaluation Tool, which gives examiners a standardized approach to reviewing insurer AI governance. Principles based guidance with an exam methodology behind it is a compliance regime. The European deadline has arrived. Annex three of the EU AI Act classifies risk assessment and pricing systems for life and health insurance as high risk, with obligations applying from August second of twenty twenty six and penalties reaching thirty five million euro or seven percent of global turnover. Mike and Laura explain why the NAIC and European frameworks, structurally different as they are, demand largely the same evidence, and why carriers should build one governance capability rather than two compliance projects. Modernization and AI are the same program. With realistic core system replacement running eighteen to thirty six months, the episode closes on why phased migration that unlocks a real AI capability at each stage beats deferring all the value to a distant end state. To learn more about how PiTech Solutions helps carriers and regulated enterprises turn AI ambition into governed, production grade capability, visit pitechsol.com. #InsuranceAI #AIGovernance #ClaimsAutomation #NAIC #InsurTech

  7. Jul 31

    Capital Markets - Tokenization Goes Live, Agentic AI Reaches Production, and the T+1 Clock Starts Ticking | PiTech Solutions Podcast

    Capital Markets: Tokenization Goes Live, Agentic AI Reaches Production, and the T+1 Clock Starts Ticking Two clocks are running in capital markets right now. One is the innovation clock, moving faster than almost anyone predicted. The other is the readiness clock, and that is where most firms are quietly falling behind. In this episode, Mike and Laura unpack four developments reshaping the sector and explain what each one demands of leadership teams in regulated industries. Tokenized securities move from theory to production. The Depository Trust and Clearing Corporation moved tokenized securities into live trading in July 2026, processing real production trades in tokenized stocks, exchange traded funds, and U.S. Treasurys. The limited production rollout expands to full service integration in October 2026. The eligible asset set is deliberately conservative, covering Russell 1000 equities, major index funds, and Treasury bills, and the industry working group behind it spans more than fifty firms including Goldman Sachs, J.P. Morgan, BlackRock, Circle, and Ondo Finance. The broader tokenized real world asset market now sits near $33.8 billion, with BlackRock's tokenized Treasury fund alone above $2 billion. The regulatory picture gets clearer. On January 28, 2026, SEC staff issued a joint statement establishing that tokenization does not change the legal character of an asset. If it was a security before it went on chain, it remains one. Chair Paul Atkins has since set an agenda covering crypto capital raising, digital asset custody, and on chain trading of tokenized securities, with a proposal known as Regulation Crypto in circulation. Full rulemaking across the SEC and CFTC may take up to eighteen months, which is precisely why waiting for final rules is the riskiest option available. Agentic AI crosses from pilot to production. Broadridge put agentic AI into live production across capital markets and wealth management workflows in May 2026, with new clients told to expect up to 30% day one operational cost reduction. Seventy seven percent of the largest global asset managers now run organization wide generative AI deployments, and algo wheel adoption has climbed to 42%. But 63% of buy side firms still lack unified data across front, middle, and back offices, and that fragmentation, not model quality, is the binding constraint on autonomous operations. The crowding paradox. Research covered by Bloomberg on July 1, 2026 suggests a profitable trading signal may now lose half its excess return in roughly eighteen months, down from five to seven years before AI became widespread. New York University researchers studying nearly one million institutional fund holdings found portfolios growing measurably more similar as AI adoption spreads, most sharply among the heaviest users. Mike and Laura discuss what that means for where competitive advantage actually lives, and why AI governance is now a risk control rather than a compliance checkbox. T+1 arrives in the UK and Europe. Go live is October 11, 2027, but the date executives should have circled is December 31, 2026, when trade allocations and confirmations between buy side firms and executing brokers must complete on trade date. That interim deadline effectively ends next day confirmation as an operating practice, and ESMA has been specific about what it requires: enhanced automation, extended CSD operating hours, improved trade confirmation processes, and coordination across a still fragmented European infrastructure. The connecting thread across all four stories is that automation is no longer optional and the deadlines are now external. Firms no longer set their own pace on modernization. To learn more about how PiTech Solutions helps organizations in regulated industries build the data foundations and automation capabilities these shifts demand, visit pitechsol.com. #CapitalMarkets #Tokenization #AgenticAI #T1Settlement #FinancialServices

  8. Jul 24

    Banking - Agentic AI Reaches Production While Stablecoins and New Model Risk Rules Reshape the Sector | PiTech Solutions Podcast

    Banking - Agentic AI Reaches Production While Stablecoins and New Model Risk Rules Reshape the Sector | PiTech Solutions Podcast This week on the PiTech Solutions Podcast, Mike and Laura unpack the forces converging on banking in 2026, a year when artificial intelligence stopped being an experiment and became a core operating priority. From autonomous agents on the front line to a redrawn regulatory map covering AI, stablecoins, and open banking, this is the strategic briefing that C suite leaders in regulated industries need. Agentic AI moves from pilot to production. With 82% of U.S. banks planning to increase their AI budgets, institutions like BNY, TD Bank, and Commonwealth Bank of Australia are deploying autonomous agents and even naming chief AI officers. The early returns are concentrated in fraud and compliance, where detection agents cut false positives by 60% or more and automation reduces AML and KYC workloads by 30 to 50 percent. The model risk rulebook gets rewritten. The Federal Reserve, OCC, and FDIC issued SR 26-2 in April, superseding the decade old SR 11-7 framework. Notably, it leaves generative and agentic AI outside its formal scope, placing the governance burden squarely on boards and executives. Stablecoins, tokenized deposits, and open banking. The GENIUS Act has made stablecoin strategy operationally unavoidable, with real implications for deposits and lending capacity. Tokenized deposits are emerging as banks' preferred path to modernize payments without losing the customer relationship, while Section 1033 keeps open banking in regulatory limbo. The through line is clear: technology and customer expectations are outpacing regulation, and the winners are building governance and infrastructure now. To learn more about PiTech Solutions, visit pitechsol.com. #Banking #AgenticAI #FinTech #Stablecoins #RegTech

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About

The PiTech Solutions Podcast delivers expert insights at the intersection of banking, government, and emerging technology. With CMMI Level 3 certification, ISO credentials, and an 11-year track record with Fortune 500 financial institutions, PiTech brings government-proven methodologies to help regional banks compete, comply, and transform. Tune in for conversations on AI, cloud strategy, data analytics, and the future of financial services technology.

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  • Creator
    PiTech Solutions
  • Years Active
    2026
  • Episodes
    37
  • Rating
    Clean
  • Copyright
    © 2026 PiTech Solutions Podcast
  • Show Website
    PiTech Solutions Podcast