MISMO Mic'd Up: Beyond the Standards

Brian Vieaux, President MISMO
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MISMO Mic’d Up: Beyond the Standards brings you inside the work that quietly powers the housing finance ecosystem. Hosted by Brian Vieaux, President of MISMO, each episode features candid conversations with lenders, servicers, technology providers, regulators, and long-time MISMO volunteers who are building the data standards our industry runs on. You’ll learn: How MISMO workgroups actually operate Where standards reduce friction, risk, and cost How emerging tech (AI, POS, eClosing, consumer-permissioned data) connects to MISMO Practical ways to plug your team into the work

  1. 4 days ago

    MISMO Community Update: MCD Adoption, AI Governance and What’s Ahead

    Standards create value when the industry puts them to work. In this episode of MISMO MIC’D Up, MISMO President Brian Vieaux launches a monthly community update focused on the initiatives moving forward across MISMO and what they mean for lenders, technology providers, and the people responsible for implementation. Brian covers growing momentum around the Mortgage Compliance Dataset (MCD), evolving AI governance expectations, and preparations for the 2027 MISMO Winter Summit in New Orleans. Throughout the episode, he offers practical steps companies can take to prepare, participate, and help turn collaborative work into operational improvements. MCD adoption: A direct call to LOS providers Brian opens with a refresher on MCD and its purpose: giving lenders and state examiners a common structure for exchanging the loan data used in compliance examinations. Developed through collaboration among MISMO, the Conference of State Bank Supervisors, regulators, lenders, and technology providers, MCD aims to reduce the repeated work of assembling, translating, and correcting examination data. He discusses California’s planned pilot and Iowa’s move to accept MCD files, explaining why these developments raise the urgency around technology readiness. His message to loan origination system providers is direct: lenders need the ability to produce MCD files and a clear implementation timeline. For lenders, Brian outlines questions to ask about system capabilities, data mapping, integrations, and testing. He also encourages direct conversations with state regulators and participation in the MCD Development Workgroup. AI governance: Connecting policy to everyday operations Brian reviews Fannie Mae’s October 21 update and the practical questions lenders should be addressing: Where is AI being used? Who owns each use case? How is risk evaluated? What AI is embedded in vendor products? And how does the organization demonstrate ongoing oversight? He explains how **MISMO’s FRAME—Framework for Responsible AI in the Mortgage Ecosystem—**provides a foundation lenders can adapt to their businesses while retaining responsibility for implementing controls and demonstrating that they work. Brian also previews the November 18 webinar at noon Eastern, which he will moderate with James Brody, Suha Zehl, and Brooke Anderson Tompkins. The discussion will compare Fannie Mae’s and Freddie Mac’s AI governance requirements, explore legal and operational considerations, and connect FRAME with GSE expectations and CSBS guidance. Winter Summit: Bring your implementation questions to New Orleans Looking ahead to January 11–14, 2027, Brian previews a four-hour AI Governance Workshop designed to give lenders hands-on experience with implementing and managing their programs. He also highlights planned workgroup discussions on standardizing tri-party eNote bailee language, reducing friction in eNote adoption, and advancing MCD adoption and potential future expansion into state-specific testing and additional loan products. Who should listen: Mortgage executives, compliance and risk leaders, LOS and compliance technology providers, operations teams, warehouse lenders, investors, and capital markets professionals. The invitation: Ask your LOS provider about MCD readiness, bring your colleagues to the November 18 webinar, and join the MISMO community in New Orleans prepared to contribute.

  2. 29 Oct

    Rethinking Credit Data Early

    Rising credit costs are prompting lenders to rethink a familiar habit: pulling a full credit report at the first interaction with a prospective borrower. What information does a lender actually need at that moment—and when does it make sense to invest in more? In this episode of MISMO Mic’d Up, host Brian Vieaux, President of MISMO, welcomes Reno D’Water, Chief Innovation Officer at Factual Data, for a practical conversation about credit data, borrower engagement, and managing expenses throughout the origination process. Brian and Reno explore how lenders can rethink the sequence of credit-related purchases, beginning with identity verification and early insight into a consumer’s credit profile. Reno describes Factual Data’s approach to helping lenders configure workflows around their own processes, with the goal of purchasing the information they need when they need it. The discussion connects those operational decisions to a broader challenge: reducing unnecessary expense while helping consumers understand their next steps toward homeownership. Topics covered include: Getting the first interaction right. Why validating consumer information early can help lenders identify data quality issues before they create rework, delays, and additional costs downstream. Matching credit information to the borrower’s stage in the journey. Reno explains Innovis Early View, which he describes as a low-cost soft pull providing identity verification and credit trade data without a credit score, and how lenders can use that information to guide the next step. Managing credit spend through sequencing. How lender-configured workflows and decision parameters can help determine when to obtain additional reports and deeper insight. Keeping information current through closing. Reno discusses refreshing a credit file or an individual tradeline through Innovis, with the aim of reducing repeated purchases of full credit reports as information changes. Preparing for credit score modernization. A discussion of Classic FICO, VantageScore 4.0, and FICO 10T, including the questions lenders are weighing as they evaluate their options and operational readiness. Connecting automation with personal attention. Reno describes the Innovis Early View integration with Blend, including how messaging can help direct loan officers toward situations that require additional review and a conversation with the consumer. Strengthening identity verification at the front end. How confirming a consumer’s presence in a transaction and using prefilled information could support data quality and help address challenges in direct-to-consumer channels. The conversation also highlights MISMO’s role as a neutral forum for industry collaboration. Reno shares why bringing lenders, credit providers, technology companies, and the GSEs together matters when translating industry change into workable processes. Brian encourages lenders to engage with MISMO’s Credit Community of Practice—even if their first step is simply to listen and learn. Reno closes with a practical starting point for lenders: revisit the first interaction with the consumer. Examine how identity is validated, how data enters the process, and what triggers the next purchase of information. For lending executives, operations and credit leaders, technology teams, and loan originators, this episode offers a useful perspective on how better data and more deliberate workflows can support cost control and a more informed borrower experience. MISMO. Where Our Industry Builds What’s Next.

  3. 22 Oct

    Beyond the Next Loan: Building Trust, Community, and Influence

    Loan officers are on the front lines of homeownership every day. They answer the questions, work through the challenges, and help consumers make some of the biggest financial decisions of their lives. What more can we do as an industry to equip them for that responsibility? In this episode of MISMO MIC’D Up, Brian Vieaux welcomes Dave Savage, Co-Founder of FirstHome IQ, and David Upbin, VP of Education at the Mortgage Bankers Association, to discuss the recently announced launch of MBA Homebase. Introduced at MBA’s Annual Convention, Homebase brings together education, coaching, market insights, and advocacy to help loan officers strengthen their businesses and become more valuable resources in their communities. David shares how the initiative came together, from early conversations about serving loan officers more directly to the collaboration between MBA and FirstHome IQ. Dave explains the vision behind that partnership: equipping loan officers to become financial literacy first responders who can build trust, have meaningful conversations about money, and help consumers prepare for homeownership well before they are ready to apply. The conversation explores a challenge many originators will recognize. As the economics of mortgage lending have changed, access to dedicated coaching and production leadership has become uneven. Brian, Dave, and David discuss how Homebase aims to help fill that gap through a community built around practical education, shared experience, and ongoing professional development. Topics covered include: - What MBA Homebase includes. A look at the annual subscription, including eight hours of federal continuing education, a choice of four vetted CE providers, monthly coaching, and access to MBA research and advocacy information. - Turning market intelligence into useful conversations. How MBA’s economic research and policy expertise can help loan officers communicate more effectively with borrowers, real estate agents, and other referral partners. - Building trust through financial education. Why FirstHome IQ’s approach starts with helping loan officers improve their own knowledge and ability to explain the financial decisions surrounding homeownership. - Playing the long game in your community. The value of reaching students and future homebuyers years before a transaction, and why serving those audiences matters. - Expanding the loan officer’s voice. How participation in the Mortgage Action Alliance and advocacy at the state and federal levels can connect everyday lending experience to the policies shaping housing. - Growing a community of engaged professionals. Dave and David discuss their ambition to reach 25,000 loan officers and what that level of participation could mean for consumer education and industry advocacy. We also clarify how participation works: MBA membership is held at the company level, and loan officers employed by member companies can access Homebase for $150 per year. The annual price for those at nonmember companies is $300. For loan officers, branch managers, and mortgage executives, this conversation offers a practical look at an initiative designed to support the people consumers rely on throughout the homebuying process. It is also an invitation to get involved, share the opportunity with your team, and help more loan officers bring education and advocacy into their everyday work. Learn more about MBA Homebase:[www.mba.org/industry-resources/mba-homebase](https://www.mba.org/industry-resources/mba-homebase)

  4. 17 Oct

    Down Payment Assistance Needs a Common Language

    Down payment assistance can help put homeownership within reach. But connecting a prospective buyer with the right program often requires lenders and loan officers to navigate information that is difficult to compare, exchange, and incorporate into their everyday workflows.In this special edition of MISMO MIC’D Up, Brian Vieaux, President of MISMO, welcomes Rob Chrane, Founder and CEO of Down Payment Resource, to discuss a proposed initiative to standardize the foundational data describing down payment assistance programs.Building on Rob’s HousingWire article, “Down payment assistance doesn’t need simplification; it needs standardization,” the conversation explores how a common data specification could help lenders, technology providers, and program administrators work together more effectively while preserving the different requirements and purposes of individual programs.Rob explains why the challenges surrounding DPA extend beyond awareness and education. Even when assistance is available, operational friction can keep it from becoming part of the borrower conversation. Loan officers need an efficient way to access and use program information, and the systems supporting them need a consistent way to exchange it.The proposed scope is deliberately focused. Rob describes a vendor-neutral foundation covering basic program information, including repayment terms, first-time homebuyer definitions, funding status, eligible property types, geographic coverage, and permitted uses of assistance. The effort would preserve proprietary eligibility algorithms, decisioning logic, and program maintenance methods while creating a more consistent foundation for information exchange.Brian and Rob discuss:Where DPA opportunities fall through the cracks. Why education matters, but cannot resolve every obstacle lenders and loan officers encounter when trying to use assistance programs.What a common data standard could accomplish. How consistently describing program characteristics could support better connections between DPA information and mortgage technology.Why an initial specification should stay focused. The importance of identifying a manageable set of data and a practical first deliverable that participants can implement.How to support borrowers earlier. Why geographic information should accommodate both a specific property and a prospective buyer who is still deciding where to purchase.How existing MISMO work could contribute. Brian discusses the potential to build on the Reference Model, Business Glossary, and lessons from the Housing Counseling Dataset.Who needs to help shape the effort. Why lenders, loan officers, LOS and POS technologists, housing finance agencies, state and municipal housing authorities, and other program administrators all bring essential expertise.The episode also explains where the proposal stands. Rob is gathering expressions of interest to support a formal MISMO work request. This is an early opportunity to help shape the initiative ahead of MISMO’s review process and a potential formal call for participation.As Rob puts it: “Lend us your name, not your calendar.”If your organization administers assistance programs, builds mortgage technology, or helps homebuyers access financing, this conversation is an invitation to contribute. Reach out to Rob or Brian to express interest and share the experience you could bring to developing a practical DPA data standard.

  5. 15 Oct

    Can You Trace It Back? Building Trust in AI-Powered Mortgage Lending

    How can mortgage lenders use AI to reduce the cost of manufacturing a loan while preserving the evidence behind the work it performs? In this episode of MISMO Mic’d Up, host Brian Vieaux welcomes Steve Butler, CEO of TRUE, a MISMO member company, for a practical conversation about mortgage automation, data quality, and AI governance. Together, they explore how lenders can identify near-term operating improvements while establishing the oversight and traceability needed to support responsible adoption. Steve begins with the loan file itself, explaining how TRUE’s Mortgage Operations Service handles document classification, data extraction, validation, and condition clearing. He describes how automating these tasks can reduce repetitive work for processors and quality control teams, creating capacity for more complex issues and borrower interaction. Brian and Steve also discuss Steve’s distinction between the “coarse dial” of broader operational transformation and the “fine dial” of targeted improvements that lenders can pursue sooner. Steve shares his perspective on the potential savings from document and data automation and how lenders might use those savings to compete for borrowers. The conversation then turns to accountability. Drawing on the Massachusetts student-lending enforcement case, Brian and Steve discuss why mortgage executives should pay attention to AI developments in adjacent financial industries. Brian highlights an important distinction: automating document processing and using AI to make lending decisions involve different risks. The connection between them, however, is the data supporting the decision. To make traceability tangible, they follow an income figure from a borrower’s document into the loan origination system and consider what a lender would need to produce if that figure were challenged a year later. Steve explains TRUE’s approach to combining generative AI with deterministic validation methods, which he describes as a “chain of trust,” and discusses preserving data lineage as documents and information change. They also examine what meaningful human oversight looks like. Steve outlines TRUE’s approach to passing qualifying data through automatically while routing exceptions for review, and explains why reducing manual checking still requires executive attention to governance. Topics include: Where document and data automation can reduce friction in loan manufacturing. How targeted workflow improvements differ from multiyear transformation projects. Why AI risk should be evaluated by use case. What lenders should be able to trace from a data point back to its source. The roles of automated validation, exception review, and executive oversight. How vendors can bring governance into sales and implementation conversations. How MISMO’s FRAME can help smaller and mid-sized lenders organize their governance efforts. Brian and Steve close with a practical starting point: evaluate the data foundation, establish the current cost and time required to prepare a reliable loan file, and decide what evidence must be preserved before expanding automation. For lending executives, operations leaders, risk professionals, and technology teams, this episode offers a concrete discussion of how efficiency and accountability can advance together. Learn more about TRUE at https://true.ai and MISMO’s work on AI governance and industry standards at https://www.mismo.org.

  6. 9 Oct

    Putting FRAME to Work: Two Lenders Share Their AI Governance Playbook

    Everyone is talking about AI governance. What does itactually take to build a program inside a mortgage company? In this episode of MISMO MIC’d Up, host Brian Vieauxwelcomes Nicole Taylor of Longbridge Financial and John Ashley of PRMG for acandid conversation about their firms’ AI governance journeys. Both share thedecisions, challenges, and practical lessons behind their programs—includingwhere MISMO’s FRAME helped them move forward and where the work is stillunderway. Nicole explains how Longbridge began by identifying the AItools already operating in its environment, understanding how employees wereusing them, and moving widely used tools into enterprise arrangements. She alsodraws an important distinction between Longbridge’s Center of Excellence, whereemployees share useful applications and ideas, and the governance processresponsible for evaluating risks and overseeing adoption. John describes PRMG’s experience building a governancestructure as requests for AI tools multiplied. Early proposals moved betweendepartments without a clear path to a decision. Bringing digital marketing,cybersecurity, vendor management, and legal together helped establish ownershipand move reviews forward. He also shares a practical communication lesson: anacceptable use policy needs guidance employees will actually read andunderstand. Throughout the conversation, both guests are transparentabout the difference between having an inventory and completing the work ofassessing risk. John discusses PRMG’s backlog of existing use cases requiringreview, even as the company establishes a more structured intake process fornew requests. Nicole explains how FRAME helped Longbridge recognize the need tomore deliberately document risks across both vendor products and internal AIusage. Topics include: • Finding AI already in use, including employee tools andcapabilities embedded in vendor products.• Using existing technology to discover usage and start constructiveconversations with employees.• Defining the scope of an AI governance program and prioritizing reviews.• Establishing clear responsibilities across business, technology, legal,compliance, and vendor management.• Addressing vendor contract language concerning the use of company data formodel training.• Translating governance policies into practical employee guidance.• Managing the resource demands of risk assessments and enterprise AI access.• Applying FRAME’s governance policy template and risk assessment tools to eachfirm’s needs.• Securing executive support and deciding what to tackle in the first 30 days. The guests describe how FRAME provided an accessiblefoundation for their work. For Longbridge, it offered a way to check anexisting policy draft and strengthen its approach to risk documentation. ForPRMG, it helped clarify governance responsibilities and structure theassessment process. Their experiences show how firms can build from a sharedfoundation while adapting their programs to their business models and risktolerances. A central theme runs through the discussion: a cleargovernance process can help organizations evaluate AI more efficiently, maketimely decisions, and give employees a practical path to responsible use. Whether your organization is getting started or refining aprogram already in motion, this episode offers a detailed look at the workinvolved—and concrete lessons from two leaders willing to share what they havelearned. Learn more about FRAME at mismo.org.

  7. 2 Oct

    From Rate Lock to Loan Sale: Data, AI and Human Accountability

    More data. Faster technology. The same fundamental objective: protect mortgage margins from rate lock through loan sale. How can capital markets teams use standardized data and artificial intelligence to make better decisions—and maintain confidence in the outcomes? In this episode of MISMO Mic’d Up, Brian Vieaux welcomes Fuad Nasir, Vice President of Product Management for Hedging and Trading at Optimal Blue. Building on their conversation at the MISMO Fall Summit in Reston, Virginia, Brian and Fuad explore the connection between consistent data, transparent workflows and responsible AI across the mortgage capital markets life cycle. With roughly 20 years of experience in mortgage hedging, trading and analytics, Fuad shares his focus on connecting front-end pricing with hedging, loan sales and servicing values. He explains how greater visibility across those activities can help capital markets professionals understand risk, identify margin leakage and carry decisions through execution. The conversation returns to a foundational point: AI needs consistently defined data to support decisions people can trust. When systems rely on different definitions or repeated manual translations, teams spend more time reconciling information and have less confidence in the inputs driving their analysis. Brian and Fuad discuss how MISMO standards provide a common vocabulary that helps systems communicate and supports closer alignment among lenders, technology providers and investors. They also examine what responsible AI means when decisions carry real financial consequences. Fuad emphasizes explainable insights, repeatable processes, monitoring and auditability, alongside clear human accountability. Automation can help professionals identify changes and evaluate options, but teams still need the expertise and controls to challenge an output and determine when to act. Brian adds a personal reflection on using AI to summarize information, raising a broader question: how do we capture the efficiency of these tools while preserving the understanding and judgment needed to use them well? Topics include: • Connecting pricing, hedging and execution to support margin protection.• Reducing reconciliation and manual data translation across systems.• The role of MISMO standards in creating consistent context for analytics and AI.• Improving visibility into risk and performance throughout a loan’s journey.• Keeping human oversight and accountability central to automated workflows.• Avoiding overreliance on AI at the expense of professional judgment. The episode closes with a preview of the 2027 Optimal Blue Summit, scheduled for February 1–3 in Scottsdale, Arizona. Fuad shares what clients can expect, including hands-on learning, capital markets discussions, access to product teams and opportunities to help shape future technology. For capital markets leaders, mortgage executives and technology professionals, this conversation connects the promise of AI to the data quality, controls and expertise that make it useful.

  8. 24 Sept

    Solving Mortgage Friction - 1 Issue at a Time

    There’s a cost to solving the same mortgage problem company by company, over and over again. It shows up in repeated data requests, time spent negotiating agreements, disconnected systems, and uncertainty about how to govern new technology. In this solo episode of MISMO Mic’d Up, MISMO President Brian Vieaux explores how the industry’s standards community brings lenders, technology providers, regulators, and other stakeholders together to address those shared challenges. Building on his recent HousingWire Daily conversation with Sarah Wheeler, Brian connects four areas of MISMO’s work to the practical decisions mortgage companies face. FRAME and practical AI governance Brian explains how FRAME helps companies organize their approach to AI through a governance policy template, an inventory, and a risk assessment tool. He discusses why that inventory needs to account for AI embedded in vendor products and the “shadow AI” employees may already be using. For companies getting started, his advice is straightforward: bring the people doing the work into the conversation, understand how AI is being used, and assign responsibility for keeping the governance process current. The Mortgage Compliance Dataset and examination efficiency The Mortgage Compliance Dataset, or MCD, emerged from a challenge shared by state regulators and lenders: exchanging loan data consistently for examinations. Brian shares how CSBS and Rocket brought different perspectives on that problem to MISMO, and how collaboration led to a common dataset. He explains the opportunity to reduce repeated formatting and data rework, while emphasizing that the benefits depend on implementation by lenders, regulators, and technology providers. Credit data and MISMO’s responsibility to stay neutral As the industry debates credit scoring models, reporting configurations, cost, and risk, MISMO’s role centers on the data needed to support those products. Brian explains why neutrality matters when bringing competitors together and how common data standards can help information move between systems with its meaning intact. eNotes and the agreements that affect adoption Digital mortgage adoption also depends on how easily trading partners can establish working relationships. Brian discusses the tri-party eNote bailee agreement and the effort to develop common starting language that could reduce repeated negotiation, support more consistent onboarding, and expand trading options for lenders originating eNotes. He encourages digital closing teams to include capital markets and warehouse partners when identifying what is slowing adoption. Throughout the episode, Brian recognizes the people contributing their time and experience to this work and connects their efforts to MISMO’s priorities of Awareness, Adoption, and Alignment. His closing challenge: choose one issue that creates friction in your business, bring it to the colleague who deals with it, and explore how your organization can use or contribute to the work underway. Learn more about MISMO’s resources and opportunities to participate at [MISMO.org](https://www.mismo.org).

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MISMO Mic’d Up: Beyond the Standards brings you inside the work that quietly powers the housing finance ecosystem. Hosted by Brian Vieaux, President of MISMO, each episode features candid conversations with lenders, servicers, technology providers, regulators, and long-time MISMO volunteers who are building the data standards our industry runs on. You’ll learn: How MISMO workgroups actually operate Where standards reduce friction, risk, and cost How emerging tech (AI, POS, eClosing, consumer-permissioned data) connects to MISMO Practical ways to plug your team into the work

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