Heidi Patalano

This session explores how lenders can strengthen relationships with realtors, builders, and other partners by modernizing the way they share data, communicate, and deliver leads. Speakers will discuss technologies that streamline co-marketing, automate status updates, improve lead attribution, and create more seamless borrower handoffs. Attendees will learn which tools actively reduce friction in the referral pipeline, how to evaluate partner-facing platforms, and how better transparency and collaboration can boost conversion rates while deepening long-term partnerships.

This session dives into the challenges lenders, AMCs, and appraisers are experiencing as they transition to UAD 3.6, and how to turn the new standardized data structure into an advantage. Speakers will address practical onboarding issues—training, system integration, workflow redesign—and provide insight into where lenders are getting stuck and how they’re resolving it. Beyond compliance, the conversation will highlight how UAD 3.6 unlocks richer analytics for property insights, risk assessment, QC, and long-term portfolio intelligence, helping organizations use the new data model as a catalyst for operational and strategic growth.

This session focuses on how mortgage lenders are evaluating the business impact of their technology investments amid tighter budgets and ongoing market volatility. Panelists will examine the tools and KPIs that matter most—such as cost per loan, pull-through rate, cycle time reduction, and staff efficiency—and how to build an internal framework for measuring ROI over time. The discussion will help attendees understand which data sources are most reliable, how to align ROI analysis with strategic goals, and how to avoid common pitfalls when evaluating vendor promises versus actual performance.

Many lenders have experimented with AI, but fewer have successfully scaled it across core operations. This session examines how organizations are moving beyond proofs of concept to embed AI into underwriting, processing, quality control, and servicing workflows. Panelists will discuss change management, model governance, data readiness, and integration with LOS and core systems. Attendees will learn what it takes to operationalize AI responsibly, where implementations commonly stall, and how leading lenders are aligning people, process, and technology to drive sustained impact.

AI-driven decisioning tools are transforming credit assessment, income and asset analysis, collateral review, and risk identification. Speakers will dive into how machine learning models are augmenting—not replacing—human judgment, enabling faster decisions while reducing defects and repurchase risk. The discussion will address data integrity, explainability, and regulatory expectations, as well as how lenders are validating model outputs and building trust internally and with investors.

As AI adoption accelerates, lenders face growing pressure to demonstrate tangible business value while managing compliance and reputational risk. This session focuses on how organizations are evaluating the ROI of AI investments, from cycle-time reduction and cost per loan to error rates, staffing efficiency, and borrower satisfaction. Panelists will share how they benchmark success, align AI initiatives with strategic goals, and assess vendor claims versus real-world outcomes. Attendees will walk away with a clearer framework for measuring performance, managing risk, and justifying continued AI investment.