Day One October 26th - PST
- Douglas Harter - Managing Director, BTIG
- Abhinav Asthana - CTO, Redwood Trust
- Pritish Nawlakhe - VP AI Strategy, Kind Lending
- Dan Vasquez - AI Strategy Lead, Rocket Mortgage
- Nik Shah - Chief Executive Officer, 100x
- Alysse Prosnick - EVP, Operations, Angel Oak
- Chuck Iverson - President, Mason-McDuffie Mortgage Corporation
- Ray Yang - Founder and Chief Executive Officer, Termblocks
- Suzy Lindblom - Managing Director, National Operations and Credit, Acra Lending
- Taylor Waldo - Director, Technology PM & Optimization, Prime Finance
- What investment thesis drives your firm's approach to mortgage AI, and how has it evolved given current market conditions?
- Which AI applications in mortgage—fraud detection, appraisal automation, or income verification—are you prioritizing for new investments?
- How do you evaluate regulatory risk and compliance capabilities when conducting due diligence on mortgage AI startups?
- What key metrics and milestones differentiate a Series A-ready mortgage AI company from early-stage point solutions?
- How are you guiding portfolio companies to adapt their AI strategies as origination volumes decline and market dynamics shift?
- Varant Herculian - Director of Customer Success, JazzX AI
A series of interactive small-group networking discussions designed to connect mortgage executives, operations leaders, technologists, investors, and compliance professionals around the industry’s biggest AI challenges and opportunities. Participants will exchange practical insights, deployment experiences, vendor evaluations, workflow strategies, and lessons learned surrounding automation, underwriting, servicing, fraud detection, data infrastructure, and operational scale.
- Alan Qureshi - CEO & Co-Founder, Black Lake Investments
- Steve LaPlante - Portfolio Manager, Mortgage and Structured Finance, Loomis, Sayles & Company
- How are institutional investors using AI to identify relative value opportunities across RMBS, Non-QM, HELOC, MSR, CRT, and other mortgage credit sectors?
- What role is AI playing in prepayment forecasting, delinquency prediction, cash flow modeling, and portfolio surveillance?
- How are investors leveraging AI-driven analytics to improve credit selection, asset allocation, and risk-adjusted returns in volatile rate and housing market environments?
- Can AI meaningfully enhance secondary market liquidity, trading execution, and real-time monitoring of mortgage portfolios and structured products?
- What model risk, transparency, regulatory, and overreliance concerns emerge as investors increasingly depend on AI-generated insights and predictive analytics?
- How will AI reshape competitive dynamics among mortgage REITs, hedge funds, insurers, private credit firms, and institutional fixed-income investors over the next five years?
- Paul Gigliotti - CEO, California Mortgage Bankers Association (CMBA)
- Jonathan Feigelson - Senior Executive Vice-President and Chief Legal Officer, Freedom Mortgage
- Lee Jelenik - EVP, Chief Innovation Officer, United Wholesale Mortgage
- Paula Tuffin - Chief Compliance Officer & General Counsel, Better
- Sheila Oliver - Deputy Commissioner, Escrow & Mortgage Lending, California Department of Financial Protection and Innovation
AI is rapidly transforming every corner of mortgage finance — from underwriting, servicing, and customer engagement to securitization, investing, and risk management. But is the technology genuinely improving the industry, expanding access to credit, and strengthening decision-making — or simply accelerating existing processes while introducing new operational, regulatory, workforce, and systemic risks? In this fast-paced Oxford-style executive debate, two opposing teams of senior mortgage finance leaders, investors, technologists, and risk experts will examine whether AI is truly creating a smarter, more resilient mortgage industry — or merely a faster and more automated one. Through moderated exchanges, rebuttals, audience polling, and live Q&A, the session will explore the biggest opportunities, risks, and unanswered questions surrounding AI’s long-term impact on housing finance.
