Fintech Hunting

Fintech Hunting covers the mortgage industry through conversations with fintech builders, lender-facing operators, coaches, and relationship-driven connectors. The show’s center of gravity is practical technology adoption. AI comes up often, but the useful question is always what the tool does for a lender, a loan officer, or a borrower. Recent episodes examine agentic processing, AI loan officers, internal knowledge search, conversation intelligence, call review, lead scoring, CRM connections, and borrower outreach. The show is especially interested in the space between promise and implementation. Guests are asked where leverage actually appears, where lenders hesitate, and what teams need before new tools become part of daily work. Compliance and risk are treated as real constraints, not excuses to wait forever. That gives the show a sales-floor feel as much as a strategy feel. It spends time on cost to originate, speed, retention, data timing, and the emotional rhythm of sales work. Fintech Hunting also keeps returning to the people side of mortgage. Episodes with Christine Beckwith focus on coaching, trust, resilience, market conditions, and the danger of behaving like a rate seller instead of an advisor. Conversations with Courtney from MMI and Liz Short put networking, LinkedIn, conferences, and relationship-first growth in the foreground. The show’s pacing is friendly and conference-season fluent, with direct praise, warm guest rapport, and clear asks for examples. It is not detached analysis. It is closer to an industry conversation where vendors, coaches, and operators explain what they are seeing in the field. Listeners looking for highly skeptical journalism may find the tone promotional at times. Mortgage professionals, fintech teams, and lender leaders, however, will find a steady stream of practical signals about where the industry is putting attention. Fintech Hunting works best as a shortcut into current mortgage tech conversations. It shows what people are building, what lenders are worried about, and why relationships still matter even as AI becomes part of the stack.