a16z Podcast · · 41 min

How Valon Rebuilt a $13 Trillion Industry From Scratch

With Andrew Wang, Linda Du

Summary

Linda Du and Andrew Wang of Valon describe how the company is rebuilding U.S. mortgage servicing, a roughly $13 trillion consumer debt market still run largely on decades-old systems. Linda argues Valon's software makes its servicer about three times as efficient, lifting margins from near breakeven to roughly 70-80% and passing savings to asset-manager customers, with NewRez's subserviced loans cited as a lower-bound demonstration. Andrew argues AI agents let servicers handle long-tail cases and customer-specific plans, shifting the industry from commoditized servicing toward specialized service, and he highlights amortized escrow handling as a practical pain point for homeowners facing rising insurance and tax costs. The episode also argues servicing data can extend Valon into commercial mortgages, small-business financing and healthcare revenue-cycle management, and Linda frames enterprise AI adoption as a change-management problem and a key future skill.

Key takeaways

  • Linda Du on US housing: Mortgage servicing is a $13T market still running on a pre-internet incumbent's legacy system.
  • Linda Du on AI & jobs: People hired in the next decade will be valued for their ability to apply AI.
  • Andrew Wang on US housing: Rising insurance and tax costs are straining homeowner escrow payments that legacy systems handle poorly.

What was said, by company and theme

3 views from 2 speakers. Every quote is checked against the episode's transcript (how).

US housing

  • Linda Du · Valon

    Mortgage servicing is a $13T market still running on a pre-internet incumbent's legacy system.

    Linda describes mortgage servicing as one of the top three least-disrupted industries. About $13 trillion of consumer debt runs mostly on a single incumbent whose system was built before the internet. She argues the industry hasn't yet caught up to 2000s technology, so the opportunity to rebuild it is very large. She notes that most industries face modern startups, but mortgage servicing still runs on decades-old systems.

    “And so it's $13,000,000,000,000 of consumer debt that basically runs on, for the most part, a single incumbent that built their legacy system before the internet was invented.”at 3:59
  • Andrew Wang · Valon

    Rising insurance and tax costs are straining homeowner escrow payments that legacy systems handle poorly.

    Andrew says insurance costs and property taxes are surging, so many homeowners can't make the large escrow payment or adjust it quickly. Most legacy systems calculate the annual escrow cost in one lump, even though regulation and investor standards allow amortizing it over 36 months. As a result, each change needs an ad hoc supervisor approval rather than an automated decision. He argues that automated, configurable escrow handling would help servicers keep customers in hard times.

    “One of the problems right now that everyone faces is actually insurance costs and taxes are actually exploding. And so many homeowners aren't able to make that large payment or change a payment in such a quick fashion.”at 8:07

AI & jobs

  • Linda Du · Valon

    People hired in the next decade will be valued for their ability to apply AI.

    Linda says Valon tells its team that the skill set people will be hiring for over the next decade is the ability to apply AI. Her evidence is Valon's own deployments: it is rolling out AI into the largest enterprise deployments, training thousands of employees and replacing core operating systems in a heavily regulated industry. She argues that learning to apply AI in the hardest industry is the best preparation for that hiring shift.

    “what we always tell the team is that the skill set that people will be hiring for in the next decade is the ability to apply AI.”at 4:36

Topics

  • AI agents in servicing
  • AI skills demand
  • enterprise AI deployment
  • homeowner escrow payments
  • mortgage servicing efficiency
  • mortgage servicing technology
  • outcome-based pricing
  • servicing expansion into adjacent sectors
  • servicing unit economics
  • software demand

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