Building AI Around the Financial Advice Workflow With Marloo

What happens when a one-hour conversation with a financial advisor creates an entire day of paperwork behind the scenes?

In this episode of Tech Talks Daily, I speak with Hardy Michel, Co-Founder of Marloo, about the administrative load limiting how many clients financial advisors can support. Hardy previously helped build retail investing platforms in New Zealand and the UK, where he saw people gain easier access to investments while personal financial advice remained harder to obtain.

Before building Marloo, Hardy and his co-founders spent months inside financial advice firms. They interviewed managing directors, compliance leaders, support teams and advisors, then worked beside them as they moved between inboxes, planning tools, client records and compliance systems. This “go slow to go fast” approach helped the team map the complete advice process before deciding where software could remove friction.

Hardy says a 60-minute client meeting can produce 10 to 14 hours of follow-up work. An advisor may need to document the discussion, demonstrate why the advice was suitable, complete product research and cash-flow modeling, record fees and disclosures, and prepare a client-facing report that can run to dozens of pages. According to Hardy, the cost and time involved have left some advisors unable to accept new clients for several years.

Marloo began as a specialist meeting assistant because note-taking is frequent, painful and driven by regulation. Hardy explains how transcripts created a current source of client context that was often absent from static records. The company then expanded into the work that follows a meeting, including advice documents and presentations, with the longer-term aim of becoming a central working environment for an advice firm.

We also discuss the trust required when AI handles personal and financial information. Hardy describes Marloo’s zero-data-retention arrangements for certain model APIs and the security information it provides to firms. He argues that specialist systems need to demonstrate how client data is handled and give advisors language they can use to explain recording and transcription to clients.

Adoption is another major theme. Hardy recommends a focused two-week trial with three to five likely power users, a defined goal and a clear measure of value. Rather than relying on a successful demonstration, firms should examine whether advisors continue using the product and are prepared to recommend it to colleagues.

The strongest business outcome may be what advisors choose to do with the time returned to them. Hardy says some Marloo users have increased client meeting frequency from once or twice a year to five or six times. Should AI in financial advice be measured by the volume of cases completed, the quality of client relationships, or a combination of both? Listen to the episode and share your thoughts with me.