Podcast: Achieving operational leverage with Bryce Crawford, founder of Meow

This episode of the Beyond Bots podcast features is with Bryce Crawford, founder and CTO of Meow.

Highlights

Tell me about where Ntropy and Meow connect. Give me a little bit about how long you've been a customer and how you're using the tool.

What we use Ntropy for is essentially taking a lot of dirty text that comes through on transaction data. If you've ever looked at your bank statement, you might see on your credit card statement, you might see some transaction where it's like "8674 [ ACH," combined with a merchant name and you're like, I don't know what this is and you Google it and turns out it's the restaurant you had dinner at last week, right?

So Ntropy has a solution that helps clean up this data and makes it user presentable. We use it for our checking account to clean up that transaction data, give reference data to our customers so they can understand what category of spend was that? What was the name of the merchant? What's their website? Just make it easier for people to review their spend.

How are you guys passing revenue to customers in banking? It's really a difficult problem to solve given sort of the margins in banking. Tell me, tell me a little bit about how you're thinking about that today.

It's a very difficult problem because the margins are very tight and as the world becomes more digital, customers are going to demand higher rates of return on their cash and and better economics on their offering. So what meow focuses on is scaling as much as possible through automation and software, not through people.

And we're really focused on bringing down the cost of services and our operating costs as well. So today we have somewhere around 1.3 billion of assets under management. We employ 16 people. So we have an incredible amount of operational leverage. And the only way that's possible is with software. We are very happy with Ntropy's software and helping us achieve this operational leverage.

What is the real impact of AI on finance going to be?

Finance is a regulated space, so we have to see how regulations and frameworks play out over time. There are laws that govern, for example, what sort of investment advice you can provide in an algorithmic way. There's a whole set of robo advisor laws.

I think in the more immediate term, there's a lot of room for impact in streamlining analysis and helping people's workflows, helping generate policy documents or Excel productivity or even code productivity that is immediately applicable, that doesn't have as much of a regulatory lens on it.