SoFi Teaches Its AI Coach to Read the Financial Room

Watch more: Digital Shift With SoFi’s Brian Walsh

Digital transformation in financial services has traditionally hung its hat on the promise of democratization and accessibility.

Software could reach consumers who lacked enough assets to attract a traditional adviser, delivering basic education and automated portfolio management at a fraction of the cost.

Conversational artificial intelligence is now taking that premise even further. AI-powered financial coaches are beginning to combine conversational guidance, account-level data, visual explanations and persistent memory into an experience that more closely resembles an ongoing advisory relationship.

“People want to interact and receive guidance in different ways,” SoFi Head of Advice and Planning Brian Walsh told PYMNTS. “Sometimes it’s going to be a convenient chat-based experience. Sometimes it’s going to be a little bit more complicated, more high-touch with humans.”

Walsh, who leads financial planning efforts behind SoFi’s AI-powered Coach platform, said roughly half of Coach’s own customer interactions concern investing, reflecting the familiar financial challenge of how to spend less than one earns and put the difference to work.

The takeaway for both financial firms and their customers is not that AI is replacing the financial planner. It is that software is starting to absorb some of the context, continuity and communication techniques that once made human advice difficult to scale.

Better AI Communication Matters More Than Better AI Answers

The quality of financial guidance depends on context. A recommendation to invest excess cash, for example, may be appropriate for a consumer with a fully funded emergency reserve and no costly debt. The same recommendation could be harmful for someone facing a near-term expense or carrying a high-interest credit card balance.

“It’s one thing to say, ‘Hey, you have a bunch of extra cash in this account. This cash should be invested, or it should be used to pay down debt,’” Walsh said. “But if you don’t have any context in how it fits into their overall picture, that could be correct, it could be incorrect.”

Consumers frequently hold accounts across five, 10 or even 15 institutions, making it difficult to understand their actual financial position. Bringing that information together reduces the organizational work that often prevents people from acting in the first place.

“It’s not just what you say,” Walsh said. “It’s how you position it to get them to take action and make positive changes in their financial lives.”

Memory adds another layer. When an AI system can retain details about family circumstances, long-term priorities or previous conversations, users do not have to repeatedly reconstruct their financial lives. That matters not only for convenience but also for behavior.

“There are a lot of financial concepts that are much easier to express visually than they are in writing,” Walsh said. “It opens up this whole new dynamic of how do we communicate these topics in as simple and understandable manner as possible.”

A written statement showing that 30% of discretionary spending goes toward one category may have little impact. A pie chart showing that category towering over every other expense can create a different response.

AI Financial Coaches Are Turning Personalization Into Financial Infrastructure

The expansion of AI guidance also raises an unavoidable question: Where should automation stop?

Coach was developed using principles, communication methods and boundaries drawn from eight years and tens of thousands of conversations conducted by human financial planners, Walsh said. Rule sets are designed to identify when an interaction moves beyond the intended scope of automated guidance and should be escalated.

“There are going to be clear rule sets that are built in,” he said. “This is going to expand beyond the scope of the advice or the guidance that we want to provide. Now let’s escalate this to a human interaction.”

The human-in-the-loop structure may be essential to scaling AI in regulated financial environments. It allows software to handle education, organization and routine guidance while preserving a pathway for complexity, judgment and regulated advice. The result could be a two-sided productivity gain. AI tools can serve consumers who might otherwise receive no guidance, while human planners can use the information gathered through digital interactions to serve more people efficiently.

“You get this snowball effect where you’re exposing expertise to more people,” Walsh said. “You’re making the human side of the things more efficient.”

That may ultimately be the more important measure of progress. The future of AI-powered financial guidance will not be determined by whether a chatbot can imitate an adviser. It will be determined by whether technology can make informed, contextual and actionable guidance available to people who have historically been left outside the financial advice system.

Watch the full PYMNTS TV interview with SoFI’s Brian Walsh to learn why:

AI financial guidance is becoming more contextual. The most useful tools can connect assets, spending, debt and cash flow to determine whether a recommendation fits a consumer’s broader financial picture.

Personalization can improve financial action. Remembering family circumstances, priorities and long-term goals reduces repetition while helping AI frame guidance in ways that are more relevant and easier to act on.

Human escalation remains essential. AI can expand access to financial education and routine guidance, but clear boundaries are needed to route complex or regulated questions to human advisers.

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