Below is one of several panel discussions held at last week’s Family Wealth Report Family Office Fintech Forum 2025. 

Unsurprisingly, AI loomed large in the conversations at this news service's Annual Fintech Forum, and this panel examined the use cases in family offices. The panel was entitled â€śRisk management use case for AI: the already here, the possible and the unlikely.”

The panel featured three Altari Ventures portfolio CEOs whose companies offer concrete and urgently needed solutions for the investment management industry: Sindhu Joseph (CogniCor), Jeremy Sisselman (Bondway) and Charles Anselm (Osyte).
 

Anna Garcia, of Altari Ventures, moderated the panel and summarizes its conversations:

As an enterprise fintech investor, I constantly evaluate companies that leverage data and top notch AI to deliver value-added solutions to financial services clients. AI’s potential effect on the industry is being widely discussed, with conclusions ranging from the obvious that it will boost productivity, to the scary that it will replace most humans, to the dramatic that AI will rewrite the face of the financial industry on every level imaginable. Some call AI's impact nothing short of revolutionary. But there are few notions in greater opposition than “risk” and “revolution” in financial services, as pace of change is existentially tied to risk management and compliance keeping up. It's a slow transformation process because the financial industry is incredibly risk averse.

That’s why I view the AI investment opportunity through a risk management lens: Where does it surface real risk? Where does it mitigate it? And where does it create it?

Here are a few takeaways from three industry leaders working in different segments of the investment management industry regarding AI and its applications:

The nuances and examples of AI’s current risk applications
For family offices, managing multi-generational wealth isn't just about returns – it's about navigating liquidity needs, market volatility, and operational complexity. As Charles Anselm, CEO of Osyte, explained, true risk management goes beyond individual assets. His company helps allocators think about and effectively manage liquidity risk in multi-asset portfolios. 

With AI-powered liquidity forecasting and conversational intelligence, Osyte enables chief investment officers to anticipate cash flow needs, optimize capital calls by raising cash from the best sources, and uncover hidden exposures often unseen by the human eye – turning fragmented data into a powerful forward-looking liquidity management strategy for multi-asset portfolios that span public and private, liquid and illiquid investments.

Sindhu Joseph, CEO of CogniCor, painted a picture of an AI-first family office and offered a perspective rooted in AI’s adaptability. With a PhD in artificial intelligence and a mission to modernize wealth advisory workflows, she emphasized that AI’s greatest strength is simplifying complexity. Sindhu explained how most tech stacks weren’t built for family offices, but AI allows them to personalize across unstructured data without rebuilding their systems. Risk, in Joseph’s view, is not knowing your client, not acting in a timely manner and not being able to show evidence of why you’re making certain decisions – all considerations that CogniCor’s platform helps directly address.

Jeremy Sisselman, founder of Bondway, tackled one of the most opaque corners of finance: the corporate bond market. He shared how, as a former bond originator on Wall Street, his biggest risk was missing something because at the time market participants could only access limited information through their firm’s trading desk. 

Bondway’s AI-driven analytics now track thousands of bonds in real time across the whole market, providing predictive pricing and liquidity insights where manual monitoring once fell significantly short. Bondway is giving traders and portfolio managers visibility into bond pricing, along with the quality assessment of that price, which reduces the risk of making costly trade execution mistakes.

What AI can’t do yet (and what’s coming next) 
While AI’s potential is vast, the panelists agreed on its limitations. Joseph cautioned against over-reliance on automation and argued the importance of preserving the human element in areas of financial advisory where emotional intelligence, personal connection, empathy and authentic delivery remain irreplaceable. She also called out the risk of AI creating more tech fragmentation and warned the audience to focus on integrated solutions, not isolated tools.

Charles Anselm weighed in on AI and investment decisions, noting that it is great for handling large amounts of data and automating manual processes, but it can’t yet manage the trade-offs and nuanced decisions that experienced investors make. Ultimately, as Sisselman put it, AI capabilities are evolving fast. What wasn’t possible a few short months ago we can now do. Staying ahead requires constant adaptation.

As we neared the end of our panel, we shifted to discussing what’s next for each of the businesses represented on stage.

Charles described a future where AI helps allocators navigate an overwhelming universe of private market opportunities through customized portfolio construction and near instant evaluation. Joseph advocated for an AI intelligence layer that unifies fragmented tech stacks and avoids a situation where point solutions only create additional silos. Jeremy shared that his company is pushing into predictive pricing and predictive liquidity driven by deep statistical models which could aid in discovery of additional arbitrage opportunities. 

Parting thoughts
AI offers family offices a way of managing risk dynamically, adapting to shifting markets and uncovering new opportunities while also streamlining their operations and minimizing the cost of compliance. Data is a foundational piece of the AI utility puzzle, thus doing the groundwork to ensure access to the most complete and accurate information is key to realizing the full benefit of what AI can deliver now and over the long-term.