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As AI reshapes industries worldwide, fund accounting is embracing its transformative potential. At FundGuard, we are exploring how AI can create a low-touch fund accounting experience while maintaining the necessary accuracy and control that teams need. To get a better picture of where we’re headed, FundGuard’s co-founders, Yaniv Zecharya, CTO, and Uri Katz, VP of R&D, share how AI is shaping both our platform and our operations. Gain insight from industry leaders as Yaniv discusses how we’re embedding AI capabilities to enhance client outcomes, while Uri offers a behind-the-scenes look at how our team is using AI to drive innovation and efficiency within FundGuard itself.
Yaniv Zecharya: An effective AI-human partnership is about using technology to enhance expert judgment. AI can help us automate complex and repetitive processes like data mapping, which must constantly adapt as clients’ needs evolve. The same applies to reconciliation. While most transactions match automatically, AI can now propose explanations or even auto-approve items with a high level of confidence.
We’re also seeing value in anomaly detection. Traditionally, exceptions such as unusual trades or prices were flagged by rule-based systems. Now, AI augments these controls with contextual insights, identifying true issues more accurately and reducing false positives. It’s about freeing teams to focus on other functions like investigation and validation.
Uri Katz: Our team is exploring AI as a tool to accelerate development rather than replace engineers. AI assists with coding, testing, and planning, but humans remain essential to ensure both the context and quality. The partnership works best when AI handles repetitive tasks and humans guide the process and provide the nuanced judgment AI can’t.
Yaniv: At FundGuard, we’re focused on creating a low-touch, ideally no-touch, experience for our clients’ accounting operations. A lot of time in fund accounting is spent on data mapping and manual entry. These tasks are necessary but they’re repetitive, and they take time away from higher-value activities like insights and analysis.
Our vision is that any file, whether CSV, Excel, or XML, can be uploaded and mapped automatically into FundGuard. Similarly, we want our users to upload transaction files, screenshots, or financial statements, review suggested mappings side by side, and approve them. This reduces manual entry significantly while keeping humans in the loop for oversight.
Uri: In product development, we’re adopting AI tools like Cursor across our R&D teams. It helps our engineers with coding and planning. We’ve evaluated several AI coding tools, trained our teams thoroughly, and now monitor usage to ensure the outputs are reliable. Beyond development, we’re exploring how AI can streamline client onboarding, potentially reducing what can be a 6 to 12 month process to something significantly faster. AI can also support some of our client-facing tools, such as chatbots that provide insights into fund exposures, helping both operations and sales.
Yaniv: One of the biggest challenges is ensuring AI operates with minimal errors. In reconciliation or anomaly detection, a false positive or a missed break can create noise or undermine trust. That’s why we deploy AI gradually with human oversight until confidence is high enough to move towards automation. Another challenge is balancing capabilities with cost, particularly when using AI that relies on cloud computation.
Uri: In development, the challenge is guiding AI to do what you intend. Without proper oversight, AI-generated code may be incorrect, overly complex, or difficult to maintain. Code review remains essential, and humans must always be in the loop. Training and monitoring our teams is key. Simply giving engineers an AI tool isn’t enough.
Yaniv: I believe it’s clear that fund accounting will continue moving toward low-touch operations. Teams need to do more in terms of regulations and the calculations as well as work with more complicated asset types. Organizations must do more with less, and AI is becoming critical to achieving efficiency. It will allow administrators, custodians, and research teams to focus on insights rather than their manual tasks.
Uri: It’s difficult to predict exactly where AI will take us because it’s evolving so quickly, but what we do know is that humans will remain essential for context, judgment, and complex problem solving. Over the next year, we could expect incremental improvements like faster development cycles, more efficient operations, and smarter client tools, but the partnership between developers and AI will always be central.
Ready to see how AI can actually support fund accounting instead of adding noise? FundGuard brings cloud-native architecture and embedded AI together so firms can automate the repetitive work, tighten controls, and build a more resilient operating model. Explore how our platform helps teams move toward low-touch operations with confidence. Request a demo to learn more.
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