So your CEO wants AI in finance? Imagine it’s month-end. You’re in NetSuite, late again, exporting reports into Excel. The numbers are correct, but the story isn’t there yet.
Hi, I’ve been following AI In Finance and really like how you explore the intersection of AI and finance beyond just the technology itself. The idea of helping finance teams turn numbers into stories and build influence especially resonates with me.
I also write and work in the fintech and crypto space, focusing on digital finance, payments, blockchain, AI, and the future of financial infrastructure. I’d love to connect, subscribe to each other, and support each other’s work.
Would be great to exchange perspectives on AI, fintech, and how technology is reshaping finance, and potentially explore a collaboration down the line. Would you be open to staying connected? 🤝
"The numbers are correct, but the story isn't there yet." That sentence is doing more work than it looks like, because it assumes the first half.
The failure I would watch for is not a missing story. It is a confident one built on numbers that were wrong in a way nobody could see. We ran one extraction setting across our whole client book and it produced entries that were wrong for a subset of clients for months. Wrong account, right magnitude, consistent month over month. Nothing looked odd, so nothing got looked at. A narrative layer sitting on top of that would have told a clean, board-ready story every month, and the confidence of the telling would have made it harder to catch, not easier.
So the question I would want a storytelling layer to answer is not how fast it narrates. It is what trust level it inherits from its input, and whether it can refuse. A layer that declines to narrate a line whose source has not passed a check is worth more than one that narrates everything beautifully.
And the uncomfortable part, which is ours not yours: we could not state our own input trust level if you asked. We record correction rates only partially, so I cannot tell you what fraction of our reviews change anything. Most finance teams I talk to are in the same position, which means most of them cannot tell you what their story is standing on either.
Does finstory expose the provenance of a line in the story, or only the number?
The interesting shift is AI moving from financial reporting to financial interpretation. If the ERP remains the system of record while AI turns the underlying data into a repeatable narrative, the real value isn’t replacing finance teams it’s reducing the manual work between having the numbers and understanding what they mean.
Hi, I’ve been following AI In Finance and really like how you explore the intersection of AI and finance beyond just the technology itself. The idea of helping finance teams turn numbers into stories and build influence especially resonates with me.
I also write and work in the fintech and crypto space, focusing on digital finance, payments, blockchain, AI, and the future of financial infrastructure. I’d love to connect, subscribe to each other, and support each other’s work.
Would be great to exchange perspectives on AI, fintech, and how technology is reshaping finance, and potentially explore a collaboration down the line. Would you be open to staying connected? 🤝
"The numbers are correct, but the story isn't there yet." That sentence is doing more work than it looks like, because it assumes the first half.
The failure I would watch for is not a missing story. It is a confident one built on numbers that were wrong in a way nobody could see. We ran one extraction setting across our whole client book and it produced entries that were wrong for a subset of clients for months. Wrong account, right magnitude, consistent month over month. Nothing looked odd, so nothing got looked at. A narrative layer sitting on top of that would have told a clean, board-ready story every month, and the confidence of the telling would have made it harder to catch, not easier.
So the question I would want a storytelling layer to answer is not how fast it narrates. It is what trust level it inherits from its input, and whether it can refuse. A layer that declines to narrate a line whose source has not passed a check is worth more than one that narrates everything beautifully.
And the uncomfortable part, which is ours not yours: we could not state our own input trust level if you asked. We record correction rates only partially, so I cannot tell you what fraction of our reviews change anything. Most finance teams I talk to are in the same position, which means most of them cannot tell you what their story is standing on either.
Does finstory expose the provenance of a line in the story, or only the number?
The interesting shift is AI moving from financial reporting to financial interpretation. If the ERP remains the system of record while AI turns the underlying data into a repeatable narrative, the real value isn’t replacing finance teams it’s reducing the manual work between having the numbers and understanding what they mean.