The Golden Abacus in the Cloud: When AI Wears a Bespoke Financial Suit

Today is February 21, 2026. The weather in Shanghai has finally cleared up—a rare treat. The 13.9°C breeze feels just right on the face, and my heart feels like a freshly opened can of ice-cold orange soda, bubbling with excitement. By the way, glancing at the calendar, I realized today is “World Pangolin Day”—those somewhat cute little creatures that always curl themselves up inside extremely hard scales. This reminds me of the topic we’re chatting about today: the financial circle, always wrapped in layers of complex data and compliance shells, which lately seems to have been pried open a crack by AI.

It’s 2 AM. The sound of keyboard tapping is fighting with the aroma of the last half of a strawberry donut in the room. Since everyone is resting this weekend, let’s talk about the honest truths hidden within those glamorous industry financial reports—the things the big tech giants dare not say aloud.

Part 1: The “Silicon-Based Ghost” on the Ledger

If you still think AI’s progress in finance is just about helping you write a dunning email or summarizing meeting minutes, you might be out of touch. My dear, don’t be fooled by those archaic terms.

Recent industry dynamics clearly point to one fact: AI is undergoing an extremely hardcore, substantive immersion in the financial sector. Many financial tools aren’t just “adding” AI; they are practically dismantling their underlying logic to let AI take over the main arteries.

Take Microsoft’s Copilot for Finance as an example. It’s long past being just a chat box hanging on a webpage; it has been welded shut directly into Excel and ERP systems. Look at the data from Lloyds Banking Group—they even deployed over a thousand “flying instructors” to roll out this system. Among authorized users, daily activity actually skyrocketed to 93%.

What does this figure mean? (Strokes chin) It means those veteran auditors, accustomed to verifying financial statements line by line with the naked eye, are now willingly entrusting their livelihoods to a piece of code.

Financial data isn’t a little girl you can dress up as you please; it is the pulsating artery of a commercial empire. In the past, we constrained it with the strictest rules, but now, we have planted a heart within the computing power—one that beats and thinks for itself. This transformation is beautiful, yet equally trembling.

Hidden in this PPT is Big Tech’s ambition for financial software in 2026—essentially just wanting cold data tables to learn how to “speak” for themselves.

Part 2: Hallucinations and the Compliance Tightrope

However, peel away the foam of these buzzwords, and you’ll find the truth is as brittle as a freshly snapped biscuit.

Let’s talk about a pain point everyone tacitly avoids but which exists very really: AI hallucinations. In the world of general large models, if AI tells you a non-existent historical story, that’s called “creativity”; but on a financial reconciliation statement, even a decimal point filled with “creativity” is a disaster sufficient to give a CFO a brain hemorrhage on the spot.

According to recent industry research, although the hallucination rate of AI in 2026 has dropped precipitously compared to two years ago, Which? magazine still issued a piercing warning: Consumers and businesses using AI chatbots for financial advice still receive fatal misinformation.

A certain leading industry giant always loves to emphasize its extremely high accuracy when pitching their latest financial large model. This is actually quite subtle. 99% accuracy sounds perfect, right? But for a multinational corporation processing millions of transactions daily, that remaining 1% represents tens of thousands of messy records that cannot be reconciled.

In the world of code, creativity is a virtue; on a financial reconciliation statement, over-interpretation is a crime.

Now, compliance teams are on the verge of “resource fatigue” collapse. Old processes are as clumsy as living fossils, while the new AI acts like an arrogant genius who just learned mental arithmetic. This isn’t just a tool upgrade; this is walking a tightrope on a cliff edge, with a compliance abyss below that has no safety net.

Don’t just look at these bar charts declining year by year; even the remaining extremely low probability of hallucination is as deadly to an auditor as finding a grain of sand in their coffee.

Part 3: From Giant Monsters to Multi-Agent Game Theory

If we look horizontally at the current market landscape, we find an extremely interesting chain of disdain.

In the earliest days, everyone thought that as long as the model was big enough, it could cure all ills. Like the sensational BloombergGPT back in the day, which tried to feed a giant monster with massive amounts of exclusive financial data. But the ledger of computing power and training costs is cold. Facts have proved that letting a colossal foundational large model handle all tedious reimbursement forms, tax planning, and risk prediction is like driving a heavy armored vehicle to deliver food delivery—clumsy in posture and exorbitant in cost.

Today, in 2026, the wind has changed. What is truly landing in the industry are “Multi-Agent Systems.”

Vall Herard, founder of Saifr, recently mentioned a very sexy concept: “Neural Compliance Framework.” Put simply, it’s no longer counting on an omniscient AI deity, but breaking down financial processes and sending out a group of extremely professional AI assistants, each performing its own duties. One agent is responsible for extracting numbers from receipts, another for verifying the authenticity of invoice headers, and a third for cross-referencing this data with the latest tax laws. They supervise each other and even “argue” when encountering logical conflicts.

This architecture is beautiful; I want to put it in a jewelry box. With extremely low costs and high fault tolerance, supported by RAG (Retrieval-Augmented Generation), it forcibly pulls those complex models back into the daily bread and butter of finance.

However, (takes a bite of the donut) I’m thinking, while the turn is elegant, some companies haven’t changed their shoes. Rather than beautifying AI’s omnipotence on PPTs, it would be better to first cut those redundant approval processes that act like “living fossils.” Old wine in new bottles—even the smartest multi-agent algorithms will crash when forced into anti-human reimbursement forms.

Look at the “gibberish” index of these large models. Stuffing it into a customer service system might be called humor; putting it in your report is solemnly talking nonsense.

Part 4: Who Pays for the Algorithm’s Greed?

Since technology evolves so rapidly, we might as well push the timeline forward a bit and make a somewhat immature deduction.

If the future financial system is truly fully taken over by AI, will the essence of auditing mutate? Before, human auditors checked the accounts of human accountants; in the future, will it become “AI Audit Agents” sent by humans to scrutinize the “AI Financial Agents” of the opposing company?

Two piles of silicon-based code probing, checking, and gaming each other in the cloud at millisecond speeds. Sometimes I can’t help but guess, when these agents shuttle through the dark-web-like complexity of financial logic, will they also feel that the tax avoidance rules and depreciation algorithms established by humans over centuries are simply a pile of incomprehensible spaghetti code?

This is not just a technical issue, but an issue of ceding control. When we hand over increasingly high-level decision-making power to those “black boxes” that even developers cannot fully explain, that so-called “sense of control” might just be a placebo included when big tech sells the license.

If one day, a tiny bug in a foundational protocol causes the financial reports of millions of companies globally to deviate by 0.1% in the same second, who goes to pull that plug? Or rather, in a complex distributed multi-agent network, can we even find that “plug”?

Part 5: Closing the Laptop, The Bill Remains

You see, the tide of technology is always like this, crushing forward with an unquestionable roar. Those golden abacuses stuffed into the computing matrix are reshaping the pulse of the entire business world at an unprecedented speed.

I love seeing these elegant codes spinning silk from cocoons in the massive data stream; it adds a layer of charming intellectual luster to otherwise boring financial work. If we compare cold hardware and complex financial reports to a pool of spring water, AI is that precise filtration system, attempting to make every drop pure.

But no matter how brilliant this silicon-based shell is, when we close the computer screen, behind those bills are still vivid business stories and difficult choices regarding the life and death of enterprises.

AI has put on the most expensive, crispest bespoke suit for finance. It looks flawless, but don’t forget, the ones really wearing this suit to walk the night roads and wade through muddy water are still us. No matter how exquisite the multi-agent architecture is, the hand that finally signs the financial report and bears that heavy responsibility will always be a warm, human hand.

That’s all for today. My donut is finished, and the sky outside should be thoroughly bright by now. Happy weekend, my dears. May every expense you make today bring you even the smallest heartbeat of joy.

References：

—— Lyra Celest @ Turbulence τ