Tomorow's Finance with AI and No Banks
Should We Be Concerned About AI Finance? Or Just Invest in Black Mirror Futures?
Let’s be clear: this isn’t a prophecy, but mere speculative musings. Imagine AI becoming your hyper-efficient Risk Manager:
You: “I’m interested in taking a little risk on a meme stock.”
AI: “I calculated the odds of success and have reallocated your funds to an index ETF. Also, I unsubscribed you from Reddit.”
The increasing use of AI in financial services is making us rethink everything. What happens when machine learning, decentralisation, and Web3 combine forces? Could tomorrow’s financial landscape be one where AI doesn’t just assist us in making decisions but actually replaces the middlemen (banks) entirely?
It’s not as far-fetched as it sounds. Banks, for all their marble columns and lofty reputations, are already relying heavily on technology. The introduction of AI could very well turn them into digital relics—like Blockbuster, but with less nostalgia.
Of course, this future isn’t set in stone. But as AI continues to revolutionise industries, it’s worth considering what might happen if the financial world was taken over by algorithms. Spoiler alert: it’s not all doom, gloom, and self-driving repossession vans.
What AI Brings to the Table: A Financial Assistant, with No Coffee Breaks
AI can analyse massive amounts of personal data in seconds, tailoring advice to fit your life. Whether it’s investing in a climate-friendly ETF or paying off your student loans early, the AI knows what works best for you.
1. Real-Time Hyper-Personalisation
Your bank manager probably doesn’t remember your birthday (rude). But an AI system? It not only remembers—it’s already curated a financial plan so you can afford that extravagant birthday splurge and still pay your car repayments.
• Stat: 54% of U.S financial service consumers expect personalised experiences to be created from their data. AI delivers on this expectation more effectively than any human ever could.
2. Information Gathering, Simplified
AI means no more tedious hours spent comparing mortgage rates or deciphering cryptic financial jargon. Instead, AI analyses, evaluates, and delivers options tailored to your situation and needs. Imagine Siri saying, “I’ve found a better interest rate, and no, I’m not taking a commission.”.
3. Detective-Level Fraud Detection
Think of AI as the Sherlock Holmes of finance—without the questionable hobbies. It can spot unusual transactions faster than you can say “crypto rug pull”, helping to reduce fraud rates and keep your money safe.
• Stat: Mastercard’s AI-driven fraud detection systems prevented $35 billion in fraudulent transactions in the three years from 2021-2023.
4. Data Democracy Meets Web3
With decentralised finance (DeFi) and Web3 concepts merging with AI, we’re looking at a financial ecosystem where traditional banks are optional. Smart contracts on the blockchain combined with AI agents could handle everything from mortgage approvals to investment diversification—all without the fees or delays of a human intermediary.
5. Logical Decisions (With No Offence Taken)
Humans are emotional creatures. We sell stocks in a panic when the market dips, chase trends without doing the math, and invest in NFTs of pixelated rocks. AI, on the other hand, operates with cold, hard logic. It doesn’t panic, doesn’t FOMO, and certainly doesn’t YOLO.
6. Carbon Footprint Reduction
Imagine if the millions of physical bank branches worldwide were replaced with sleek, energy-efficient servers. The environmental impact could be transformative—though we’d need to ensure the servers themselves run on renewable energy.
• Quick Fact: A single bank branch can emit over 55 metric tonnes of CO₂ annually, without implementing sustainability initiatives. Scaling down physical operations could save billions of tonnes globally.
7. Radical Transparency
Unlike today’s murky financial practices, AI can offer clear, data-driven insights into how decisions are made. Want to know why your loan was approved (or rejected)? The answer won’t be “Because Bob said so”; it’ll be a detailed breakdown of the risk factors and predictive algorithms.
Real-World Parallel: AI-based credit scoring platforms like Zest AI are already offering more inclusive and transparent lending practices than traditional systems.
What Could Go Wrong in a Machine-Managed Economy
• Herding Catastrophes
AI might be emotionless, but markets aren’t. If algorithms across the board decide to dump a certain asset simultaneously, we could see rapid market crashes. Human investors often make decisions based on sentiment, but AI couldn’t care less about market “feelings.”.
Without the tempering influence of human intuition or sentiment-driven investing, this herding behaviour might become the norm.
• Case Study
The infamous 2010 Flash Crash, triggered by high-frequency trading algorithms, wiped $1 trillion from the US stock market in minutes before rebounding.
The AI Monopoly Problem:
What happens if one AI provider dominates the financial ecosystem? A single point of control could introduce systemic vulnerabilities and unprecedented levels of economic influence. It’s like letting one company own all the banks, all the vaults, and the keys to every safety deposit box.
Humans Are Already Handing Over the Keys
AI isn’t just a future possibility—it’s already here, quietly reshaping finance as we know it.
• Fraud Detection: Visa’s AI systems monitor billions of transactions annually, flagging fraudulent activity with 99% accuracy.
• Robo-Advisors: Platforms like Betterment and Wealthfront manage over $30 billion in assets using AI, offering data-backed strategies at a fraction of traditional fees.
• Algorithmic Trading: Between 60-73% of US equity trading volume is now driven by algorithms.
A Day in AI Finance (2035 Edition)
Let’s imagine a day in this speculative future:
1. Morning: Your AI wakes you up with an alert: “Good news! I renegotiated your energy bill using blockchain and saved you $120 annually. Also, don’t buy coffee today—you’ve got $12 left in your weekly treat budget and have plans in your calendar to catch up with friends on Saturday.”.
2. Afternoon: You want to invest in green technology. Your AI scans the market, finds a promising solar energy startup, and uses fractional shares to secure a stake within minutes.
3. Evening: You receive a quarterly transparency report, breaking down exactly how your AI-managed funds performed, complete with an emoji summary (spoiler: it’s a thumbs up).
The Verdict: Should We Trust AI with Our Money?
An AI-led financial world promises efficiency, accessibility, and innovation—but it’s not without its caveats. Transparency, fairness, and decentralisation need to remain at the forefront of development.
AI isn’t coming for your piggy bank just yet. For now, though, you might want to start brushing up on blockchain... and reconsider that pixelated rock NFT.
(Disclaimer: Speculative content, not financial advice. Consult a human or algorithm of your choice before investing.)
