By Stuart Kerr, Technology Correspondent
🗓️ Published: 12 July 2025 | 🔄 Last updated: 12 July 2025
📩 Contact: liveaiwire@gmail.com | 📣 Follow @LiveAIWire
🔗 Author Bio: https://www.liveaiwire.com/p/to-liveaiwire-where-artificial.html
The Rise of Autonomous Capital
Artificial Intelligence has quietly taken root in the global financial system, not just as a support tool, but increasingly as a decision-maker. From high-frequency trading to risk assessments, AI now drives processes once reliant on human discretion. The age of autonomous capital is upon us—but few understand the code behind the curtain.
In our recent report on Invisible Infrastructure, we noted that most AI deployments operate in the shadows. Finance is no different. Algorithms now allocate billions in milliseconds, scan for fraud across networks, and even generate synthetic assets. The pace is dazzling; the transparency is lacking.
From Black-Scholes to Black Boxes
Financial modelling once rested on mathematical elegance. Today, it's driven by machine learning models trained on petabytes of data. While powerful, these tools are often inscrutable. A 2024 Reuters report highlighted the European Central Bank's growing concern that AI-driven trading platforms pose systemic risks due to their opacity and unpredictability.
The OECD has echoed these fears, urging international cooperation on transparency standards. Without auditability, AI becomes a liability—a black box with its own logic steering market behaviour.
Central Banks in Catch-Up Mode
The Bank for International Settlements (BIS) recently warned that central banks must prepare for the "profound impact" of AI, particularly in credit systems, monetary policy, and financial stability. Their 2024 bulletin called AI a "game changer," reshaping not only how institutions operate but how they are regulated.
Still, most central banks lack the infrastructure to audit or even comprehend proprietary models used by private firms. This gap—between innovation and oversight—could widen instability.
Credit Scores and Discriminatory Code
Retail finance has not escaped the algorithmic wave. AI models now determine creditworthiness, set insurance rates, and approve mortgages. But as explored in The Silent Bias, these tools often reflect existing inequalities.
In the absence of clear explainability requirements, borrowers are denied credit by systems they cannot challenge. The Financial Times recently reported on regulators pushing for fairness audits, but progress remains slow.
Fintech's Algorithmic Gold Rush
Startups are racing to integrate AI into everything from robo-advisors to smart contracts. Some promise decentralised lending without banks; others use natural language processing to build synthetic traders. The Financial Stability Board has warned of "concentration risk" as more firms rely on the same foundational models.
And as shown in Faith, Fraud and Face Filters, synthetic identity fraud is on the rise—with AI now used to both detect and perpetrate fraud.
A Fork in the Financial Road
The future of finance is not just digital; it's algorithmic. But without strong governance, AI may amplify volatility, not reduce it. The BIS and Reuters make clear that coordination is essential.
The question isn't whether AI should be used in finance. It already is. The question is whether society can ensure that the systems shaping our economies remain accountable, fair, and aligned with the public interest.
About the Author
Stuart Kerr is the Technology Correspondent at LiveAIWire. He writes about AI’s impact on infrastructure, governance, creativity, and power.
📩 Contact: liveaiwire@gmail.com | 📣 @LiveAIWire
