- Sam Sammane argues that Hybrid AI is no longer an option but has become a mandatory requirement in the banking and finance industry.
- The article warns that generative AI models like OpenAI’s ChatGPT operate based on probability, meaning they cannot guarantee absolutely stable results.
- The author states that the same prompt can produce different results; for instance, an AI might rate a contract at 70% compliance today but 100% on another day.
- In the financial sector, such “hallucinations” can lead to litigation, fines, and severe reputational damage.
- A small error, such as mistyping a penalty interest rate from 24% down to 6% in an automated system, can cause massive financial consequences for a bank.
- Many legal departments are reportedly losing almost all time-saving benefits because they must manually verify the AI’s output.
- The author emphasizes that the correct solution is “neuro-symbolic AI,” which combines neural networks with symbolic logic and deterministic mathematical systems.
- In a Hybrid AI model, the AI reads and understands documents, while calculation, regulatory checking, and verification are assigned to deterministic libraries in Python or C++.
- An agent system acts as a coordinator, automatically routing each task to the appropriate specialized tool instead of letting the AI handle everything.
- For example, an AI can analyze a 70-page bank contract, but the disclosure and compliance checks must be performed by specialized verification tools.
- The author notes that combining AI with traditional tools can reduce research and development time by up to 95% in financial projects.
- A cited MIT study shows that about 95% of AI pilot projects at large enterprises fail because of the expectation that AI can do everything.
- The article suggests that the future of finance does not need an “army of coders” but rather experts who understand business, law, and how to combine AI with deterministic systems.
- The author warns that cheap AI solutions lacking expertise could expose businesses to serious legal and operational risks.
📌 The finance industry is entering a “post-AI-hype” phase, where speed is no longer as important as accuracy and risk control. The article shows that Hybrid AI, combining language models with mathematical and logical verification systems, is becoming a mandatory architecture for banks. In an environment where a small error can cause millions of dollars in damages, “approximate AI” is no longer safe enough to manage customers’ money.
