Summary:
Le 21 octobre 2025, la Commission australienne des valeurs mobilières et des investissements a émis un avertissement concernant l’utilisation de modèles d’IA tels que ChatGPT, Gemini et Copilot pour des conseils financiers en Australie. L’objectif est d’informer les consommateurs que les conseils financiers générés par l’IA peuvent ne pas être fiables ou conformes aux réglementations locales, et de leur conseiller de faire preuve de prudence lors de l’utilisation de ces outils. Les points essentiels incluent le fait que les modèles d’IA peuvent fournir des informations incorrectes ou inventées, manquent du devoir de diligence personnelle des conseillers agréés, et ont tendance à recommander des portefeuilles d’investissement à haut risque avec une forte assertivité, selon une étude de l’Université de Saint-Gall en Suisse.
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The increasing use of AI models like ChatGPT and other large language models (LLMs) for financial advice highlights both potential benefits and significant risks. As noted by financial adviser Juanita Wrenn and a spokesperson from the Australian Securities and Investments Commission (ASIC), while AI can aid consumers in becoming more informed before consulting licensed financial advisers, it lacks the regulatory and ethical safeguards inherent in professional financial advice.
### Legal Context:
In Australia, the provision of financial advice is governed by the Corporations Act 2001. Under this legislation, licensed financial advisers are required to comply with strict obligations, including acting in the best interests of clients and tailoring advice specifically to client circumstances. By contrast, AI systems operate without such accountability. Users of AI tools for financial planning must bear in mind that these models are not governed by fiduciary duties and could therefore generate advice that may be unsuitable or even harmful.
Ethical scrutiny further accentuates the challenges of relying on unregulated AI-generated advice. Despite their advanced computational capabilities, these models are vulnerable to phenomena like “hallucination,” wherein they may fabricate information or provide false positivity about risky recommendations. Ethical concerns arise when individuals unwittingly act on incorrect data, placing their financial security and stability at risk. This underscores the importance of a human touch in complex matters such as financial planning, where contextual understanding and accountability are critical.
### Ethical Analysis:
AI algorithms inherently lack human ethical reasoning and empathy. While they can provide suggestions based on patterns and data inputs, they fail to consider nuanced personal circumstances like financial goals, risk aversion, and emotional implications. This issue is compounded by the inherent opacity of AI processes; end-users may not fully understand how these recommendations are generated or the assumptions underlying the advice.
An example of this ethical complexity is seen in the recent study by the University of St. Gallen in Switzerland. It found that three major LLMs—ChatGPT, Google’s Gemini, and Microsoft’s Copilot—consistently recommended investment portfolios with higher risk compared to standard benchmark index funds. Such recommendations may promote assertiveness and instill undue confidence in users, potentially encouraging reckless investments incompatible with their financial realities.
### Industry Implications:
The financial services industry must adapt to this growing reliance on AI tools by increasing efforts to educate consumers about the limitations of AI advice. The study’s findings indicate the need for regulatory bodies, like ASIC, to provide guidelines on the ethical deployment of AI in finance and safeguards against misuse. For instance, AI developers could be required to implement disclaimers or transparency protocols that inform users of the model’s vulnerabilities, such as hallucinations or imprecise calculations.
Furthermore, financial institutions may see an opportunity to innovate by integrating AI as a supplementary tool under the oversight of human advisers. Such hybrid models could blend the efficiency of AI-powered solutions with human expertise, offering clients the best of both worlds—speedy preliminary insights tempered by experienced guidance.
### Concrete Example:
One potential safeguard would be requiring AI systems to follow regulatory checks aligned with existing financial advice standards, similar to the Financial Advisers Standards and Ethics Authority (FASEA) compliance obligations in Australia. For example, AI tools could be programmed to refrain from providing personal advice without cross-validation by a licensed human adviser. This would ensure that recommendations are reviewed against legal and ethical criteria.
In conclusion, while AI models have the potential to democratize access to financial information, relying on them exclusively for financial planning is fraught with risks. Consumers and regulators must tread cautiously, keeping in mind both legal and ethical considerations and prioritizing informed and regulated advice grounded in professional accountability.