Financial advisory (private wealth management, wealth management, investment advice) is undergoing a full transformation with generative AI. Wealth summaries, scenario simulations, personalized advisory notes, market monitoring: all tasks that can be accelerated. Confidentiality remains critical (professional secrecy, GDPR, MiFID II) and requires respectful tools. This guide presents secure workflows and high-ROI use cases in a wealth management firm or private banking service.
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What confidentiality for wealth data?
Critical. Solutions: Claude for Work / ChatGPT Enterprise (contractual no-training clause), prior pseudonymization of amounts and names, or ideally dedicated wealth management platforms. No identifiable client data on public LLMs.
Can AI replace the advisor?
For analytical production: largely. For client relationships (trust, listening, reading unspoken wealth and family matters): no. The advisor who does best: automates production, keeps the human element for decision-making and relationships.
Does AI respect MiFID II?
Not automatically — it's the advisor's responsibility to ensure compliance. AI can produce recommendations that don't respect the duty of care or suitability. All output must be human-validated before client transmission.
Hallucinations on financial figures?
High risk on chained calculations (IRR, capitalization, IFI). Always verify with a calculator or dedicated tool. Code Interpreter (ChatGPT) or Claude with Python tool are more reliable.
What's the real ROI on productivity?
On summary notes and reporting: 60-70% time savings. On personalized advice and relationships: ~10%. Overall, an advisor can handle 30-50% more portfolio at constant headcount.