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Scenario 4: Trust shock

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In the fourth scenario, a major failure linked to artificial intelligence undermines public trust. The trigger could be a market disruption caused by correlated trading algorithms, a large fraud using deepfakes, a data breach at a provider of models used by many banks or a discriminatory credit system that harms thousands of clients. Whatever the cause, the reaction is political. Legislators in Switzerland and the European Union adopt restrictive rules, supervisors require extensive approval procedures and institutions withdraw AI tools from client-facing functions.1

In this scenario, the gains of the technology would be delayed. Institutions that had invested heavily in automation would face costs of reversal, while those that had maintained human processes and strong governance would gain an advantage. Clients would value discretion, personal contact and demonstrable control, qualities that Swiss private banking has long claimed. The parallel with the history of Swiss banking is instructive, because the crises that ended banking secrecy for foreign clients also began as failures of trust and led to rules that transformed the industry. Indicators of this scenario would be a rising number of AI-related incidents, public debates on the liability of providers and political initiatives for moratoria or strict licensing.

Notes

  1. Scenario constructed by the author. On the role of crises in triggering regulatory change, see Part F, Chapter III on the regulatory response to the collapse of Credit Suisse. ↩

For general information only. This article does not constitute legal or tax advice, does not replace advice on an individual case and creates no lawyer-client relationship. It reflects the legal position as of August 2025.

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