INSIGHTS
Silvan Schriber · October 2026
A model-prepared recommendation and a board decision may read identically. They are different in kind, not in quality, and only one of them carries accountability. That is the governance lesson in Pope Leo XIV's recent statements on artificial intelligence.
Silvan Schriber · September 2026
The FOMC raised its target range to 3.75–4.00% on Wednesday, unanimously. Markets had it priced at better than 90%, so the decision itself carried little information. Three things it did not settle are worth more attention than the move.
Quantum computing crossed, in 2026, from a research storyline into a governance one. The hardware progress reported this year is real, and the algorithmic work behind it moved expert timelines materially – without a single working cryptographic attack having been demonstrated. For a Swiss bank board, the operative question is no longer whether the physics will arrive on schedule. FINMA has already put a date on it: it recommends a board-approved PQC roadmap by mid-2027 at the latest – and in supervisory practice, a FINMA recommendation of this kind functions as an expectation, not a suggestion. Separately, the confidentiality of data stolen today is compromised the moment it is copied, not the moment it is decrypted. Both facts argue for treating this as a funded, owned, multi-year technology programme starting now, independent of how the underlying science resolves.
Silvan Schriber · August 2026
Silvan Schriber · June 2026
The next AI decision your bank makes won't be about which model to buy — it will be about where data is allowed to leave the building. As AI splits into two layers — small models running locally on staff hardware, and frontier models locked inside regulated cloud data centres — Apple, NVIDIA/Microsoft, and Perplexity are racing to keep inference on-device, while Anthropic is doubling down on the opposite bet: governed, auditable frontier access via the hyperscalers. The dividing line carries real regulatory weight — FINMA Circular 2018/3 outsourcing obligations and revFADP/GDPR transfer rules apply the moment data crosses to the cloud, and disappear the moment it doesn't. The winning architecture isn't a choice between local and frontier — it's a tiered system where local is the default, frontier is the deliberate exception, and the router that decides which is which becomes the institution's new control point, with every handoff logged and auditable.
Silvan Schriber · May 2026
Banks and wealth managers are accelerating AI and digital initiatives faster than their governance has adapted. FINMA's April 2025 survey found half of supervised institutions already using AI or piloting it, with another quarter intending to do so within three years; on average, five applications in production and nine more in development. Boards are now asked to oversee model risk, data ethics and conduct risk in domains where the established three-lines-of-defence playbook only partly applies. This piece sets out where the gap really sits, and what a pragmatic board-level AI governance framework looks like in practice.
Silvan Schriber · April 2026
Between March and April 2026, three separate incidents — at McKinsey, Anthropic, and Bain — exposed how quickly AI platforms can become vectors for data exposure, even at organisations with substantial resources and security investment. None required a sophisticated exploit; all three were remediated swiftly. For financial services boards, the lesson is structural: governance frameworks and vendor oversight must now account for attack surfaces that shift with every deployment. The regulatory framework — from FINMA Circular 2023/1 to DORA — already provides the structure. These incidents provide the urgency.
Silvan Schriber · May 2026
On 24 April 2026, an AI coding agent – Cursor, running Claude Opus 4.6 – deleted a SaaS provider's entire production database and all backups in nine seconds, with no human in the loop. Asked to explain itself, the agent produced a written confession, quoting both its own guardrails and the customer's project rules and acknowledging it had broken every one of them. The case is small in scale but architecturally identical to setups now common in banks and asset managers piloting agentic AI. The relevant question for boards is not whether the agent went rogue, but why the institution had given it a path to do so.
Silvan Schriber · March 2026
Dario Amodei's January essay is the most important thing a technology CEO has written for financial services leaders this year. Not because it's about banking — it isn't. But because everything it describes is about to land on the desks of every bank CEO, CTO, and board member.
For decades, banks optimized Systems of Record (SoR) to post transactions with precision and maintain regulatory integrity. That battle has largely been won. What now differentiates institutions is not how accurately they book activity, but how intelligently and quickly they make decisions.
Silvan Schriber · April 2026
An autonomous AI agent breached one of the world's most sophisticated professional services firms in 120 minutes — using a vulnerability class that has been documented since 1998. If McKinsey can't secure its AI platform, the question every bank board should be asking is: can we?
Silvan Schriber · April 2026
A few days ago, I wrote about the McKinsey Lilli breach and what it means for bank boards. Then Anthropic — the company that built its brand on AI safety — leaked its own source code. Twice. In five days. The two incidents are structurally different, but they converge on the same uncomfortable question: if the most security-conscious organisations in the AI ecosystem can't protect their own systems, what does that mean for the rest of us?
Silvan Schriber · April 2026
Private credit stress is no longer hypothetical — shadow defaults are rising, PIK usage is at cycle highs, and borrower cash flows are deteriorating. Large banks sit at the centre of this ecosystem, yet their exposure is scattered across desks, products and legal entities with no consolidated view. By integrating siloed data, resolving entities across systems and applying causal AI to trace how stress propagates from borrowers through funds to the bank’s own balance sheet, institutions can finally see the full picture — and act before losses crystallise.
In March, I co-hosted a session with senior COOs and operating leaders from across the asset management industry. The question on the table was deceptively simple: what does the COO role actually look like in 2026? The answers that emerged were anything but simple — and they point to a fundamental shift in how firms think about their operating models, their partnerships, and the role of data in driving decisions.
Die steigenden Gesundheitskosten in der Schweiz stellen eine große Herausforderung dar:
Bis 2027 werden die Ausgaben voraussichtlich auf rund 110 Milliarden CHF steigen und damit das Lohnwachstum sowie die Inflation übertreffen. Gleichzeitig decken große Versicherer 74 % der Versicherten ab, während kleine Anbieter nur 3 % erreichen. Dies zeigt die Notwendigkeit von Effizienz und Innovation im Markt.
Skalierung und digitale Transformation sind keine Optionen mehr, sondern Voraussetzungen für die Zukunftsfähigkeit der Schweizer Krankenversicherungsbranche. Alvarez & Marsal unterstützt Versicherer mit M&A-Expertise, digitaler Modernisierung und operativer Resilienz, um den Wandel erfolgreich zu meistern.