Strategy and execution for banks, insurers and financial firms
Financial institutions must hold together FINMA requirements, risk control and economic performance. We build your strategy, deploy it across your organisation and steer the results with you.
Banks, wealth managers, insurers and financial infrastructures operate within a dense regulatory framework, where every strategic decision affects capital, compliance and reputation. In Switzerland, FINMA's expectations on governance, risk management and anti-money laundering shape the daily agenda of executive teams and leave little room for approximation.
For each engagement, we compose a senior team: a dedicated contact, the WALVIS core team (strategy, finance, operations, data, AI) and sector experts from our network, selected for their expertise profile. We work with your existing tools, we do not sell software, and we stay engaged until results are visible in your figures and in your processes.
The industry’s challenges
FINMA requirements keep evolving and overlap with international standards, which makes implementation harder. We turn them into readable processes, defined responsibilities and control evidence you can actually use.
Client due diligence, transaction monitoring and alert handling often produce more volume than signal. We clarify the risk-based approach so that your teams spend their time where the risk is real.
Margin pressure, the cost of compliance and legacy systems weigh on the business model. We arbitrate priorities, sequence the workstreams and tie each initiative to a financial effect that is tracked.
Where AI makes the difference
AI can triage alerts, extract information from client files and summarise regulatory texts, under human supervision. It does not replace the compliance officer's decision or the traceability of the reasoning behind it.
Many gains come from clear roles, well-articulated lines of defence and simple procedures. Here, common sense and organisation are enough, with no added technology.
Reliable indicators built on your existing data give the executive team a shared view of the situation. Predictive models come in only where data quality allows and where their results remain explainable.