Risk-adjusted compensation framework for bankers

Peter Haenni

13 Mar 2025 — 1 min read

SIPOC map auto generated by the ProcessHorizon web app

A risk-adjusted compensation framework for bankers should include the notion of a referential base salary cap, tied to a percentage of the bank's capital reserves.

1. Base Salary e.g. 0.1% tied to Capital Reserves (Eigenkapital)

2. Risk-Adjusted Performance Bonus (30%)

3. Deferred Performance Bonus Compensation (30%)

4. Personal Responsibility for Regulatory Fines and Penalties (15%)

5. Equity Compensation and Stock Options (25%)

6. Clawback and Risk Management Mechanisms

Such a risk-adjusted compensation framework effectively links executive pay to a bank's capital reserves, financial health and risk management practices.

By tying base salary to a percentage (e.g. 0.1%) of the capital reserves, it ensures that compensation remains aligned with the bank’s financial stability, discourages excessive risk-taking and promotes long-term value creation.

Additionally, personal responsibility for regulatory fines and clawback provisions ensure that executives are accountable for their actions, further enhancing governance and risk management practices within the institution.

Universal Event-driven SIPOC Action Architecture

My objective was to provide one universal, intuitive and stakeholder-oriented Action Architecture for understanding, designing, governing and executing value-creating activities across the enterprise, from business modeling to autonomous AI operations. The architecture consists of five interconnected layers, each using the same Event-driven SIPOC methodology, with explicit objectives, trigger events, process

Integrated Quality Management within GRC: A Foundation for Responsible Agentic AI

Governance defines what should be achieved. Risk Management determines what could go wrong. Compliance establishes what must be respected. Quality Management ensures that processes and their outcomes consistently fulfill requirements & intended objectives. Together, they establish an integrated management system for responsible human & AI-driven enterprise operations. Event-driven SIPOC model

AI Literacy: The 5-stage event-driven AI Operating & Control model

My objective is for AI users to understand: how information becomes AI intelligence, how intelligence is used to perform tasks & how the entire journey is governed to produce reliable, safe & useful outcomes. The five-stage event-driven AI Operating & Control model follows the analogy of the Vacuum Cleaner sucking

Innovation-driven growth model

Inspired by last year's nobel prize winners in Economic Sciences, Joel Mokyr, Philippe Aghion & Peter Howitt, I am proposing a value chain focusing on the processes & data from Knowledge to Innovation to Process Transformation to Value Creation to Economic Growth and eventually to New Innovation Opportunities.

Read more

Universal Event-driven SIPOC Action Architecture

Integrated Quality Management within GRC: A Foundation for Responsible Agentic AI

AI Literacy: The 5-stage event-driven AI Operating & Control model

Innovation-driven growth model