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Interview

Viewpoint: The shifting frontlines
of business conduct risk

Dr. Philipp Aeby

Interviewee

CEO and Co-founder

April 2026

Viewpoint: The shifting frontlines of business conduct risk

Transparency and trust are cornerstones of responsible risk management. They sit at the heart of RepRisk and our mission.

"To provide transparency on business conduct risks to drive positive change."

Navigating a turbulent and dynamic risk landscape requires high-quality business conduct data to drive timely and sound decision-making.

Banking and asset management executives are clear: business conduct data is no longer limited to the compliance department. It is now a strategic imperative, and successful institutions are savvy when considering the robustness of the data used in decision-making.

As AI becomes a more material conduct issue, risk leaders know that the way their data is generated matters just as much as the insights themselves. As companies seek to leverage agentic AI and integrate data as part of optimized workflows, those more advanced in their strategies know that they cannot rely on business conduct data that is generated from AI-only outputs alone (i.e., without expert human intelligence).

Caution must be exercised, as random and misleading data too often leads to costly mistakes and results in far-reaching implications. False positives and false negatives, and lack of transparency, explainability, or auditability, are the biggest concerns, as untrained AI-only data is more prone to hallucination. Inconsistent sources and opaque methodologies that break time series comparability reinforce the importance of defensible, stable methods when data is used to inform successful long-term investment strategies.

Hybrid human-AI methodologies that combine the scale and speed of advanced technology with the discernment of expert human judgement, have emerged as the most trusted and the most capable of delivering decision-grade risk intelligence. By contrast, AI-only and purely human approaches fall short in different ways, either lacking reliability and transparency, or speed and breadth. As business conduct risks intensify, data is key when the high stakes include fiduciary responsibility, regulatory accountability, and value creation.

As a pioneering AI company with humans in the lead, RepRisk continues to set the global standard for business conduct risk data. As we mark our twentieth year of operations, we are proud to provide clients with trusted, decision-ready data that is known for its relevant coverage, unparalleled accuracy, timely insights, and historical benchmarks. In a world where the cost of poor information is rising, transparency, and trust are essential for success.

The Business Conduct Risk Intelligence Report 2026, commissioned by RepRisk in collaboration with Oxford Economics, sheds further light on how C-suite leaders are evaluating the trustworthiness and strategic value of business conduct risk data. I hope the insights and recommendations in the report spark meaningful conversations and help to surface the questions that matter most when appointing a business conduct data partner. I look forward to exchanging perspectives and ideas on tackling the new risk landscape.

Read the full report

Insights from 500+ C-suite leaders on the future of business conduct risk and risk intelligence.

Download the report

Bio - Dr. Philipp Aeby, CEO and Co-founder

Dr. Philipp Aeby is the CEO and co-founder of RepRisk. He is an expert in business conduct risk management, with a special interest in machine learning. Before joining RepRisk in 2006, Philipp served in various managerial positions across Europe at Amgen, a global biopharmaceutical firm, and worked on a broad range of international assignments with the Boston Consulting Group. He started his career as a visiting scientist at the International Center for Tropical Agriculture in Colombia. Philipp holds a PhD in Environmental Physics and a Master’s degree in Climatology and Hydrology from the Swiss Federal Institute of Technology (ETH) in Zurich, Switzerland, where he earned the ETH Medal for outstanding research that involved applying neural networks to pattern recognition.

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