A financial institution relied on a legacy credit risk model for automated loan decisions. While the model was functional, the institution had growing concerns about its fairness and susceptibility to emerging risks. Without a clear auditing framework, they were exposed to significant regulatory risk, reputational damage, and potential financial losses from an unreliable system.
We developed and executed a rigorous model auditing framework focused on three critical dimensions of AI governance: performance, equity, and robustness. This holistic approach provided a complete, evidence-based assessment of the model's capabilities and its hidden vulnerabilities.
We delivered a comprehensive model audit report and an interactive monitoring dashboard. This system provides real-time insights into the model's health, performance, and fairness metrics, with automated alerts for any significant deviations. It transformed the client's approach from reactive to proactive, ensuring continuous model reliability and compliance.
Our audit transformed the client's model from a liability into a reliable, fair, and future-proof asset. We achieved over 70% vulnerability mitigation and a significant bias reduction.
Our team of experts can audit your models for performance, equity, and robustness, protecting your business and reputation.
Each project is a testament to our commitment to turning complex data science into concrete business outcomes that drive growth and innovation
