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Case Study: Finance 

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Fixing AI Bias Before Regulators Do It for You

<p class="large">A major bank’s AI-driven loan approval system was flagged for bias—denying too many applications from certain demographics. With regulators watching and lawsuits looming, they needed a fix. Fast.</p>

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The Problem

<p class="large">- Audited their AI’s decision-making process to uncover where bias crept in.</p>
<p class="large">- Reworked risk assessment criteria to align with fair lending practices.</p>
<p class="large">- Implemented ongoing bias monitoring to catch issues before regulators did.</p>

What We Did

<p class="large">✔ 25% fewer unfairly rejected applications, expanding fair access to credit.</p>
<p class="large">✔ Passed regulatory audits with zero issues.</p>
<p class="large">✔ AI decisions that held up under scrutiny—no more black-box excuses.</p>

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Results

<p class="large">AI doesn’t get a free pass just because it’s ‘data-driven.’ If you don’t check for bias, regulators will—at your expense. We made sure this bank’s AI worked ethically and legally before anyone else had to step in.</p>

The Takeaway

Danny Katz Consulting

We help companies fix knowledge chaos, streamline AI governance, and build systems that actually work. Whether it’s unsearchable knowledge silos, AI making bad decisions due to bad data, or compliance teams struggling with operational execution—we solve the problems that stall productivity, increase risk, and waste time.