Introduction Algorithms are making hiring and legal decisions faster — and riskier. From biased resume screeners to opaque background‑check pipelines, teams are increasingly asked to justify automated outcomes to candidates, regulators and internal auditors. When records are scattered across tools or lodged with engineering, audits stall, subject‑access requests slip, and sensitive data exposures multiply. Document […]
Tag: model risk management
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