Data security in AI deployment requires layered protections: encryption and access controls for sensitive data, model risk management and cybersecurity integration. Jack Henry’s security guidance for banks recommends encrypting customer data, enforcing strict access controls, auditing data usage and using anonymization and differential privacy techniques. Regular model validation, monitoring for bias and adversarial vulnerabilities, and third‑party risk oversight are also key.
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How is data security maintained when banks deploy AI models?
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