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Security

As explained in Financial AI in Practice

The protection of systems, information, and operations against unauthorized access, disruption, or harm.

In financial AI, security is a prerequisite for public trust in a strictly regulated environment. It protects the system before a query reaches the model. section 2.6 section 3.2.1

A front-door security layer authenticates users, enforces usage policies, and strips or masks personally identifiable information (PII) so sensitive customer data does not reach the model unsecured. section 3.2.1

How Financial AI in Practice covers it

How deep it goes
Specifies authentication, usage-policy enforcement, and PII stripping or masking before model access, without implementation details.
Examples
Illustrates protecting a user query by masking customer PII before it reaches the model.
What you can do after
Operate/configure a front-door layer to authenticate users, enforce usage policies, and strip or mask PII before model processing.
How it connects
Connects financial AI security with authentication, usage policies, personally identifiable information, and input guardrails.

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This explainer was generated by Manning's knowledge graph from the text of Financial AI in Practice. The section links point to the parts of the book it draws on.