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A case study examining ethical algorithm concerns in an automated user loan system — analyzing systemic bias, fairness, and accountability in financial decision-making.

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Ethical Algorithm Analysis: User Loan System

Author: Mbachu Emmanuel Ebube

Credit: Mr. Bill Kowaski – My Teacher
Case Study based in Canada


Overview

This repository contains a case study analyzing ethical concerns in an automated User Loan System.
The study explores how algorithmic decision-making in financial institutions may unintentionally reproduce human or systemic biases, affecting users applying for business loans.


Objective

To examine how a simple loan-approval algorithm can raise six major ethical concerns:

  1. Inconclusive Evidence
  2. Inscrutable Evidence
  3. Misguided Evidence
  4. Unfair Outcomes
  5. Transformative Effects
  6. Traceability

Each concern is mapped to its real-world implication within financial lending processes.


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A case study examining ethical algorithm concerns in an automated user loan system — analyzing systemic bias, fairness, and accountability in financial decision-making.

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