Model Impact on Business Processes

Model Impact Analysis on Business Processes refers to the practice of analysing probabilistic models and machine learning models.

The analysis is done in a way that ensures equitable and unbiased treatment of different groups or individuals. It involves addressing and mitigating potential sources of bias in the data, algorithms, and model development process to avoid discriminatory outcomes.

Why is Model Impact Analysis on Business Processes important?

Fair model training considers factors like race, gender, age, or other protected attributes to prevent models from perpetuating unfair disparities or unjustly favouring certain groups.

This policy sets guidelines for evaluating, monitoring, and adjusting models to achieve fairness and ensure that they produce equitable predictions or decisions that align with ethical and legal standards, promoting a just and inclusive business environment.

How does FAIRLY perform Model Impact Analysis on Business Processes?

The project is assessed through a collaborative effort. Evaluation involves a combination of qualitative questionnaire-based assessment and quantitative model testing. Supporting evidence can be attached to each of the controls to substantiate the provided answers.

Specifically, we perform Business Process Analysis on Human Interventions to ensure consistency in the frequency of human interactions across different groups is crucial to promote fairness and prevent discrimination in various decision-making processes, such as lending, hiring, or criminal justice.

When these percentages vary significantly across groups, it can indicate disparities or biases in the system, potentially leading to unequal opportunities and treatment.

Consistency implies that individuals from different racial or ethnic backgrounds have an equal likelihood of positive outcomes, which aligns with principles of fairness and equity.

Monitoring and addressing disparities in these outcomes help organizations identify and rectify systemic biases, fostering a more just and inclusive environment while complying with legal and ethical standards.

We also perform Differential Analysis on Target Variable to ensure consistency in the target values across different groups.This is crucial to promote fairness and prevent discrimination in various decision-making processes, such as lending, hiring, or criminal justice.

When these percentages vary significantly across groups, it can indicate disparities or biases in the system, potentially leading to unequal opportunities and treatment.

Consistency implies that individuals from different racial or ethnic backgrounds have an equal likelihood of positive outcomes, which aligns with principles of fairness and equity.

Monitoring and addressing disparities in these outcomes help organizations identify and rectify systemic biases, fostering a more just and inclusive environment while complying with legal and ethical standards.