
Understanding AI bias in banking
AI systems could unfairly decline new bank account applications, block payments and credit cards, deny loans, and other vital financial services and products to qualified
AI systems could unfairly decline new bank account applications, block payments and credit cards, deny loans, and other vital financial services and products to qualified
Through a case study of mortgage applications, this article shows how bias might be introduced to AI systems by either bias within historical data, and/or
This short article looks at the link between the lack of diversity in the AI workforce and the bias against ethnic minorities within financial services
A detailed summary of research by Mark Weber, Mikhail Yurochkin, Sherif Botros and Vanio Markov, breaking down the lack of racial justice in the current
Explains (from a US perspective) how the development of machine learning and algorithms has left financial services at risk of exacerbating biases. Using the example
There is data which predicts that the introduction of AI into the financial system will bring with it increased racial bias and discrimination. Through a
This US focused report considers four distinct ways of incorporating Artificial Intelligence into credit lending. It highlights the existing racial bias in credit scores, where
Algorithms can be used to decide when to withhold loans, mortgages and even bank accounts, on the basis of who is likely to make money for the bank. Minority ethnic groups can be disproportionately disadvantaged within these prediction systems by being determined as not meeting the criteria for lending, even when others with the same financial status get approved.
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