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. Minority groups are often treated as high risk (more likely not to pay back money) because of the use of proxy data in financial institutions. This means that people from minority ethnic groups can find it hard to get credit, and get offered higher interest rates, widening poverty gaps.
The impact of artificial intelligence in consumer lending. 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 white / non-hispanic individuals are likely to have a much higher credit score than black / African American individuals. And argues that […]
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