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.
Today in the United States, African Americans continue to suffer from financial exclusion and predatory lending practices. Meanwhile the advent of machine learning in financial services offers both promise and peril as we strive to insulate artificial intelligence from our own biases baked into the historical data we need to train our algorithms. A detailed […]
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