Description: Financial bias refers to discrimination in financial services driven by artificial intelligence (AI) algorithms, affecting access to loans and credit. This phenomenon occurs when AI models designed to assess the creditworthiness of applicants incorporate historical data that reflects social and economic inequalities. As a result, certain groups, especially those from minority communities or low-income backgrounds, may be unfairly penalized, limiting their access to financial resources. Financial bias not only raises ethical concerns but can also perpetuate cycles of poverty and social exclusion. The lack of transparency in algorithms and the difficulty in auditing their decisions exacerbate the problem, as affected users often have no way of understanding why they are denied a loan. This type of bias reflects how technology, rather than being a neutral tool, can replicate and amplify existing inequalities in society. Therefore, it is crucial for financial institutions and AI developers to work on creating fairer and more equitable models that consider the diversity of applicants and promote financial inclusion.
