The increasing usage of new data sources and machine learning (ML) technology in credit modeling raises concerns with regards to potentially unfair decision-making that rely on protected characteristics (e.g., race, sex, age) or other socio-economic and demographic data. The authors demonstrate the impact of such algorithmic bias in the microfinance context. Difficulties in assessing credit are disproportionately experienced among vulnerable groups, however, very little is known about inequities in credit allocation between groups defined, not only by single, but by multiple and intersecting social categories. Drawing from the intersectionality paradigm, the study examines intersectional horizontal inequities in credit access by gender, age, marital status, single parent status and number of children. This paper utilizes data from the Spanish microfinance market as its context to demonstrate how pluralistic realities and intersectional identities can shape patterns of credit allocation when using automated decision-making systems. With ML technology being oblivious to societal good or bad, we find that a more thorough examination of intersectionality can enhance the algorithmic fairness lens to more authentically empower action for equitable outcomes and present a fairer path forward. We demonstrate that while on a high-level, fairness may exist superficially, unfairness can exacerbate at lower levels given combinatorial effects; in other words, the core fairness problem may be more complicated than current literature demonstrates. We find that in addition to legally protected characteristics, sensitive attributes such as single parent status and number of children can result in imbalanced harm. We discuss the implications of these findings for the financial services industry.

Today is National Single Parents Day and Match has unveiled a new app designed to help such folks find love. The aim of Stir is to help single parents meet, chat with and date folks who also have kids. Match says there are around 20 million single parents in the US who are often underserved by many dating apps. After you answer questions on personality and values, Stir will show you potential matches. Once you find someone you have a spark with, you'll be able to arrange a date.

Women in politics are sometimes accused of consciously exploiting their femininity to get ahead in a male-dominated world. Frances Perkins did that, but in an unusual way: she tried to remind men of their mothers. She dressed in a plain, three-cornered hat, and she refined the way she acted, based on careful observation of what seemed to be most effective in persuading men to accept her ideas. Perhaps it's no coincidence that those ideas could reasonably be described as maternal or parental. Any parent wants to shield their children from serious harm, and Perkins believed governments should do the same for their citizens. She became President Franklin D Roosevelt's Secretary of Labour in 1933.