10 Matching Annotations
  1. Aug 2017
    1. To conclude, the possibility of receiving a loan increases based on our experience. In some cases, we have even seen a drop in the interest rate. This results in more people receiving access to credit with a better interest rate thanks to increase of scoring model accuracy. We believe that designing systems from the start in discrimination-conscious way will reduce the risk of machine-learning algorithms introducing unintentional bias much like humans do. This should avoid the moral problem of discrimination. In addition, requiring drivers to pass an eye test discriminates against the blind, but eyesight is quite essential to safely drive a car. As the last exclusion is justified then loaning to people who are not creditworthy should be an acceptable exclusion as well.
    2. big data scoring credit score financial inclusion