The problem is that as we all know, many companies will simply ignore corner cases - it is too expensive, and many people making the decisions trust the correlations and confuse them with causes because they frankly don't understand how the analysis was arrived at.
A simple, and topical example is flood insurance. Insurance companies make use of postcode data to assess flood risk. It will work in, say, the middle of Carlisle where postcodes uniquely refer to a very small area. 45 miles away, the postcode refers to a much larger area. A colleague of mine, and a number of his neighbours found that they were either refused insurance or had massive premium hikes by a number of companies, because this area includes a stream that floods, and having seen it this winter, a 2 metre rise in water levels is quite impressive.
All well and good, but there is only one houses down there. All the other houses in that post code are at least 50 metres above the level of the water. It seems those companies have made a decision to use what in practice is a very crude and inaccurate risk assessment simply because it works elsewhere. They won't change because their business processes would make it too expensive to do so.
A trivial example, but there are much more subtle decisions being made on the basis of complex data analysis and I fear no matter what organisations such as the FTC 'mandate', they will carry on discriminating though ignorance.