@Anonymous wrote:Looking to have a discussion on this topic, as I know there will be differing opinions. We know that score ranges for different scorecards can overlap in spots. As a result, someone that has a positive change happen to their file could result see a score drop. I understand that scorecards are based on groups of people with similar profile data and that we really shouldn't get hung up on any one individual example. For me though personally, I don't necessarily agree with how that works. If a Fico score is a representation of risk / likelihood of default, it doesn't make sense that a positive profile change would result in a lower score.
For example, someone reaches an age of accounts scorecard reassignment that results in a score drop. Looking at that individual alone, there's no way that they became more of a risk (lower score now) due to positively crossing an age of accounts threshold. Now that person lost (say) 20-30 points which could be the difference between X rate and Y rate on a new mortgage. That just seems counterproductive to me.
Anyway, I get it that it "is what it is" and how the system works when looking at groups of individuals and that it isn't going to be perfect at all times. Just curious to hear thoughts from others on this topic, whether you think it matters and/or if you believe this issue should be addressed. If so, what would you propose... such as no overlapping score cards, for example?
1. I do agree that it would be inappropriate for someone's score to drop due to a positive change in their profile, just because the positive change resulted in a scorecard reassignment.
2. This has never happened to me, and I have been on different scorecards.
3. Personally, I think the frequency of this occurring is greatly overrated by the cognoscenti among us. In my opinion it's not a big deal only because it doesn't really happen much, if ever.
@Curious_George2 wrote:@Anonymous:
Isn't the fundamental problem the existence of the scorecards (bins)? Seems like anytime one uses bins, there will be some number of sub-optimal risk calculations at the edges, when an individual moves from one bin to the next. Getting rid of the bins would eliminate that, but you say binning is necessary.
The factory example makes sense, but can you explain why binning is necessary in the consumer credit scoring context? Shouldn't the vast number of datapoints, even in a sample spanning just a few years, make it possible to dispense with bins? Whereas you had no information about machines like yours performing in that particular environment, it seems like FICO must have data about huge numbers of consumers with essentially identical profiles making any particular change (e.g. hitting 2 yrs AoOA).
The binning is necessary because the number of 'bads' is going to be significantly different for those just starting out with credit compared with a group that's been managing credit for a much longer time. Like a new robot design performing in a factory for the first time compared to the old proven design (that probably used a lot more energy or took longer, but was incredibly reliable).
Some things just don't change with time, like a relatively high proportion of college kids getting their first credit card or auto loan and defaulting within a year or two. That's why a static profile dataset from 2006-2008 isn't such a bad thing for FICO 8.
But sometimes data from a certain timeframe can include too many in the bad category, which is why they update models from time to time, as shown here:
They cited changes in consumer behavior including:
- Mortgage crisis and Great Recession
- Decrease in consumers with new account openings
- Consumers seeking credit less often