Related Blogs

« UK Cardholders Are Careful to Avoid Overlimit Penalties | Main | Analyzing Credit Trends by Age: Part Two »

Analyzing Credit Trends by Age

One of the things I enjoy most about being a data scientist is when I get to slice and dice data in various ways to identify important new trends. Recently, my team completed an analysis of how consumers of different ages changed their credit behavior before, during and after the Great Recession. Our study reveals some interesting trends.


The chart above shows average debt of consumers by age group at four points in time: well before the recession (October 2005), immediately before the recession (October 2007), immediately after the official end of the recession (October 2009) and the most recent time period (October 2012).

Not surprisingly, outstanding debt peaked in the period immediately before the recession for most age groups. After October 2007, there was a steady decline in debt for all age groups—except for consumers 60 years and older.

In fact, the most notable observation is that consumers aged 60 and over were the only age group who increased their debt levels. If we only look at the October 2005 and October 2012 periods, consumers 40 and over have more debt today than they did in 2005. By contrast, younger generations owe less in October 2012 than they did in October 2005.

Next, my team looked at how these changes impacted consumer FICO® Scores, given the importance of indebtedness on credit risk. The chart below shows the percentage of consumers by age group with FICO Scores greater than or equal to 760. For example, 11.2% of consumers in the 18-29 age group score 760 or greater in October 2012.


We observe two contrasting movements at the two ends of the age spectrum. A greater proportion of young consumers score higher in recent time periods, while a smaller proportion of older consumers have high FICO® Scores. Keep in mind that carrying lower debt has a positive influence on the FICO Score.

In an upcoming post, I’ll peel back another layer of the onion to better understand what is driving these changes in outstanding debt.

First time on the Banking Analytics Blog?
Subscribe to the Banking Analytics Blog Feed or check out some other recent posts:


John K

Just wondering, how do you account for shift from one age group to the next and how is that impacting the numbers shown in the graph? Thx.

Frederic Huynh

As we cycle through the four time periods, it is possible for an input record to shift into a different age group. Nevertheless, in the analysis presented, each series still represents the general credit trends for a particular age group at a particular point in time.

The comments to this entry are closed.