« Count data are less useful than you think | Main | I can't believe I'm citing David Brooks on data »


Feed You can follow this conversation by subscribing to the comment feed for this post.

Jon Mellon

I'd be interested to know whether a relatively smaller bank (in terms of customers at least) like Schwab has more difficulties with this. Presumably, your ROC curve gets better with more data (or better data analysis anyway) so the larger banks like BoA will be able to do a better job predicting fraud.

It's also worth considering that the probability of these types of fraud may be low precisely because of these kinds of protections. In a world where we accepted more false negatives, there would be an increased incentive to try and defraud these systems.

Also, banks may be in a race to the bottom (or top depending on how you view it) not to be perceived by fraudsters as the easiest target. BoA don't want it to get around that BoA has the loosest fraud rules or we get the same incentive effect as above.

I guess what I'm saying is that it's at least a possibility that this level of false positives is an equilibrium that you can't easily go below (because true positives increase in response).


I've wondered about these algorithms in another context: the push by my local supermarket chain to "scan" guns you as customer wield as you fill your cart. I loved being able to walk up to a register, point the scanner at a barcode and have it download everything I've bought to the register so I can pay and leave very quickly. Problem: it asked for a bag check. OK, they need to do some form checking: the light flashes and a cashier has to come over, unload every single item and scan each one. Next time, it asked for a bag check. I said something to a manager. Next time it asked for a bag check. Manager gave me a new number (though of course it was still my customer information). Next time it asked for a bag check. I called corporate. They had no ideas at all. Not kidding: they couldn't figure out what was happening, if I was just on some weird run of luck or if, as I suspected, some data field had corrupted and that defaulted me automatically to bag check. It was simply beyond them to figure it out.

I would suspect the rejection flag was never reset in your case. That may require more intervention, like a ticket for work, than a phone call can easily generate or than a phone call can cause to happen overnight.

Thinking about it, years ago I had a problem with charges suddenly being denied by AMEX. No one could figure out why. I ended up talking to the executive offices and was told the problem was - this is kind of funny in retrospect - that it originated in how their balance carrying credit cards worked with their old-fashioned pay it all off cards. That is, if you took out one of their actual new credit cards they hadn't correctly connected the approval mechanism for that to the one used for the charges you made on your regular AMEX card. They were getting reports of charges being denied for customers like me and the only solution they had for now was to delete the credit card account. Not kidding. Stuff like this happens. Builds break. Your build may work fine for your department but break what another department uses.


These days cash withdrawals are less common and therefore probably considered more suspicious by fraud detection software. Given the roaming fees you incurred, it seems you may have been better off paying the credit card transaction surcharges.


Josh: That was exactly what irked me. Schwab has now offered to pay for the roaming charges so at least the monetary loss is taken care of. Cash is definitely still an important thing especially in a foreign country.

Jon: I don't think the generic concept of "big data" is useful at all. What kinds of data do big banks have more of? These banks need more "cases"; adding more non-fraudulent transactions don't improve the algorithms. One could argue that maybe small banks are more targeted by fraudsters so they may even have better data. The other issue is the adversary. Historical data are not as useful as it seems because the adversary is constantly adapting and actively gaming the system.


Couldn't you use credit card at the suit place? The $100 you paid in roaming is more than credit card charge on fx conversion.
you are behaving to your hard coded algorithm of not using a credit card.

The comments to this entry are closed.

Get new posts by email:
Kaiser Fung. Business analytics and data visualization expert. Author and Speaker.
Visit my website. Follow my Twitter. See my articles at Daily Beast, 538, HBR, Wired.

See my Youtube and Flickr.


  • only in Big Data
Numbers Rule Your World:
Amazon - Barnes&Noble

Amazon - Barnes&Noble

Junk Charts Blog

Link to junkcharts

Graphics design by Amanda Lee

Next Events

Jan: 10 NYPL Data Science Careers Talk, New York, NY

Past Events

Aug: 15 NYPL Analytics Resume Review Workshop, New York, NY

Apr: 2 Data Visualization Seminar, Pasadena, CA

Mar: 30 ASA DataFest, New York, NY

See more here

Principal Analytics Prep

Link to Principal Analytics Prep