5 ms·

I love these. Building fraud detection systems is so funny because the signals themselves end up usually being really simple, it's just a matter of: a) Having

by wdewind 12y ago

I love these. Building fraud detection systems is so funny because the signals themselves end up usually being really simple, it's just a matter of: a) Having the tools to look at all your data to see where the patterns are b) Having the tools to track instances of patterns once you've identified them. But as I said, the patterns themselves are usually pretty simple, as you see in this article. This one is a bit specific to Justworks since we use bank account numbers instead of credit card numbers, but one we've picked up is the source of the bank account is a great signal. If a company has bank accounts exclusively from certain banks then they are almost certainly fraudulent. We've even seen people try to sign up with consecutive bank account numbers from the same banks!

aestra 12y ago
This goes for other industries as well. For example every insurance claim from any insurance company is run through fraud detection software. Turns out there are some characteristics of a fraudulent insurance claims that have been identified over the years. The software can flag a claim as potentially fraudulent for further human review. Discover Card's fraud detection worked extremely well in my case. My CC number was stolen and after only two fraudulent transactions (total about $500) it tripped the software to freeze the card. I have no idea how they identified those as fraud so quickly, they didn't seem out of place to my eyes considering my transaction history.
- Mz 12y ago
  For example every insurance claim from any insurance company is run through fraud detection software. Turns out there are some characteristics of a fraudulent insurance claims that have been identified over the years. The software can flag a claim as potentially fraudulent for further human review. I worked for an insurance company for over 5 years, processing claims. This is the first I have ever heard this. Which does not prove it to be untrue but does make me skeptical. We had some claims automatically paid via computer but most claims were reviewed by human eyes. Humans were trained to look for indicators of fraud. There was no one thing that would get it sent to the fraud department for investigation. We were looking for a pattern or multiple indicators.
  - aestra 12y ago
    >We had some claims automatically paid via computer but most claims were reviewed by human eyes. Humans were trained to look for indicators of fraud. There was no one thing that would get it sent to the fraud department for investigation. We were looking for a pattern or multiple indicators. Oh, I'm never saying that claims get paid automatically or that humans don't look for fraud too. I'm saying that there is also software on the back end that flags things to go to the fraud department automatically. Probably without your knowledge. I just remember reading an article about it a while ago - just about how good it has gotten over the years and it has become an important part of the insurance industry. Just another example of extensive data mining. When I say "every insurance claim from any insurance company" I mean that I assume any insurance company worth anything would be running such software. Found some products: http://www.csc.com/p_and_c_general_insurance/offerings/26121/57633-fraud_detection_software_fraud_prevention_via_analytics http://www.csc.com/p_and_c_general_insurance/offerings/26121... http://www.sas.com/en_us/industry/insurance/fraud-framework.html http://www.sas.com/en_us/industry/insurance/fraud-framework.... AllState implies they do. http://www.allstate.com/claims/fight-fraud.aspx http://www.allstate.com/claims/fight-fraud.aspx >Through the use of innovative technologies and network analysis tools, we are able to help detect and stop these crimes
    - Mz 12y ago
      Ok. But I think you are still misinformed --> For example every insurance claim from any insurance company is run through fraud detection software. From digging around, this seems kind of a new trend. I seriously doubt that "every claim at any insurance company" is being analyzed this way. And, sure, it's possible it was in use at the company where I worked and I simply did not know. But from reading some of what you linked to, I doubt it. (Though perhaps that has changed since I left.) From one of the sites you linked to: "Industry research indicates 10 percent of all claims contain an element of fraud," says Wolfe, and as of the end of 2010, CNA was seeing just 3.7 percent of its claims referred as potential fraud. "That’s considerably below the industry average, and we wanted to find out how much we were missing that wasn’t identified by our adjustors." So, yeah, that's relatively recent and the searches I did sort of imply that this is an emerging market, they are still trying to convince insurance companies to do this, etc. Insurance is a very conservative industry. They tend to be somewhat slow to adopt new technologies. They are regulated by both federal laws that cover financial companies and also federal laws that cover medical companies (like HIPAA). So they have a huge regulatory burden and this makes change especially hard. Any new tech or new processes have to really be put through their paces to see if they still pass muster on multiple fronts. The de facto result is that insurance companies are kind of sticks in the mud. Where I worked, a lot of the software was homegrown. It had been developed in-house. They didn't like hiring outside vendors/buying outside solutions. From what I gather, they were fairly cutting edge -- though, of course, it is possible that was just company hype. Since I worked there, I sometimes knew that some statements amounted to spin-doctoring. But I did only have an entry level job and was not really expecting it to turn into a career, so I am sure there is plenty that I missed. Thanks for replying.
- superuser2 12y ago
  Sometimes the pattern only exists in data writ large. For example, a particular merchant is breached, and then the fraudsters try to run most of the cards stolen in that breach at a few locations. It could be obvious on your bank's end that a few dozen customers made a charge at Store A and then reported a charge at Store B to be fraudulent, so then they decided to freeze the cards of everyone with the same Store A -> Store B pattern.
  - aestra 12y ago
    Great point.
- NoMoreNicksLeft 12y ago
  Quite possibly, they saw the same item purchased 5 times within minutes, all off of other Discover cards. You'd only see the transaction that used your number.
- x0x0 12y ago
  I've heard that good signals are things like small gas purchases at a gas station you haven't been to before; they're used to test card validity at a pay-station with no human present.
  - meowface 12y ago
    This has been such a common signature for fraud over the years that I'd be surprised if many fraudsters are still doing this. If they were smart they'd buy a chocolate bar from a grocery store that has self-checkout, then buy something a little more expensive from Target or whatever, then buy the very expensive thing they really want.
    - Estragon 12y ago
      What's the purpose of the target purchase?
      - tatterdemalion 12y ago
        I think because it masks the "tiny purchase -> giant purchase" signal that is used to detect fraud?
        Estragon 12y ago
        Ah, thanks.
      - x0x0 12y ago
        a guess: probing the available balance. Presumably, you only get a couple shots at the apple store to buy that laptop because a single person isn't going to be able to try 5 cards with different names on them in a row without the police being called.
- keithpeter 12y ago
  Do you tend to go shopping for a given product at the same kind of times/days? E.g. for me clothes shopping is on Saturday or Sunday. Do you tend to go to certain physical locations or use a limited number of Web sites to buy from? Just guessing.
  - aestra 12y ago
    Nope! My spending habits are kinda random and I travel a lot.
andreyg 12y ago
Disclaimer: I work here. Thanks @wdewind! We do too. We had a field day playing with the data. We actually have thousands of features and these are just some of the most simple signals. We're really careful not to disclose some of our more complex (and powerful) ones - but I can say that we statistically model patterns such as position of digits in email address, page visit sequence, etc.

by wdewind 12y ago

aestra 12y ago

This goes for other industries as well. For example every insurance claim from any insurance company is run through fraud detection software. Turns out there are some characteristics of a fraudulent insurance claims that have been identified over the years. The software can flag a claim as potentially fraudulent for further human review. Discover Card's fraud detection worked extremely well in my case. My CC number was stolen and after only two fraudulent transactions (total about $500) it tripped the software to freeze the card. I have no idea how they identified those as fraud so quickly, they didn't seem out of place to my eyes considering my transaction history.

Mz 12y ago
For example every insurance claim from any insurance company is run through fraud detection software. Turns out there are some characteristics of a fraudulent insurance claims that have been identified over the years. The software can flag a claim as potentially fraudulent for further human review. I worked for an insurance company for over 5 years, processing claims. This is the first I have ever heard this. Which does not prove it to be untrue but does make me skeptical. We had some claims automatically paid via computer but most claims were reviewed by human eyes. Humans were trained to look for indicators of fraud. There was no one thing that would get it sent to the fraud department for investigation. We were looking for a pattern or multiple indicators.
- aestra 12y ago
  >We had some claims automatically paid via computer but most claims were reviewed by human eyes. Humans were trained to look for indicators of fraud. There was no one thing that would get it sent to the fraud department for investigation. We were looking for a pattern or multiple indicators. Oh, I'm never saying that claims get paid automatically or that humans don't look for fraud too. I'm saying that there is also software on the back end that flags things to go to the fraud department automatically. Probably without your knowledge. I just remember reading an article about it a while ago - just about how good it has gotten over the years and it has become an important part of the insurance industry. Just another example of extensive data mining. When I say "every insurance claim from any insurance company" I mean that I assume any insurance company worth anything would be running such software. Found some products: http://www.csc.com/p_and_c_general_insurance/offerings/26121/57633-fraud_detection_software_fraud_prevention_via_analytics http://www.csc.com/p_and_c_general_insurance/offerings/26121... http://www.sas.com/en_us/industry/insurance/fraud-framework.html http://www.sas.com/en_us/industry/insurance/fraud-framework.... AllState implies they do. http://www.allstate.com/claims/fight-fraud.aspx http://www.allstate.com/claims/fight-fraud.aspx >Through the use of innovative technologies and network analysis tools, we are able to help detect and stop these crimes
  - Mz 12y ago
    Ok. But I think you are still misinformed --> For example every insurance claim from any insurance company is run through fraud detection software. From digging around, this seems kind of a new trend. I seriously doubt that "every claim at any insurance company" is being analyzed this way. And, sure, it's possible it was in use at the company where I worked and I simply did not know. But from reading some of what you linked to, I doubt it. (Though perhaps that has changed since I left.) From one of the sites you linked to: "Industry research indicates 10 percent of all claims contain an element of fraud," says Wolfe, and as of the end of 2010, CNA was seeing just 3.7 percent of its claims referred as potential fraud. "That’s considerably below the industry average, and we wanted to find out how much we were missing that wasn’t identified by our adjustors." So, yeah, that's relatively recent and the searches I did sort of imply that this is an emerging market, they are still trying to convince insurance companies to do this, etc. Insurance is a very conservative industry. They tend to be somewhat slow to adopt new technologies. They are regulated by both federal laws that cover financial companies and also federal laws that cover medical companies (like HIPAA). So they have a huge regulatory burden and this makes change especially hard. Any new tech or new processes have to really be put through their paces to see if they still pass muster on multiple fronts. The de facto result is that insurance companies are kind of sticks in the mud. Where I worked, a lot of the software was homegrown. It had been developed in-house. They didn't like hiring outside vendors/buying outside solutions. From what I gather, they were fairly cutting edge -- though, of course, it is possible that was just company hype. Since I worked there, I sometimes knew that some statements amounted to spin-doctoring. But I did only have an entry level job and was not really expecting it to turn into a career, so I am sure there is plenty that I missed. Thanks for replying.
superuser2 12y ago
Sometimes the pattern only exists in data writ large. For example, a particular merchant is breached, and then the fraudsters try to run most of the cards stolen in that breach at a few locations. It could be obvious on your bank's end that a few dozen customers made a charge at Store A and then reported a charge at Store B to be fraudulent, so then they decided to freeze the cards of everyone with the same Store A -> Store B pattern.
- aestra 12y ago
  Great point.
NoMoreNicksLeft 12y ago
Quite possibly, they saw the same item purchased 5 times within minutes, all off of other Discover cards. You'd only see the transaction that used your number.
x0x0 12y ago
I've heard that good signals are things like small gas purchases at a gas station you haven't been to before; they're used to test card validity at a pay-station with no human present.
- meowface 12y ago
  This has been such a common signature for fraud over the years that I'd be surprised if many fraudsters are still doing this. If they were smart they'd buy a chocolate bar from a grocery store that has self-checkout, then buy something a little more expensive from Target or whatever, then buy the very expensive thing they really want.
  - Estragon 12y ago
    What's the purpose of the target purchase?
    - tatterdemalion 12y ago
      I think because it masks the "tiny purchase -> giant purchase" signal that is used to detect fraud?
      - Estragon 12y ago
        Ah, thanks.
    - x0x0 12y ago
      a guess: probing the available balance. Presumably, you only get a couple shots at the apple store to buy that laptop because a single person isn't going to be able to try 5 cards with different names on them in a row without the police being called.
keithpeter 12y ago
Do you tend to go shopping for a given product at the same kind of times/days? E.g. for me clothes shopping is on Saturday or Sunday. Do you tend to go to certain physical locations or use a limited number of Web sites to buy from? Just guessing.
- aestra 12y ago
  Nope! My spending habits are kinda random and I travel a lot.

andreyg 12y ago

Disclaimer: I work here. Thanks @wdewind! We do too. We had a field day playing with the data. We actually have thousands of features and these are just some of the most simple signals. We're really careful not to disclose some of our more complex (and powerful) ones - but I can say that we statistically model patterns such as position of digits in email address, page visit sequence, etc.