More on fraud detection from IBM - the MoneyGram case

I have recently written about real-time fraud detection solution from IBM based on SPSS and CICS. 

Another solution from IBM in the fraud detection space has been recently highlighted by David Luckham in his site citing a Forbes article.   This solution is based on the "Entity Analytics" solutions (specifically the Infosphere Identity Insights product.    David Luckham comments "that are a lot of CEP under the hood of  this stuff".  This is true.    After the acquisition of SRD by IBM, our team in IBM Haifa Research Lab helped integrating our work on Amit as embedded part in the Entity Analytics -  (see the DEBS 2010 presentation by Ella Rabinovich on Industry Experience with Amit - slide 3).   This integration seems to have survived all these years and being employed for useful purposes. 

In any event,  there are many solutions in which event processing is integrated with other technology to create specific solution, and we can see alliances between event processing technology and other technology in this area.

On malicious event sources: the Twitter Hoax case

In case anyone missed it -- the Twitter Hoax occurred last week.  The story is that a Twitter message occurs at 1:08 pm, that was sent on behalf of Associated Press, notifying on two explosions in the white house, and the injury of the USA president Obama.  Since there are automatic trading programs who get their decisions based (among other sources) on social media, and AP is considered a reliable source, the figure above (taken from Wall Street Journal) shows what happened to the Dow Jones.  The Tweet, of course, was not sent by AP, it was hacked.   Within 2 minutes denials started to arrive, and around 1:13 the Dow Jones got back to where it was 5 minutes earlier.   Regulators are now checking what they can do about such incidents, as reported today by the NY Times.    While writing three years ago about the benefits of Twitter as event source, I noted the danger of abuse.  

Actually when relying on events, the danger of abuse and hacking exist anywhere, one can abuse medical events and sabotage health systems, one can abuse traffic events and make the roads messy, and I guess that there are many other creative way to abuse life.  Yet, I don't think that going backwards and ignore incoming information is practical.    In fact we made malicious sources as one of the motivation of dealing with uncertainty in event processing, but this area is still young.    This struggle will continue to evolve as one of the challenges of big data.   

Real-time fraud detection from IBM

IBM has recently published a Redbook on its solution in Real-time fraud detection. 

Fraud detection is a very important application, since every computerized system attracts people who attempt to hit the system.  While much of today's effort is dedicated to fraud in financial transaction systems, I guess that future efforts will be dedicated to those who are trying to sabotage your computerized car, or even bionic cells in your body.   The interesting fact about this IBM solution that two of the IBM products that participate in the solution are CICS and SPSS.   I worked a lot in SPSS during my first couple of years as a programmer in the Israeli air-force and this was in 1976.  At the same time CICS was used as the transaction processing system of the operational part of the air-force.   .   The SPSS modeler has a data-flow view from the family of event processing networks.  Interesting to see how old guys learn new tricks and handle very different applications relative to their original ones.