Payments

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Mike Urban
Mike Urban
Commentary
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The Role of Big Data in Monitoring Real-Time Payments Fraud

Predictive and behavioral analytics hold the key to tracking fraud in a real-time payments environment.

The US Federal Reserve announced in early 2014 plans to update the financial services infrastructure to accommodate faster payments, even a path to real-time funds transfer. This is a noble goal, but real-time payments could come with substantial risk. While real-time payments will likely be popular with consumers, financial institutions must be prepared to manage the significant financial crime risks associated with payments in real-time. Enter big data. Big-data analytic tools will play a critical role as real-time payments proliferate and will help institutions adapt their existing crime-fighting strategies to meet the rapidly evolving techniques of fraudsters.

Financial crime has become an arms race between banks, risk managers, and criminals. Real-time analytics to detect crime have now become essential as fraudsters are using rapidly evolving attack scenarios, exploiting multi-channel vulnerabilities, and compromising payments systems on an expanded scale. The explosion of access channels in payments -- through online, mobile, apps, and soon-to-be real-time -- and increasing transaction volumes have escalated the rate of false positives from standard fraud detection rules.

[For more of our security coverage, check out: 3 Keys to Making Payments More Secure.]

Strategies to combat financial crime today are, in many ways, similar to the strategies first employed by financial institutions when digital payments burst on the scene many years ago. Predictive analytics has long been a powerful weapon in the fight against criminals, and variations of other financial crime fighting techniques -- behavior monitoring, network analysis, pattern recognition, and profiling -- have been key components of banks’ toolkits for decades. But today, big data is changing the game.

While banks have been employing these strategies for decades, big data has enabled banks to deploy real-time analytics on a massive scale to meet these growing threats. Financial fraudsters are becoming increasingly sophisticated and daring, raising the potential for serious disruption to the entire financial system. Financial institutions must have effective, real-time crime detection analytics in place.

To meet the financial crime risks that could accompany real-time payments, institutions must implement a financial crime risk management philosophy that relies on a multi-faceted analytic approach to detecting and mitigating financial crime. A blend of analytic behavioral profiling, real-time detection scenarios, and predictive analytics provides the most accurate results. Big data enables financial institutions to provide these services on a scale the industry could only have imagined five years ago.

Today’s financial criminals are well funded and creative. New attack patterns, previously unknown, are emerging daily. As new forms of payments emerge, so, too, do emerging forms of financial crime, and real-time payments should not be the exception to this rule. The best defense is a combination of behavioral profiling, known scenario event detection, and real-time anomaly detection to identify, classify, and rapidly deploy new defenses against emerging attacks.

Mike Urban is Director of Financial Crime Risk Management Solutions at Brookfield, Wisc.-based Fiserv. He has more than 18 years of experience in financial crime management. He analyzes financial crime issues and trends to provide continuous ... View Full Bio

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Byurcan
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Byurcan,
User Rank: Author
9/15/2014 | 9:26:56 AM
Re: Behavioral and Predictive Analytics
Very true Mike, it will be inetresting tos ee how this space evolves.
MikeUrban
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MikeUrban,
User Rank: Apprentice
9/11/2014 | 6:58:33 PM
Re: Behavioral and Predictive Analytics
Fire is a great example!  Everyone is talking about Apple and how it is impacting PayPal - Amazon can take the picture of the product, find it in their system, pay and ship it ...  The e-wallets still use the payment card rails for the most part.
Byurcan
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Byurcan,
User Rank: Author
9/8/2014 | 10:38:11 PM
Re: Behavioral and Predictive Analytics
Yes, many people say that Apple getting into the game will really push mobile payments to the next level. But speaking of companies leveraging their existing customer for mobile payments, I think the fire phone has just as much potential, since Amazon has hundreds of millions of customers who alreay are comfortable making payments in that ecosystem.
MikeUrban
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MikeUrban,
User Rank: Apprentice
9/8/2014 | 7:20:52 PM
Re: Behavioral and Predictive Analytics
Costs of data management, aggregation, people to analyze the data and create analytics ...   It is an investment; Moore's law does help us a bit here, as well as open source software like R.  The question becomes what is the cost of not doing it?  Eventually it will become a part of doing business – just like the internet in the mid 90's ...   Big data is an investment area and we are only scratching the surface of its value today.  It will transform our future in ways we don't understand today.  Exciting stuff! 
MikeUrban
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MikeUrban,
User Rank: Apprentice
9/8/2014 | 7:11:45 PM
Re: Behavioral and Predictive Analytics
You and a lot of other people... Cash won't disappear in our lifetimes. There are lots of good use cases for it. What will truly make mobile or any other form of payment is the convenience. We are creatures of convenience and that is what drives our actions. Make it convenient and people will follow.
MikeUrban
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MikeUrban,
User Rank: Apprentice
9/8/2014 | 7:07:42 PM
Re: Behavioral and Predictive Analytics
Hi Becca,

Agree there is a lot of excitement about mobile these days.  Lots of people are already using their mobile devices for shopping today – so convenient.  Will be interesting to see what Apple announces this week and how they impact the market economics by leveraging all of those iTunes accounts ...

 
Kelly22
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Kelly22,
User Rank: Author
9/3/2014 | 1:28:47 PM
Re: Behavioral and Predictive Analytics
You may be right, that could be just the thing that kick-starts mobile payment adoption among consumers. I'd be a bit nervous to be in the first group that tries it, but if it proves to be secure I'd consider giving it a try.
Byurcan
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Byurcan,
User Rank: Author
9/3/2014 | 9:02:54 AM
Re: Behavioral and Predictive Analytics
I'll be sticking with the most secure channel of all, cold hard cash. No fancy mobile payments for me.
Becca L
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Becca L,
User Rank: Author
8/31/2014 | 8:08:49 PM
Re: Behavioral and Predictive Analytics
As more more big data techmniques and tools are used to ID users to prevent fraud, does the cost of security not rise dramatically? As you say, Jon, the landscape is changing so fast it must be a nightmare to plan and budget security initiatives.
Becca L
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Becca L,
User Rank: Author
8/31/2014 | 8:03:56 PM
Re: Behavioral and Predictive Analytics
Apple just partnered with Visa, mastercard, and american express to turn the next iphone (can't wait!) into a mobile wallet with near-field communication -  maybe this will be the tipping point for popularizing new mobile payments, and IT is running out of time to secure these channels.

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