Ten Commandments for Tackling Fraud: The Role of Big Data and Predictive Analytics

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Ten Commandments for Tackling Fraud:The Role of Big Data and Predictive Analytics

Revathi Subramanian

SCX11S #CAWorld

SVP, Data ScienceCA Technologies

2 © 2014 CA. ALL RIGHTS RESERVED.

Abstract

RevathiSubramanian

CA TechnologiesSVP, Data Science

Author of “Bank Fraud: Using Technology to Combat Losses”

Accurate enterprise-wide data combined with data-driven fraud analytics can have a transformational effect on banking and related industries. Revathi will provide tips and insights on using technologies like neural network predictive modeling, user behavior-based pattern recognition and statistical big data analytics to reduce the risk of fraudulent activities in the enterprise.


Current Challenges with Fraud Management

FraudPrevention

Operational Costs

CustomerExperience


It’s a balancing act.

Achieving balance is the only way to increase customer acceptance.Failing to achieve balance results in lost business and unhappy customers.

CUSTOMEREXPERIENCE

FRAUD PREVENTION

OPERATIONAL COSTS✔


1. Data: Garbage In; Garbage Out

“On two occasions I have been asked, ‘pray, Mr. Babbage, if you put

into the machine wrong figures, will the right answers come out?’ …

I am not able rightly to apprehend the kind of confusion of ideas

that could provoke such a question.”

Charles Babagge, ‘Passages from the Life of a Philosopher’


2. No documentation? No change!

“When dealing with data, a rose by a different name is not the same as a rose.”Revathi Subramanian, Bank Fraud: Using Technology to Combat Losses


3. Key employees are not a substitute for good documentation.

“Oh yeah! We made that change sometime in April and unfortunately we don’t have too many more details.”


4. Rules: More doesn’t mean better.

“As it is with children or pets, having too many rules is generally

counterproductive. Too many rules tend to confuse them. Interestingly, fraud

management systems are no different.”

Revathi Subramanian, Bank Fraud: Using Technology to Combat Losses


5. Score: Never rest on your laurels.

“As fraud management systems get sophisticated, fraudsters also get sophisticated … Scoring processes have to keep on improving in order to tackle fraud effectively.”Revathi Subramanian, Bank Fraud: Using Technology to Combat Losses


Non-linear models are a requirement for any complex risk management problem.

Modeling technology used needs to look beyond the “Brownian motion.”

Needs to take into account the entire domain’s fraud patterns

Needs to constantly improve – automated yearly refreshes with regional tweaks

Advanced Analytical Scoring = Huge Value


6. Score + Rules = Winning Strategy

“A sophisticated scoring system combined with a limited set of rules to take into account operational considerations is the winning combination … Having too many rules can water down the fraud management system, but even the best scores are not very useful unless the operational use of the scores is streamlined with some carefully crafted rules … .”Revathi Subramanian, Bank Fraud: Using Technology to Combat Losses


Rules should be used to satisfy its business needs using a highly predictive score.

Rules can also implement business policy.

Business needs change over time and the rules need to change with that.

One size does not fit all; There should be no need to go back to the tailor to get the best fit either.

Scores tell you who might not be legitimate.

Rules are what you decide to do with that knowledge.

Any system that requires you to outsource rules is a problem.

Maximum Precision with Maximum Flexibility


7. Fraud: It is everyone’s problem.

“Every little bit of information we drop on the floor, every transaction that

doesn’t get recorded, every rule that doesn’t get used right, every score that

doesn’t get used optimally, every fraud analyst that doesn’t get trained well

has an impact on the overall fraud management picture.”

Revathi Subramanian, Bank Fraud: Using Technology to Combat Losses


Online fraud problem is huge.

Digital footprint left behind by the customer is a goldmine of

information that can be tracked and utilized with advanced analytics.

Device/browser characteristics can identify issues very quickly and

precisely using advanced analytics.

Possible to track a device in real-time and nab the fraudster before

major damage is done

Digital World: Goldmine of Information


9. Fraud Control Systems: If they rest, they rust.

“Fraud control systems have to evolve and change with the times, and the changes have to happen in an agile fashion.”Revathi Subramanian, Bank Fraud: Using Technology to Combat Losses


10. Continual Improvement: The cycle never ends.

“Every time there is a leap forward in the digital world, there is an equal leap forward in what the fraudsters can do to increase the losses.”Revathi Subramanian, Bank Fraud: Using Technology to Combat Losses


Consider the important factors in a payment transaction:

Each has unique history, distilled down to the critical information and combined with the transaction through a complex non-linear model to produce a score.

Beyond the Simple: Pivots A person, thing or factor having a major or central role, function or effect

Customer Card Device Merchant

CustomerCard

DeviceMerchant

Transaction 789


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For Informational Purposes Only

© 2014 CA. All rights reserved. All trademarks referenced herein belong to their respective companies.

This presentation provided at CA World 2014 is intended for information purposes only and does not form any type of warranty. Some of the specific slides with customer references relate to customer's specific use and experience of CA products and solutions so actual results may vary.

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Ten Commandments for Tackling Fraud: The Role of Big Data and Predictive Analytics

Technology

Transcript of Ten Commandments for Tackling Fraud: The Role of Big Data and Predictive Analytics