SOURCE: Argyle Data

Argyle Data

February 01, 2016 07:00 ET

Mobile Fraud: Are We Winning the Wrong War?

The First in a Series of Commentaries on the Findings of the Communications Fraud Control Association's 2015 Study Examines the Issue of 'Unknown Unknown' Fraud Types

SAN MATEO, CA--(Marketwired - Feb 1, 2016) - Dr. Ian Howells, Chief Marketing Officer of Argyle Data, the leader in native Hadoop applications for revenue threat analytics in mobile communications, has released the first in a series of articles analyzing the results of the 2015 Global Fraud Loss Survey published by the Communications Fraud Control Association (CFCA). In particular, Howells examines how the overall cost of fraud could appear to have decreased even though most of those on the front lines in the fight against fraud believe that losses are actually on the rise.

"In comparison with the CFCA's 2013 report, the overall reported cost of fraud was reported as down from US$46 billion in 2013 to $38 billion in 2015. This is a very surprising result considering that the survey respondents also overwhelmingly felt that fraud was on the increase," Dr Howells commented.

Responses to the survey question asking whether respondents believed that, over the past 12 months, global fraud losses had trended up, trended down, or stayed the same, produced the following results:

  • Trended up - 55.6%
  • No change - 33.3%
  • Trended down - 11.1%

Results for the question, "Over the past 12 months, has fraud in your company trended up, trended down, or stayed the same?" were as follows:

  • Trended up - 50.0%
  • No change - 23.7%
  • Trended down - 26.3%

In summary, 88.9% thought that fraud had either gone up or stayed the same globally and 73.7% thought that fraud had either gone up or stayed the same within their company -- even though the reported total cost of fraud was shown to have reduced by $8 billion over the past two years.

Writing in Fraud and Technology Wire on the topic, Howells said, "I have often quoted Donald Rumsfeld to highlight the current state of fraud detection: 'There are known knowns. These are things we know that we know. There are known unknowns. That is to say, there are things that we know we don't know. But there are also unknown unknowns. There are things we don't know we don't know'."

When you break this down in terms of mobile communications fraud it translates as:

  • The known knowns - Known fraud attack techniques
  • The known unknowns - Fraud that we suspect but can't codify with rules
  • The unknown unknowns - Fraud that we don't know about/are not looking for

"The logical conclusion I came to was that we are getting better at detecting known fraud attack techniques, and that is why the numbers have gone down," said Howells. "The other part of the logical conclusion is that sophisticated criminals are getting much better at the known unknowns and unknown unknowns, which is why fraud specialists feel that fraud is going up when the cost seems to be going down. The visible bucket of fraud is reducing whereas the invisible bucket is increasing."

Howells believes that we are at a turning point in fraud and revenue threat analytics:

  • Known fraud attack techniques (the known knowns) are reducing.
  • Fraud that we suspect but can't codify with rules (the known unknowns) is a growth area.
  • Fraud that we don't know about/are not looking for (the unknown unknowns) is a growth area.

"Sophisticated criminals are focusing on the growth areas as they have a cloak of invisibility," said Howells. "The question I have is this: Are we winning the wrong battle on fraud? The world is moving to the use of big data and machine learning -- and that also includes organized crime rings and governments using sophisticated attack patterns."

The next phase in the battle against fraud will be for mobile operators to fight back in an equally sophisticated way:

  • Use existing rules and rules-based systems to identify known fraud attack techniques (the known knowns).
  • Use machine learning to identify fraud that we suspect but can't codify with rules (the known unknowns).
  • Use machine learning to identify fraud that we don't know about/are not looking for (the unknown unknowns).

In summary, the new mantra for defending subscribers and networks will be to use machine learning against vast data lakes to discover the known unknowns and unknown unknowns. Only then will mobile operators see a true reduction in the real cost of fraud.

Argyle Data will exhibit at the Cloudera booth at Mobile World Congress (Stand 6M30, Hall 6).  Visitors to the booth will receive a free copy of Argyle Data's book, Fighting Future Fraud: A Strategy for Using Big Data, Machine Learning, and Data Lakes to Fight Mobile Fraud. 

About Argyle Data
Argyle Data is used by the world's leading mobile operators to detect the fraud, profit, and SLA threats that cost the industry $38 billion dollars per year. Argyle Data's industry-leading native Hadoop application suite uses the latest Hadoop and machine learning technologies, proven at Facebook and Google, to identify the revenue threats and attack patterns being waged against mobile networks in real time. To learn more please visit:
Argyle Data Website
Fraud & Technology Wire
LinkedIn
Twitter

Contact Information

  • Contact:
    Mary McEvoy Carroll for Argyle Data
    Email: Email Contact
    Tel: + 1-408 691 4283