SAN MATEO, CA--(Marketwired - Feb 17, 2016) - Professional services firm Kropmann Communications Limited has signed a reseller agreement to provide Argyle Data's native Hadoop fraud analytics technology as part of its services to mobile communications operators in Africa.
Kropmann Communications Limited is in the forefront of delivering new technologies to help address business challenges in Africa. Since its inception in 2005, Kropmann has entered into strategic partnerships and alliances to deliver actionable intelligence platforms for banks and telecommunications companies in areas including customer engagement optimization, compliance, business intelligence, security, fraud and risk.
Each year Africa's mobile/cellular carriers lose the equivalent of almost US$1.75 billion through theft of service, interconnect and related frauds. Fraud prevention and revenue assurance has become a major priority for all operators. 2015 research indicates a general consensus among regional telecoms carriers that between 1 to 3% of revenues are unbilled and that between 2 to 6% of billed revenues are unpaid1.
"The downside of the growth in mobile services in African countries is that it has attracted the attention of global criminals which, combined with the high cost of delivering service in this region, highlights the importance of operators actively engaging in identifying and reducing revenue leakage," said Kim Fraser, CEO of Kropmann Communications Limited. "While the region's telecommunications industry has seen a quantum leap in the past decade, revenue fraud and the high cost of service delivery is a challenge for which the telecoms industry in Africa urgently needs new solutions. Argyle Data's fraud detection technology allows operators to fight known and unknown fraud types in real time, and we are very pleased to add their application to our portfolio."
Argyle Data's system is used by some of the world's largest mobile operators to gain real-time visibility into revenue threats and attack patterns, which cost the mobile communications industry an estimated U.S.$38 billion a year. Argyle Data's is the first in a new generation of native Hadoop applications that exploit the power of machine learning to uncover critical insights in real-time from vast data lakes.
"Research from the CFCA2 shows major growth in both International Revenue Share Fraud and Premium Rate service fraud, which in Africa is over 28% of the total," said Vikash Varma, President and CEO at Argyle Data. "Subscription and dealer fraud constitute a further 29% of the total revenue loss to fraud in Africa. Argyle Data's breakthrough approach has already been proven to dramatically improve fraud detection and prevention. We are very pleased to work with Kropmann to provide operators with a way of reducing revenue losses to fraud in the region."
About Kropmann Communications Limited
Kropmann Communications Limited is incorporated and headquartered in Nigeria. The company became fully operational in 2009, with a vision to be the foremost indigenous professional services and VAS content provider in Nigeria. Managed by experienced executives, Kropman is in the forefront of delivering new technologies to help address business IT challenges in Africa. Kropmann Communications Limited is also a licensed Internet Service Provider and a VAS content Provider to both organizations and individuals.
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 per year. Argyle Data's industry leading native Hadoop application suite uses the latest Hadoop and Big Data machine learning technologies, proven at Facebook and Google, to identify the revenue threats and attack patterns being waged against mobile networks in real time.
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1 Falcon Research, September 2015 http://www.telcoprofessionals.com/event/1538
2 http://www.cfca.org/pdf/survey/2015_CFCA_Global_Fraud_Loss_Survey_Press_Release.pdf
Contact Information:
Contact:
Mary McEvoy Carroll
for Argyle Data
Email:
Tel: + 1-408 691 4283
