Here are this week’s top stories in fraud and big data technology:
Looking beyond Fingerprint Sensors: Ways to Enhance Smartphone Security
The Motorola Atrix 4G was the first smartphone with a fingerprint scanner for quicker, more secure login authentication. But the security feature’s widespread use came about when Apple introduced it in its iPhone 5s back in 2013. Since then, Snapdragon-powered Android phones have made it a stock feature in premium models, trickling down to midrange and even budget devices for a new level of smartphone security. That new feature alone has the important function of keeping our ever-increasingly important devices safe from breaches. [Phillip Tracy, RCR Wireless]
Why Integration and Governance Are Critical for Data Lake Success
This is the final article in a three-part series exploring what it takes to build a data lake capable of meeting all the requirements of a truly enterprise-scale data management platform. While earlier installments focused on enterprise-scale data management in Hadoop, data onboarding into the data lake, and security, this article will focus on two things: Integrating the data lake within the broader enterprise IT landscape, and data governance. [Paul Barth, Datanami]
Why Artificial Intelligence Will Finally Unlock IoT
According to Gartner, there will be more than 20 billion connected devices worldwide by 2020. Today’s enterprises are already benefitting greatly from a strong, connected workforce, but as Internet of Things (IoT) enabled devices move forward, saturating the market, is it possible for them to outpace their own benefits? [Dean Tang, ReadWrite]
Turning AI into Opportunity: Why Machine Learning Innovations Matter
Globally, industries are scrambling to turn big data into actionable insight that humans can easily interpret. By far the most promising answer to this problem is the use of machine learning, or artificial intelligence (AI). Analysts are expecting the uses of AI in medical diagnosis, finance, telecommunications and many other contexts to soar. A recent article in nature.com puts estimates of the economic value of AI applications in the billion-dollar range, while IBM’s chief executive Ginni Rometty points to a US$2-trillion opportunity in AI systems over the coming decade. [Mary McEvoy Carroll, Argyle Data Insights]
Use Open Platforms or Die, Adtran Tells Telcos
Telcos that fail to take advantage of new open source platforms might not be around in the next ten years, according to a senior executive from broadband equipment vendor Adtran. Speaking at today’s Broadband World Forum in London, Ronan Kelly, Adtran Inc.’s chief technology officer for the EMEA and APAC regions, warned service providers they risk suffering a similar fate to the handset businesses of BlackBerry and Nokia Corp. unless they adapt to new market realities. [Iain Morris, LightReading]
Verizon User’s Mysterious $20,300 Data Bill Canceled after Media Coverage
Verizon Wireless has agreed to forgive a $20,300 bill sent to a nonprofit that was accused of using 1.3TB of data from one phone in just 10 days. Horizon Education Centers of Cleveland, Ohio fought Verizon for three months over the June 2016 bill before finally complaining to The Plain Dealer of Cleveland and the Federal Communications Commission. The newspaper has been publishing a series of stories about surprising data overage bills that cast doubt on the accuracy of Verizon’s data usage meter. [Jon Brodkin, Ars Technica]
Driving Value with Data Science
Fighting fraud, reducing customer churn, improving the bottom line – these are just a few of the promises of data science. Today, we have more data to work with than ever before, thanks to new data-generating technologies like smart meters, vehicle telemetry, RFID, and intelligent sensors. But with all that data, are we driving equivalent value? Many data scientists say they spend most of their time as “data janitors” combining data from many sources, dealing with complex formats, and cleaning up dirty data. [Kavitha Mariappan, Dataconomy]
Content Is New Battleground for India’s Telcos
The battles between India’s telcos have typically been fought over pricing, but the next fight could be about content. As 4G networks come online, India’s operators are trying to differentiate themselves and prevent churn by investing in their content portfolios. While 4G has usually been associated with higher-speed connectivity, telcos are also finding they must offer new and innovative services to engage with their customers. The recent market entry of 4G upstart Reliance Jio has acted as a further catalyst in this area. [Gagandeep Kaur, LightReading]
#FraudFriday: International Revenue Share Fraud
International revenue share fraud (IRSF) is a major type of fraud where scammers set up an international revenue share line and direct calls in various ways toward the number to get a portion of the revenue from the call. IRSF can be committed domestically or, more commonly, while roaming. Certain countries have particularly high interconnection fees and are a focus for IRSF. [Staff, Argyle Data Insights]
The post This Week in Fraud & Big Data Technology – October 21, 2016 appeared first on Argyle Data - Revenue Threat Analytics for Mobile Providers.