Author:amit sonawane

A friendly customer may be committing fraud and not know it.

Friendly Fire: Dealing with Deliberate Chargebacks from Consumers

Card-not-present fraud is an issue every single e-commerce sees, often in the form of the chargeback.

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The future of payments and what it means for fraud

The payments landscape is going through some exciting times. 

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As card issuers embrace IoT, how will it affect payments?

The Internet of Things presents new vectors for payments – and fraud

    In early March 2016, the Mobile World Congress met in Barcelona.

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    How will the Bitcoin split affect payments and fraud?

    In the early months of 2016, one issue dominated all discussion in cryptocurrency: Bitcoin could split in two.

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    The importance of digital security patches for ecommerce

    Securing an online store is an ongoing challenge and an important one.

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    IoT introduces a host of security issues for businesses.

    Security still a huge barrier for IoT adoption

    The Internet of Things has great implications for businesses and consumers alike, but the issue of security is still holding the industry back.

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    Democratizing Data Can Help Fraud Prevention Evolve

    Fraud prevention’s most capable asset at present is analytics. By detecting patterns through data science, there’s a great chance that banks can find anomalies consistent with fraudulent transactions. However, the problem with data science is its complexity. Namely, the proportion of information that requires analysis

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    Improving the Infrastructure of IoT for Fraud Frevention

      The Internet of Things can be a great tool for preventing fraud at various points of payment, as well as within e-commerce. However, if not properly invested and secured, it can also be a great liability. Often, the best way to mitigate the risk of

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      5 Fraud Prevention Trends for 2016

      The end of the year is always a key time for businesses, with security ranking high on the list. With 2015 drawing to a close, it’s already time to begin thinking about fraud prevention in the new year. What will the fraud landscape look like

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      Machine Learning and Cyber-Security: What are the Stakes?

        In cybersecurity, as in fraud prevention and detection, there is a constant movement between two forces: IT staff and cybercriminals. The latter always looks to outwit the former, whether to steal information from a database or take over a site, while the former keeps building

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