Faster Payments Don't Have to Mean Faster FraudJohn O'Neill Jr. of DarkTower on How Big Data, Machine Learning Can Curb LossesAs banks in the U.S. and Australia grapple with how to effectively launch faster payments, more will turn to big data and machine learning to help better manage expected upticks in fraud, says John O'Neill Jr., director of financial crime and analytics at DarkTower, formerly Queen Associates.
Forensics Specialist Garner Warner on Why Both Are EssentialAs big-data analytics matures, it will play a bigger role, but security information and event management software, or SIEMs, will also remain essential, contends Garner Warner, director of research in computer forensics at the University of Alabama at Birmingham. Alerts about traffic patterns linked to botnets used to wage massive spam attacks often come in via SIEMs, Warner explains in an interview with Information Security Media Group.
RSA's Daniel Cohen on Steps Banks Need to TakeHow will open banking, also known as baking as a service, affect the financial fraud fight? Daniel Cohen, head of RSA's fraud and risk intelligence product suite, says open banking, which opens up banking platforms to providers outside the financial services arena, will unquestionably increase transaction volume as consumer banking convenience reaches an all-time high.
Muck Rack makes it simple to find people, tweets, or articles that mention any name, keyword, company, hashtag etc. We've compiled this guide to help you make the most of your search.
Selecting a term
Start searching tweets, articles from media outlets, articles mentioned in tweets, journalists'
names, titles and bios with some suggested searches:
Companies or Topics (e.g. iPhone, Microsoft)
Phrases (e.g. "cloud computing") — use quotes to keep the terms together
Twitter handles (e.g. @username) — returns those who have mentioned or replied to
Names (e.g. "David Pogue")
Hashtags (e.g. #sxsw, #london2012)
Bio details (e.g. vegan, Olympics, father)
Muck Rack's Advanced Search allows for many boolean operators.
Find results that mention multiple specified terms, use AND or
+. For example, ensure each result contains both Elon Musk and Mark Zuckerberg by
searching Musk AND Zuckerberg or Musk + Zuckerberg.
Use the operators OR or , to broaden your search when you'd like either of
multiple terms to appear in results. (This is the default behavior of our search when no operators
are used). For example, results will contain either cake or cookie by searching cake OR cookie or cake,cookie
Use NOT or - to subtract results from your search. For
example, searching Disney will yield results about the Walt Disney Company as well as Walt Disney
World Resort. To exclude mentions of Disney World, search for Disney -World or Disney
When using one of these operators with a phrase, enclose it in quotation marks. For example, you can
find results about smartphones excluding Apple's iPhone 4S by searching smartphone -"iPhone
Exact case matching or punctuation
If you're searching for a brand name or keyword that relies on specific punctuation marks or capitalization, you can
find results that match your exact query by adding matchcase: before the keyword you're searching for, like matchcase:E*TRADE .
Use parentheses to separate multiple
boolean phrases. For example, to find journalists talking about having fun in Disney World or
Disneyland, search for ("disney world" OR disneyland) AND fun.
An asterisk can be used to search for any variation of a root word truncated by the asterisk. For example, searching for admin* will return results for administrator, administration, administer, administered, etc.
A near operator is an AND operator where you can control the distance between the words. You can vary the distance the near operation uses by adding a forward slash and number (between 0-99) such as strawberries NEAR/10 "whipped cream", which means the strawberries must exist within 10 words of "whipped cream".