The advantage of monitoring long tail international sources for operational risk

News publishers come in all shapes and sizes. There are household names across the world, such as The Wall Street Journal, Financial Times, and Bloomberg. There are national publishers that dominate their country of origin, like Le Monde, El País, and The Irish Times. There are newspapers for sprawling cities such as The LA Times, The London Evening Standard, or Mumbai Mirror. There are local papers, such as The Meath Chronicle, Santa Cruz Sentinel, or Mindanao Examiner. And there are specialist blogs and publications keeping on top of news from any subject you can think of, be it cyber security and supply chain risk, to model boats and gamelan music. Each of these tiers serves a purpose.  

The result is a truly huge amount of available information, which contains extremely valuable risk and opportunity signals for organizations of all types – financial institutions, governments, manufacturers, tech companies etc. However, the reality is that a lot of organizations are only monitoring larger news publishers and have no way of unearthing critical early signals from long tail sources that are closer to the breaking event or have expert insights into niche topics that eventually are picked up by mainstream news channels, and which have the potential to impact global business. The unfortunate truth is that if your organization is not monitoring the long tail, it will often be too late by the time they hear about an event. 

Traditional methods of media monitoring, including media monitoring solutions from the last couple of decades, are not capable of efficiently, effectively, and accurately monitoring the scale of global news, in multiple languages, in near-real time. Even if these capabilities are available to analysts, the really difficult part is still to be done: finding relevant signals amongst the overwhelming noise quickly enough that it gives a competitive edge, or gives enough time to take preventative action against the risk.  

Quantexa News Intelligence (QNI) solves this problem by applying industry-beating AI to the world’s news. We aggregate around 1.3 million news articles per day from over 90,000 publishers from around the world, from the biggest household names, to the smallest local digests, as well as niche blogs. Our natural language processing (NLP) engine does not discriminate by a publication’s reputation – it reads every single article, and transforms each one into structured news data, which makes searching and filtering the world’s news more accurate and efficient than ever before. To put this capability into context, QNI reads and tags 14 articles per second, every second, every day. It would take a human 6 years of constant reading to read what QNI can do in 1 day. And that human would have to be fluent in 16 languages! 

Let’s look at a random example we found using QNI’s Search UI, which lets you build and investigate queries in seconds. These queries can then be exported as a query for our News API. In this example, a quick supply chain related search returned results from large news sites/wires such as MSN and Morningstar about a shortage in aluminum, which has led to production delays for Jaguar Land Rover, and a profits warning  for Porsche.  

However, a canny supply chain risk analyst should be monitoring long tail news and specialist blogs for risk signals of critical materials. In this case they would have been alerted to a niche article from 2 months before the Jaguar Land Rover/Porsche articles titled ‘The aluminum shortage nobody seems to be noticing’.   

The above example is just one of countless others that could have potentially given an organization an advantage against adversity. Stories always have to start somewhere, and a lot of the time that can be in long tail news. When critical decisions need to be made fast, any delay can be costly and impactful. Try Quantexa News Intelligence for your own organization, and start monitoring long tail news today by signing up for a free 14 day trial.