Our news and views relating to Data Analytics, Big Data, Machine Learning, and the world of Credit.
The power of Customer Experience and growing competition are driving companies to take a more scientific approach to building customer loyalty.
As developed countries experience a slow but steady recovery, credit risk managers in emerging markets face growing default rates as household debt continues to rise with little relief in sight. The Institute of International Finance stated at the end of 2015 that global household debt had risen by $7.7 trillion since 2007 to more than $44 trillion, and that $6.2 trillion of that rise was in emerging markets. Household debt per adult in emerging economies also rose by 120 percent over that period to some $3000, it added.
Artificial intelligence (AI) and machine learning technology present an interesting meeting point between our fear of the unknown and our fear of being known (that is, fear of our private information being exposed and known by others). The erosion of privacy and rise of intelligent machines is actually a common theme in science fiction. But while reality still has a lot of catching up to do before we can call Skynet’s customer support or play cards with Agent Smith, many people have expressed genuine concern over the implications of modern technology – especially regarding their privacy.
Thanks to its broad applicability, data analytics has rapidly become a critical business function for modern organisations. But with expertise in the field in short supply and high demand, companies with an identified need for data analytics are looking beyond their traditional borders to monetise their information assets. Forrester Research predicts that a third of businesses will “pursue data science through outsourcing and technology” as organisations become less process-driven and look to their data to find new opportunities for innovation. And with globalisation and technological advancements making outsourcing a realistic and practical option for businesses, this trend is set to gain momentum. With this in mind, let's take a look at why an organisation would even consider outsourcing their analytics capabilities in the first place.
Machine learning is helping brands narrow the divide between their products and consumers in ways that would appear almost magical only ten years ago. From Amazon's personal product recommendations based on past purchases and browsing habits, to Netflix's uncanny ability to suggest just the right movie title according to your taste in film, data-driven insights are helping companies speak to individual customer preferences, who are demanding more personalisation in their products and engagements. This has moved data analytics from novelty status to an integral part of the marketing strategy, as brands discover new opportunities to communicate their unique selling points.