The Data Analytics Blog

Our news and views relating to Data Analytics, Big Data, Machine Learning, and the world of Credit.

10 ways of combating application fraud (part 1)

New technology gives the promise of greater enablement. But some of the shrewdest entrepreneurs understand that opportunity comes from the unintended consequences of new technology. So, let us take digitalisation of the loan application process: the opening of digital channels has enabled lenders to service their customers 24/7 and through APIs integrate with a host of sophisticated services. However, the advent of the digital channel has meant more opportunity for fraud.  The question to ask is:

My learnings on the effective use of automated self-service bots.

Organisations and individuals, need to adapt and change to the new ways of working to ensure that we survive this pandemic, and protect our sustainability for the future.

COVID 19, mitigating this risk for business continuity and social responsibility

In 2011, Microsoft founder, Bill Gates, reflected on the many strides researchers have made in terms of treating diseases such as HIV, malaria and polio. Gates warned us, “There is one area, though, where the world isn’t making much progress, and that’s pandemic preparedness. This should concern us all because if history has taught us anything, it’s that there will be another deadly global pandemic”.

The Five Most Popular Machine Learning And Artificial Intelligence Blogs of 2019

This year, we wrote about machine learning (ML) and artificial intelligence (AI) mostly in the context of chatbots. That’s because we have a brand new relationship with NML as an Atura, AI Chatbot for Financial Services reseller. You can read more about our partnership, here. We’ve also written a very interesting blog regarding machine learning in medicine, which you shouldn’t miss, so we’ve included it in this roundup.

How Machine Learning Is Helping Call Centres Improve Their CX

The call centre world, unsurprisingly, ranks as one of the highest adopters of data analytics platforms year on year. This is largely due to the invaluable insights we gain through the analysis of thousands of calls received each day by the typical call centre. With speed being of the essence in making the right decision at the right time for each caller many call centres are turning to machine learning to automate their data analysis and make crucial customer experience decisions within seconds.

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