With direct marketing, you likely have a benchmark success rate from previous similar campaigns that you base your goals on, and you try to optimise it through various strategies, whether by trying to offer the best deals or by using behavioural tactics.
In a previous blog, we looked at assessing your credit models and the challenge of building and deploying models representative of the COVID-19 crisis. At the crux of the challenge was the fact that:
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:
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.
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”.
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.
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.
At Principa, we are passionate about new ideas and product development. 20% of our revenue is ploughed back into innovation. One of our key areas of focus is machine learning where we have built machine learning solutions in both collections and the customer acquisition space. While our focus is primarily on credit risk and customer engagement, we are always interested in how machine learning has gained traction in other industries.
The benefits have been recounted many times, but now that Machine Learning has the business world’s attention, how does one get started? Moving into the machine learning space can be somewhat daunting, but we hope this blog post provides some guidance that you will find helpful.
We’ve recently partnered with Atura to bring a world-class chatbot to the credit and collections industry – and we’re very excited!
Your business is likely already considering a chatbot, and if not: you’ve likely got it on your agenda for this year. We’ve written recently about some powerful statistics on chatbots that you need to know, but in this article, we’ll detail some of the benefits of chatbots and why they are so important for your business in 2019. (more…)
"*" indicates required fields
