Over the past few years, we’ve heard a lot about the fourth industrial revolution, or 4IR as it’s become known. It’s being touted as the answer to everything from backlogs in education and skills development to companies cutting costs and serving their customers better. The problem is, few people know what 4IR really means, and what the real opportunities are that it presents.
One of the hallmarks of the 4IR is that it uses technologies such as artificial intelligence (AI), machine learning and data analytics to sift through the mountains of data that we’re bombarded with every day to pick out the nuggets, and even make basic decisions on our behalf, based on algorithms.
But while many organisations talk about digital transformation, hire consultants, sit through endless PowerPoint presentations, and then talk some more, a lot of companies still don’t really know how to go about implementing it.
A new Aite Group study commissioned by TransUnion and released this week, showed that companies across the world are amassing vast volumes of data with the intent of “optimising performance”, “identifying trends” and “meeting rising consumer expectations”. Yet nearly 75% of financial services and insurance executives admitted they “are challenged by the fractured nature and vast amounts of data available”.
Here’s the kicker, though: that’s not going to stop them continuing to secure more data sources. In fact, they’re looking to incorporate more AI and machine learning technology into their analytic platforms to help them make sense of the information. In other words, they don’t know what to do with all the data, so they’ll buy some more technology to try and make sense of it.
If you really want to unlock the benefits of 4IR, start by knowing upfront exactly what questions you want your data to answer. This is not a fishing trip. It’s no use spending a lot of time and money on embarking on an open-ended exercise, where you collect as much data as possible and then see what turns up. Simply asking what patterns the data points show is not going to be of much use.
A major opportunity lies in the way in which we use data to solve problems in a responsible manner. That means asking the big business questions: how can you improve profits and increase revenues? How can we remove friction from digital processes, and smooth our risk-making approach?
Once you have these questions, then 4IR technologies can certainly help. AI and machine learning can shorten the traditional analytic lifecycle from months to just weeks or even days.
For South Africa and Africa, there’s another huge opportunity in 4IR: how to use data to drive financial inclusion. Numerous studies by institutions including the World Bank and the International Finance Corporation have shown the benefits of financial inclusion: not just to people and communities, but to entire economies. When you have growth in consumer spending, it becomes a horse that pulls the economic cart, as it were.
Where data comes in is in helping financial institutions find people who were previously “credit invisible”, and making them credit-worthy — thereby allowing them to access formal economic systems and build credit profiles. The Aite Group study showed that financial institutions are placing an increasing importance on the value of expanding data sources to include non-traditional, third party and alternative data. Over the next 24 months, 89% of institutions have plans to use alternative data such as mobile data, purchasing patterns, and even social media data.
Integrating data from across a consumer’s credit journey provides a rich canvas for drawing insights: the challenge is to manage and extract the right information. If South African financial institutions can get that right, we’ll see 4IR starting to make the difference it has always promised to.
Stephen de Blanche is chief revenue officer at TransUnion Africa