Mar 2020 | Uncategorized | Ai, Analytics, Data

Mike Munsie is Analytics Director EMEA  for Experian, with a background that encompasses banking, finance, business intelligence – and of course data analytics. His experience makes him an expert in how businesses can become data driven.

In his recent keynote for the management event ‘Data & Analytics’, entitled ‘2020 Vision: AI, Data Science and Machine Learning’, Mike  focused on the ways that organisations can (and must) take advantage of today’s flood of data through innovative new technologies, capabilities, and solutions. They must, in other words, become data driven. And with new solutions and services, it is more than possible to accelerate that transformation.

But first, it’s good to understand why AI, Machine Learning, and Advanced Analytics are so significant. Here, Mike shares 3 key takeaways that provide context for why 2020  is THE moment for organisations to become data driven.

1. AI is today’s buzzword.

“To a large degree, the term AI entered the mainstream lexicon in the latter half of the 2010’s and. It’s one of today’s buzzwords, and it’s taken over for the former buzzword ‘Big Data’. The issue is that as far as its application within certain organisations, there has been a real lag between the buzzword arising and the actual implementation of AI. It’s not as ubiquitous as the jargon suggests – AI has a long journey to begin to yield the results that business wants and expects. However, AI is becoming more entrenched within day to day society. Look at mobile phone producers : the vast majority of mobile phones recently released leverage AI embedded in the imaging technology. It’s a much more efficient way to create an image. So AI is becoming more entrenched within processes that consumers don’t see – it is becoming much more mainstream in back office operations. The perception of AI still has a slightly science fiction feel, but It’s far from robots walking the streets like a scene from ‘Terminator’.”

2. About algorithms: The data has been around for a long time. It’s the processing power that is new.

“The thing is that the data has always been there, but there was no processing power. The cloud has enabled people to take huge amounts of data and apply equally huge amounts of processing power. This has made the use of algorithms that have existed a long time – but couldn’t actually be used – implementable in a cost effective manner.

For example if you look at financial services, it’s interesting that many of the algorithms that underpin the industry were formulated by mathematicians in the 1950’s and 1960’s. In the latter part of the 1990s banks started to implement these machine learning techniques but couldn’t do it on scale. An example: they used to download data on the mainframe, put it on a tape, send the tape on the plane to a hub, and then process it in the mainframe to produce credit scores. Now you can load it into the cloud and process it for a fraction of the cost and time.

So it’s nothing new, it’s simply that access to affordable processing power has just about caught up. Now we’re at the point where we’re using neural networks, accessing the affordable processing part to take data, process it and produce an output. This is machine learning. The one thing challenging the financial industry is that the new algorithms don’t explain their own results in a friendly fashion, and regulators have to catch up with the algorithms themselves. So banks are deploying machine learning in places that don’t require stringent regulation.”

3. Data is precious.

“When we talk about 2020 as a turning point for AI and Machine Learning and advanced analytics, there is one overarching reason. The scenario is that, historically, data wasn’t viewed as an asset. Now organisations are switching on to the fact that the data they are producing, whether that is through their consumer interactions or their own internal processes, is viewed as an asset that will provide returns if applied correctly within various processes. As a result we’re beginning to see organisations aspire to getting a better understanding of consumers.

Consumers have become focused on quick efficient services –– and data is an enabler to making that process faster and more seamless, because you understand the consumer in more vivid detail. So you’re not making a vanilla offering – you are making a customised offering. That’s not just applicable to retail or financial services. You name an industry and this seamless customer journey is applicable and important.

Today the focus is quickly shifting towards advanced analytics and decision automation that can turn the vast amount of newly-available data into actionable strategies that can be adopted instantly. At Experian, our data scientists have created an integrated, highly advanced and modular suite of services and solutions to create accurate real-time insights for every sector. We think we’re ahead of the curve here.”

Experian’s Web Data Insights is one of the latest solutions that effectively and quickly improves decisioning processes around SME lending, amongst other strengths. Find out more.