Artificial intelligence was one of the buzzwords that defined tech in 2016 and continues to be an overriding theme in 2017, particularly with technologies from Amazon, Apple, Facebook, Google and many others entering the mainstream. The truth is that AI has been around for a long time and we use it every day without even knowing about it. Great progress has been made recently with deep-learning networks and the ability to work with massive pools of data. In business, using next-generation AI to gain insights offers massive advantages. AlphaCode member Emerge Analytics plays at the forefront of intelligence-driven data analytics, offering businesses solutions to complex business problems using the power of this cutting-edge technology.
“It was formed less because there was a gap in the market - although Emerge Analytics does cater to the massive gap of bespoke, machine-learning predictive models - than because properly-deployed machine-learning models will completely transform dozens of industries through accurate prediction and mass personalisation,” says Rau.
“Although there are countless applications, Emerge Analytics, for now, is focussing its efforts in banking, insurance, medical research and retailing.”
Many new companies have entered the market to leverage the hype surrounding artificial intelligence, making it challenging for those with a more holistic approach to data analytics to craft messaging and stand out in the crowd. As with so many new technologies, customers have also burned their fingers with early attempts, making them skittish to try again.
According to Rau and Saksenberg, this has been a challenge for Emerge Analytics.
“People have engaged with machine learning, for one reason or another, but were not able to get value out of the exercise and then lost interest,” says Saksenberg,
“I think the key things to look for from a machine-learning practitioner in order to make sure one really benefits, are a proven track record in machine learning, good business acumen to make sure that the right problems are being solved, and a clear plan on how to operationalise the machine-learning applications.”
When done properly, there are so many opportunities for the technology to make an impact, especially in Africa with its unique challenges.
Rau says it is difficult to pick just one such opportunity, and that having machines profoundly individualise companies’ interactions with their clients in a range of industries will yield results that we are only starting to wrap our heads around. “If forced to choose the areas with the biggest financial (and hopefully social) impact, I would guess that banking, insurance and medical research are the biggest green-field areas, which is why Emerge Analytics places such emphasis on these areas of practice,” he explains.
As is usually the case, setting up a new company meant dealing with many unforeseen challenges, and Emerge Analytics was no exception.
“In a weird way, the hype about ‘Big Data’, ‘data science’ and ‘predictive analytics’ made it very difficult to sell machine learning – although there was tremendous interest in the broad field of data, there was for many years an absence of understanding of the distinction between machine learning and the rest of big data and predictive analytics,” says Saksenberg.
“Many decision makers were (and some are still) convinced that they had completely engaged with the topic even though all that they were using in their organisations was business intelligence and traditional statistical and actuarial modelling. Although these are all valuable techniques, they really did not address a range of problems for which machine learning is far better-suited.”
The company has gone from strength to strength and has been selected as part of the 10-member 2017 cohort of the Startup Bootcamp InsurTech program in the UK, a competition organised by the leading insurers in Europe to scout for the technology that will make the biggest impact on the way insurers do business in the future.
This recognition goes a long way to establishing Emerge Analytics as a market leader.
For Rau and Saksenberg, fintech is a thriving industry with many promising opportunities - but they caution that knowledge of the market one is getting into it key before taking the plunge.
“A lot needs to go right in order to get one’s fintech business off the ground – from the product offering and what makes it special to the most mundane of admin and procurement. I would strongly suggest finding someone who knows the challenges facing a fintech startup so that he or she can provide guidance on how best to navigate the issues most effectively and quickly,” says Rau.