For some time now one buzzword that gets dragged around meeting rooms of banks, financial institutions, insurance, regulators and startups is artificial intelligence (AI). The challenge that many in the financial services sector face, however, is the growing list of terms that are being liberally swapped with AI.
For instance Gartner includes terms like natural language processing, prescriptive analytics, deep learning, machine learning, cognitive computing, augmented reality, virtual reality, ensemble learning, deep neural networks, neuromorphic technology, and the list goes on – into the AI taxonomy. But the reality is that the confusion stemming from AI is as much the diversity of views around the technology as it is the different interests among players in the market. A few things are certain: the AI that inspired characters like Data from Star Trek or Bishop in Alien will require massive technology resources, and possibly new computing paradigm such as the developments around quantum computing.
Why banks are drawn to AI
According to the Accenture Banking Technology Vision 2017 78% of surveyed bankers believe that AI will enable simpler user interfaces that will help banks create a more human-like customer experience. Seventy-nine percent predict that AI will revolutionize the way banks gather information and interact with customers. While 76% believe that within three years, banks will deploy AI as their primary method for interacting with customers.
Trends driving AI adoption
Genady Chybranov, director for Financial Technology Innovation at Hitachi Data Systems (HDS) lists Big Data, cloud and the diametrically opposite states of increasing computing power while declining costs as key trends impacting the development of AI. “Big Data technology is creating massive amounts of data available to build models. The AI model is only as smart as the data it based on. Declining hardware cost is making AI projects more affordable while cloud is not only bringing more power to AI development but also lower barriers of entry,” he explained. At the same time he acknowledges different approaches to AI development. “From what I can see there are no general approaches to investing in AI among FI’s. Some are investing heavily in building in-house capabilities, others investing in AI companies or experimenting with 3rd party solutions,” opined Chybranov. […]