AI: preparing for the future
This article examines the development of an artificial intelligence (AI) framework for natural language processing (NLP) and generation (NLG) and offers advice for financial industry professionals.
This article examines the development of an artificial intelligence (AI) framework for natural language processing (NLP) and generation (NLG) and offers advice for financial industry professionals.
Back in October, US research and advisory group Gartner listed artificial intelligence (AI) and advanced machine learning (ML) as one of its ‘top 10’ strategic technology trends for 2017. “AI and machine learning have reached a critical tipping point and will increasingly augment and extend virtually every technology enabled service, thing or application,” the group reported.
“Creating intelligent systems that learn, adapt and potentially act autonomously rather than simply execute predefined instructions is primary battleground for technology vendors through at least 2020.”
AI and ML include everything from deep learning and neural networks to techniques like natural language processing (NLP) and its newer cousin natural language generation (NLG). NLP and NLG use an understanding of human language to process large amounts of data and generate natural language text – in the case of NLP – or to review unstructured data and give meaning to it with linguistic text (in the case of NLG). The opportunity for this technology to automate processes and bring new meaning to data in financial services is significant.
In fact, in a world where 80% of data is unstructured – according to ‘The Text Mining Handbook: Advanced Approaches in Analysing Unstructured Data’, by Ronen Feldman and James Sanger – NLP could be a powerful way to automate tasks, where it is well-known that machines makes fewer mistakes than humans when working on repetitive tasks.
What’s more, according to The Economist magazine, given the advent of digital neural networks (DNNs) over the past five years, DNNs are “helping to improve all manner of language technologies, often bringing enhancements of up to 30%. That has shifted language technology from usable at a pinch to really rather good. But so far no one has quite worked out what will move it on from merely good to reliably great.”
Four points to consider
For financial institutions looking to take advantage of the opportunity, keep the following four points in mind:
Two recent market research reports predict respectively that the AI market can expect a compound annual growth rate (CAGR) of 62.9% over six years to reach US$16bn by 2022 and that investment in AI will top US$5bn within the next three years (against just US$420m in 2014), with NLP an important part of that growth. Financial services firms can use the technology to automate manual processes and augment and elevate the role of the trader, the compliance offer and other important roles across the organisation.