Fintech platform revenues for unsecured consumer loans issued using machine learning technology are set to see a jump of 960% during the period 2016-2021, rising to $17 billion globally in the later forecast year.
This is according to a recent study by Juniper Research, which says the rise is driven by advances in analytics and accessible computing power.
The new study, "Artificial Intelligence (AI) & Machine Learning: Fintech Dynamics, Disruption & Future Opportunities 2016-2021", found machine learning spend in fintech will advance rapidly, owing to the highly data-driven nature of the market, meaning AI integration is likely to spell substantial benefits.
Machine learning - a subset of AI - has seen a tremendous leap in activity since 2011, with substantial increases in venture capital and R&D investment, says Juniper Research.
For example, US-based fintech start-ups, Kabbage and ZestFinance, have collectively raised $500 million in funding alone. Meanwhile, vendors analysed in Juniper's research have spent a total of $83 billion in R&D during 2015. Each of these vendors name AI as a part of core strategy.
The research firm says until recently, machine learning was too expensive and computationally time-intensive to break into the mainstream, with access to extensive datasets for algorithm training being limited.
Juniper says presently the ability to use graphics processing unit hardware for processing massive and highly available datasets, along with unlimited affordable computing power in the form of distributed architecture, has opened the market to a swathe of disruptive new players.
It notes AI is particularly useful for risk-assessment purposes, where variables from numerous financial and non-financial data points are assessed by algorithms to approve loans. This widens the addressable market for financial institutions considerably over traditional FICO credit scoring, where lack of credit history may mean loan rejection despite a real low risk for the lender.
"Where big data analytics offered retrospective business intelligence, machine learning offers predictive and even prescriptive capabilities," says research author Steffen Sorrell. "Data is key - and industries able to draw expertise from data scientists will be the first to capitalise on the AI opportunity."
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