Fintech platform revenues for unsecured consumer loans issued using machine learning technology will jump to 960% during the period 2016-2021, as per Juniper Research. Juniper, a market research firm, predicts that the machine learning technologies in Fintech will rise to USD 17 billion globally in the latter forecast year.
The study found that machine learning spend in Fintech will advance rapidly, owing to the highly data‑driven nature of the market, meaning that 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 VC and R&D investment. Meanwhile, vendors analysed in Juniper’s research have spent a total of USD 83 billion in R&D during 2015. Each of these vendors name AI as a part of core strategy.
AI Becomes Affordable
Until recently, machine learning was too expensive and computationally time-intensive to break into mainstream. Meanwhile, access to extensive data sets for algorithm training were limited, as per the report.
Presently, the ability to use GPU (graphics processing unit) hardware for processing massive and highly available data sets, along with unlimited affordable computing power in the form of distributed architecture, has opened the market to a swathe of disruptive new players.
Risk Assessment Driving AI Spend
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.