Data analytics is becoming a cornerstone of the financial industry, with startups and established financial service firms looking to give investors clearer guidance with information collected and captured from multiple sources.
Advances in machine learning and artificial intelligence (AI) in particular are providing greater insights and better customer experiences.
AI-powered data analytics not only captures vast amounts of data in real-time, but also helps users understand how different data points relate to each other, providing insights that might otherwise be lost. Faced with a breakdown in brand loyalty as younger customers prioritize user experience, financial services are now racing to leverage data-driven cognitive technologies.
Cambridge, MA-based Kensho, which recently received $58 million in funding from Goldman Sachs, San Francisco-based Alphasense, backed by Tribeca Venture Partners, and Toronto-based Bigterminal are some of the fintech players leveraging AI.
It’s a lucrative market. Equity deals for AI startups, including fintechs, has increased nearly six times to nearly 400 in 2015, up from from 70 in 2011. As of June 15th, more than 200 AI-focused startups raised nearly $1.5 billion (U.S.) in funding this year alone.
“Data is the lifeblood of AI,” Falguni Desai of Future Asia Ventures wrote in Forbes recently. Desai quotes Adrian Lawrence, partner at Baker & McKenzie, in saying: “data and the various rules and processes which both enable and regulate access to and use of that data, stand at the heart of disruptive fintech businesses.”
The market is also “evolving from a descriptive analytics model (rear view mirror view) to a predictive analytics model (insight GPS view),” says Jim Marous, co-publisher of Financial Brand.
“With predictive analytics, we are in a better position to ‘know the consumer,’ ‘look out for the consumer’ and ‘reward the consumer,’” he writes, “learning from previous experiences and predicting future behaviour.”
Bigterminal CEO Adam Rabie says advances in machine learning are allowing fintech platforms like his to do more for their customers.
Powered by IBM Watson, Bigterminal’s solution curates, consolidates, and analyzes financial data from markets, social media, and other sources. The company’s target market includes researchers, analysts, and traders as well as big banks and insurance companies. Bigterminal’s app can be used to conduct research, generate hypotheses, and make decisions based on significantly more data than what financial analysts traditionally use.
Leveraging IBM Watson’s cognitive technology has allowed Bigterminal to do what was previously unthinkable, Rabie says.
“Our machines are computing hundreds of thousands of stories a day, millions of tweets, and trillions of financial data points,” he says. “If it can be smart at finding the anomalies and the connections between them, it can deliver a lot of explanations that are outside of human capacity.”
Other notable financing in the space includes a $325 million Series E round last year for Avant, a personal-loan startup that leverages machine learning. Seattle-based fintech Kavout also recently launched a new investment platform that finds trading opportunities using tools powered by machine learning and big data.
Improvements in cognitive technology, such as relationship analysis and language comprehension, will expand the possibilities for data analytics in finance and banking. As fintechs bring this functionality into their services, they will continue driving disruption in the financial world.
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