Artificial intelligence is here to stay, and 2017 will be about the adoption of ML/AI by the FinTech community and beyond. Experts agree that FinTech companies will harness this technology to make better decisions and offer improved solutions—they will make use of predictive analytics to break down big data and analyze large volumes of consumer information.
Henri Arslanian, PwC’s FinTech and RegTech Lead for China/HK, emphasizes a particular area of focus for AI adoption, saying, “While the focus in the media is often on AI replacing human fund managers or traders, the most pressing use cases may be cost reduction or compliance issues—where AI helps banks in their anti-money laundering or employee misconduct detection efforts by replacing costly functions that are currently done manually by humans.”
A variety of financial institutions have turned from words to actions, adopting ML/AI in various operation areas. One of most vivid indicators of transformative processes in banking is Goldman Sachs—the company brings significant automation into areas of trading like currencies and futures using complex trading algorithms, some with machine learning capabilities. According to the MIT Technology Review, the number of US cash equities trading desks at Goldman Sachs’s New York headquarters employees went from 600 in 2000 to just two equity traders and automated trading programs supported by 200 computer engineers doing the rest of the work.
The application of AI for GS goes beyond trading automation. The bank has strong ties (as a customer and an investor) with AI software provider Digital Reasoning, whose solution GS uses to track traders. The same startup has also launched a program with NASDAQ to use its AI technology to track trading data, communications, emails, chats, and even voice data to ferret out misconduct across the entire electronic stock exchange.
Moreover, Goldman Sachs uses the machine learning platform Kensho to mine data from the National Bureau of Labor Statistics and compile all that information into regular summaries. The reports feature 13 exhibits predicting stock performances based on similar employment changes in the past, and they’re ready to print just nine minutes after the data is entered.
But let's move to some other interesting examples—HDFC, ICICI, BofA, Charles Schwab, and JP Morgan, among other institutions that Citi has revealed to be applying AI across numerous use cases.
In December 2016, HDFC Bank tied up with AI firm Niki.ai to bring in "conversational banking"—chatbots that facilitate commerce and banking transactions without getting out of the chat window. The chatbot is presently available on Facebook Messenger, where it can be used for e-commerce transactions like booking a cab, ordering food, or paying bills.
The tie-up is aligned with the vision that HDFC executives have for the future of banking: “The two-three most promising areas where digital advances could revolutionize the customer experience are artificial intelligence, chatbots, and personalization,” said Nitin Chugh, Country Head – Digital Banking.
HDFC is not the only bank bringing AI into customer touchpoints. Earlier that year, AI startup Kasisto announced that its KAI platform is powering the virtual assistant in DBS’s mobile-only bank digibank. In fact, the virtual digital assistant (VDA) market is estimated to reach $15.8 billion worldwide by 2021, with unique active consumer VDA users growing to 1.8 billion and enterprise VDA users rising to 843 million.
One of the pioneers to bring early AI tools into banking/trading was Charles Schwab, which, way back in 2011, started applying chart pattern recognition designed to simplify complex trading activities and provide a more intuitive experience for traders. Nowadays, Charles Schwab is way ahead—Schwab Intelligent Portfolios is a fully automated investment advisory service by Charles Schwab, which, being launched in March 2015, by the end of June had grown to more than $3 billion in assets under management and more than 39,000 accounts.
Ravi Narayanan, Country Head – Branch Banking & Retail Trade FX Business at HDFC, emphasized that AI would be the most defining technology for the banking industry. Given the variety of use cases that financial institutions have found for the advanced technology and undebatable benefits for organizations and customers, Narayanan is certainly not overestimating the value of AI in finances.
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