Leading banks like JPMorgan Chase, Bank of America and CitiBank have been in the limelight recently for adopting artificial intelligence (AI) technology to help them gain a competitive edge and generate more revenue. Keeping up with the ever-growing data and increasing customer expectations, cutting down costs and boosting work-force productivity are major challenges banks face – AI is here to help them address these issues.
Massive volume of data generated at high speed requires quick analysis and decision making, so that current market opportunities can be tapped to maximize profit. With the paucity of time and limited intellectual capabilities of humans, deriving accurate, unbiased, error-free and actionable insights on the fly doesn’t seem feasible. Not anymore. Having an AI-powered solution in place automates data analysis, while cutting down time and cost by a humungous amount. It finds application in loan processing, market data analysis, client portfolio analysis and insurance policy payout processing among others.
Banks spend almost 40 percent of their time on documentation- there are executive summaries, investment portfolios, loan agreements, etc. By automating data analysis and writing of reports using a natural language generation platform like PHRAZOR, banks can use this time constructively towards higher value activities. Well-researched, lucid, personalized narratives can be generated for clients, as well as everyone along the hierarchy within a matter of seconds. For instance, HDFC Bank partnered with vPhrase to automate the generation of branch manager performance reports. It helps in improving organizational productivity and striking a chord with your clients – the success formulas for an ambitious firm.
Natural language processing (NLP) bots play a major role in enhancing customer service. For instance, The Royal Bank of Scotland’s Luvo can answer frequently asked banking related questions and perform simple tasks like money transfers. Erica – the intelligent personal assistant deployed by the Bank of America, leverages predictive analysis and cognitive messaging to give financial guidance to its approximately 45 million customers. HDFC Bank has tied up with Niki.ai to facilitate chat-bot banking.
Sentiment analysis is another popular application of NLP. It can be applied to news articles and reports, social media and web content to understand the client’s sentiments about the firm and the investor’s views about the market.
AI software, armed with knowledge of the ongoing laws and latest banking regulations, serves as a good consultant. It is updated with the latest information, such that it doesn’t miss any rule and steers clear of any legal hassles involved in this space.
NLP in conjunction with machine learning techniques can be used by financial firms to detect possible illegal insider trading, by mining through e-mails, message boards and regulatory filings. Lloyds Banking Group has been using this method to identify fraudulent phone calls. Also, patterns can be detected in e-mails, transcripts of conference calls or annual securities filings to predict or detect fraud early.
In the case of Deutsche Bank, quantitative investing models and stock price prediction have seen significant improvement with the integration of an AI-enabled solution. Coming to stock trading, the US cash equities trading desk at Goldman Sachs’s New York headquarters went from employing 600 equity traders in the year 2000 to just 2 recently – the reason being that automated trading programs have taken over most of the work. Reports claim that more than 70% of the trading today is actually carried out by automated AI systems.
Finie, a voice-powered, AI-based intelligent personal assistant, can be integrated within a bank’s mobile app. It allows individuals to interact with their banking accounts using voice input. Rather than resorting to standard, template based questions, one can ask questions like, ‘Do I have enough money for the opera today?’ or ‘Did I spend more on shopping this month than the last one?’ Finie learns better over time about your financial management, offers personalized advice and also completes banking tasks. Mobile banking apps like Moven and Simple let users track their spending and increase their savings with a card linked to their smartphone app.
More power to AI as it goes on to become the most defining technology for the banking industry!