Why isn’t AI a thing yet in banking?

Challenges in AI Deployment in Banking Industry

Future of Banking in AI

Why isn’t AI a thing yet in banking?

Future of Banking in AI

Business experts predict advances in artificial intelligence and automation can replace up to half of the employees in financial services, during the next decade. However, it’s going to take a major investment to make that occur. James D’Arezzo, Chief executive officer of Glendale, California based Condusiv Technologies, says where things are headed. The roadmap ahead is complicated. Unless of course, banks handle the performance problems that AI will cause of ultra big databases, they wouldn’t be able to spend the money gathered by removing places and spend it on the new solutions and products they’ll need to stay competitive, he said.

Intensive hardware updates are often cited as a reply to the problem, but D’Arezzo explained that’s prohibitively pricey. He quoted the latest statement from the Tokyo Institute of Technology’s global science and Computing Center for instance. The center is creating a supercomputer to fulfill the needs of artificial intelligence and large information programs. But existing supercomputers have a propensity to cost $50 thousand to several hundred thousand dollars, he said, which negates the cost reduction benefits of AI technology. But technical problems aside, senior banking executives agree on the inevitability of artificial intelligence based solutions and the job losses they’ll create.
robot vs human
Talking to an audience last year in Frankfurt, Germany, Deutsche Bank Chief executive officer John Cryan predicted a bonfire of business occupations as automation moves ahead. “In our bank, we’ve people doing work like robots,” he said. “Tomorrow we may have robots behaving like people”. This puts major stress on the capability of the financial business to process all that data. Businesses in the banking sector are spending more on IT than any other industry, including healthcare and manufacturing. D’Arezzo said many jobs would unavoidably disappear. “On the service side of AI, you may get right down to the irate client who would like to know about a deposit, although you will still have to get an individual involved to handle that if it gets more complicated,” he said.

However, it is possible to shave off that top 10 to 20% of the mechanical and rote problems which come up. Potential uses of AI technology include automated client service, fraud detection, claims management, insurance management, automated virtual financial assistants, predictive analytics in financial services and asset management solutions for lower net worth customers. “It’s like anything else That the prediction statement might be a little overblown,” D’Arezzo said. “Back whenever we were children we thought we’d all be driving flying vehicles by now.”

Vymo has taken a step towards bringing in AI in the sales function. Our suggestions module has been helping reps take decisions based on the success of the out even before it has happened. Vymo’s intelligence engine crunches terabytes of data to compile answers to these questions and more. To consume the high dimensional time series data of user activity logs, we use Recurrent Neural Network (RNN) architectures like Long Short-Term Memory Networks (LSTMs) and Gated Recurrent Units (GRUs).

To know more how AI can help your sales reps do more and take outcome-oriented decisions, schedule a demo today.

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Amit Rao

Engaging thousands of prospects and customers through personalized content is impossible without arming your marketing forces with artificial intelligence. However, one of the largest issues that I predict will be in deployment is the acceptance of AI from the consumer end.

Shanta Dutta

Well said Amit. But deployment can easily be solved with enhanced coaching and organizer seminars. (:

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