Artificial Intelligence is a combination of three technologies – machine learning, natural language processing and cognitive computing. If you take a closer look, all these three have something to do with human traits.

If there is one technology that’s impacting banking like no other, it ought to be Artificial Intelligence. Among other industries banks’ adoption of AI is growing at a furious pace. For the last few years AI has shown an increasing adoption rate and have been influencing various verticals to address pressing issues and offer unique solutions to users.

Let us see why banks find AI such a crucial technology and how they are leveraging AI to add-value to their business.

The following article is split into three parts:

  1. Reasons why banks are opting for AI
  2. Areas where banks prefer to have AI
  3. AI that top banks currently use

1. Reasons Why Banks are opting for Artificial Intelligence

Though AI adoption in the banking sector is still in an early stage, increasing number of use cases tell us that they have begun to understand the potential of AI and are ready to tap its benefits, thus fueling the rate of adoption steadily.

According to a survey conducted by Narrative Science, on the benefits of AI in banking, it showed that financial services cited three big reasons why they opted for AI

  • To improve the ability to compete with peers
  • To identify data that would be otherwise missed
  • And to increase workforce productivity

2. Areas where banks prefer to have AI

Technology brings convenience, but along comes challenges, too. Big challenges at that.

With AI empowering financial industry, impacting verticals across, the increase in its adoption is quite apparent. Banks are now focusing on pressing issues, aiming to bring in a resolve through Artificial Intelligence.

Fraud Detection

With frauds becoming loftier, it has become imperative for banks to formulate new methods of countermeasures. AI in fraud detection is gaining popularity more and more.

Identifying fraudulent transaction requires logical and deductive strategies coupled with the right technology. Experts believe that Artificial Intelligence has what it takes to spot these anomalies.

With Artificial Intelligence scrutinizing and streamlining billions of transactions can be done in seconds or minutes. They can graph/link network to identify relationships, can track sentimental and behavioural analysis, perform time sequence analysis, and above all get real-time reports on fraud detection, which is critical, especially in the banking industry.

AI uses deep learning techniques to detect fraud. Another widely used method is the automatic feature engineering. As this requires massive labeled data, experts are combining machine learning and deep learning to make AI much smarter in detecting banking and online frauds.
Trading

Banks are investing heavily in technology, even the ones who are strongly rooted in legacy systems are now coming out of their comfort zones to experiment and tap the benefits of Artificial Intelligence.

future of artificial intelligence in banking

AI has been put into use for trading for some time. Since the business of trading is complex, and somewhat emotional, bankers are looking for a solution that provides accurate and unbiased output. And trading experts are finding Artificial Intelligence could be the best bet when it comes to that.

However, the idea is not to replace humans completely, but to have them work in tandem.

AI Chatbots

AI is about offering human-like solutions without much of human intervention. Banks are leveraging this to the benefit of their customer service. We can see messaging apps are gaining traction, and the way customer service is done is changing across business verticals. More and more banks are bringing AI chatbots into their equation. The best part of chatbots are that they can be trained to probe, evaluate, analyze customer queries, and offer most appropriate answers.

The AI chatbot approach is helping many mid-level banking firms to improve operational efficiency, better customer interaction, and gives a sense of satisfaction that they are – technically, to some extent – in par with the bigger banks.

The reason small and mid-level banks are able to bring AI into their paradigm is that chatbots are relatively easy to build. IBM says (using IBM Watson) that even people with no programming knowledge too can build chatbots for their business in less time.
This article shows you how easy it is to build your own chatbot using IBM Watson.

Personalized Recommendations

For banking, offering customers with sound advice and recommendations is crucial and there is a forecast that it could be the next big disruption in the industry. This looks more likely to become true.

Consider apps like Simple and Moven. These apps enables users to keep a track on their spending and suggests them with viable saving options. Based on the segmented individual preferences, the app offers them with real-time, personalized recommendations that best suits them.

Apart from the service recommendations, the AI is also taking over the task of offering advice on products and recommendations, again, based on the preferences of an individual. Since the AI method is less prone to errors, it is considered as a reliable alternative. Customers find real-time personalized recommendations to be very helpful compared to the traditional updates.

  1. AI technology top banks currently use

JP Morgan Chase

JP Morgan Chase, one of the largest multinational banking and financial services company, has been investing in technology for some time now. For them sifting through thousands of annual credit agreement has remained a big challenge, both, in terms of accuracy and the time spent on it. To overcome this problem JP Morgan introduced Contract Intelligence (CoiN). This AI-powered program is specifically designed to analyze and extract important data points and clauses from legal documents. The manual process typically would take approximately 360,000 hours to review 12,000 agreements. But with CoiN, it is done in just a few seconds.

Wells Fargo

In April 2017, Wells Fargo tested its yet to be named pilot AI-powered Facebook chatbot. Wells Fargo needed a different kind of an automated customer service program for its customers on the social platform. So, they designed a personalized AI customer service bot to cater to Fargo customers on Facebook. The chatbot responds to users about accounts details such as how much money they have in their account, finding the nearest ATM, help them reset their passwords, and other customer service queries.

Bank of America

Bank of America’s own AI virtual assistant is named Erica. This chatbot is designed to leverage ‘predictive analytics and cognitive messaging’ to provide financial guidance to the company’s vast 45 million customers. Erica is accessible 24/7 and is capable of performing ‘day-to-day transactions’ including, fulfilling unique financial needs of each customer and helping them to reach their financial goal by providing smart recommendations.

There are several other banks, Citibank, Bank of NY Mellon Corp., PNC, who are using AI to perform banking tasks, which they feel would be efficiently done through Artificial Intelligence.

Endnote

There is no doubt that Artificial Intelligence is becoming a differentiating factor in the banking sector. However, before rooting for AI, the most important question banks need to ask themselves is – not how to implement Artificial Intelligence, but to identify where to implement the technology for a better business outcome.

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