Over the last decade, banking institutions and financial services have been making use of artificial intelligence (AI) more than ever. As customers continue to embrace an exponential growth in digital markets, it is essential that older sectors like banking do what they can to keep up.
In 2017/2018, the Banking System Survey showed that banks are hiring more IT and Data professionals than ever before. Since then, many traditional banks have collaborated with fintech start-ups or devised solutions in-house to offer modernized banking solutions to their customers. The focus has been on using AI and new technology like Blockchain to propel the industry into the 21st century.
In this article, we will look at what AI is, some of the ways it can support, automate, and innovate banking and how it might look in the next five years.
What is AI?
When talking about AI today, it relates to what is known as “narrow AI.” This type of AI makes use of data and allows computer systems to learn independently from past experience. As a broad term, it involves developing machines and systems that can complete complex tasks, normally believed to require intelligence, akin to that of a human.
In all industries, AI is making smart connections between humans and machines.
AI in banking
In banking, the utilization of AI has become more of a necessity than a “nice to have.” They are under intense pressure on multiple fronts with the rise of Fintech companies, accelerated digital disruption, and widespread technological advances. The need for AI in banking includes;
· Improving operational activities and employee productivity
· Demand for customer self-service
· Reducing the risk of fraud
· Cybersecurity for the digital era
· Managing large volumes of data and transactions at speed
· Customer demand for customization
Key Applications of AI in Banking for the next 5 years
Whilst banking has already seen some major developments in AI, these will continue to gain momentum as we enter a new decade.
The conversational chatbot is forming a big part of customer service. This type of AI platform can augment human customer service by providing automated answers to routine questions. A Salesforce survey found that 64% of advisors say that chatbots allow them to spend more time solving complex problems, compared to 50% without chatbots. Advisors are able to delegate their workloads to the AI tools, saving them time, the bank money, and a better satisfaction level all round.
The problem right now is that only 16% of consumers say they are happy with the digital experience from their bank, proving there is still a long journey ahead. Some banks are in front of others. For example, Standard Chartered is using the Kasisto platform to create their chatbot. The bot has been specifically designed for financial services and can answer more complex questions. Erica from Bank of America is not able to handle the same complexities.
In the next 5 years, banks will almost definitely try to perfect the conversational chatbot.
In financial services, predictive analytics is the use of existing data to find patterns that can help forecast the future. One such example is Katana, developed by Dutch Bank ING. The platform uses both real-time and historical data to present accurate information to users. The objective is to help traders get a better price when buying and selling.
The implementation of Katana led to faster pricing decisions for 90% of trades and a 25% reduction in trading costs.
Banks can use similar technology for credit scoring, risk planning, and intelligent budget insights for their customers. We are gradually seeing more of these products hit the market as banks upgrade their legacy systems. Over the next 5 years, it is expected that they will become virtually the norm.
Arguably the biggest impact of AI in banking will be enhanced fraud detection. As more and more transactions become digital. Systems like FICO are able to use data as a method of self-learning, detecting anomalies in behavior. If transactions start falling outside of regular trends on accounts, the system will pick up on that and notify the bank.
Teradata offers one of the most popular fraud detection systems for banking. At Danske Bank, they reported huge reductions in false positives when it comes to potential fraudulent transactions whilst increasing the detection of fraud by as much as 50%. Beyond all of that, where this is automated through data, the manual work needed to pinpoint fraud was mainly removed.
Going forwards, banks will need to ensure they invest adequately in AI fraud prevention solutions if they are to meet the demands of a digital economy.
AI solutions will give banks a competitive advantage against those who fail to develop solutions. The next five years will not focus quite so much on regulation as banks move towards knowing their customers better and responding to their needs.
In reality, banks don’t really have a choice where it comes to AI. They need to develop their technological maturity to make them more effective and their staff more productive. Big banks are already heading in that direction with the support of FinTech’s and smaller institutions will follow suit in the next five years.
Of course, security is integral to financial services and banking. Many banks have already implemented voice and fingerprint recognition within their regular processes. Having these features available has become a customer expectation.
Going into the next five years, it is likely we will see these features continue to develop. For example, facial recognition could be used to authorize basic transactions as well as confirming identity. This will make transactions easier and faster.
AI is having a big impact on banking and will continue to do so in the next five years as it develops at pace. We are only are the very start of the AI journey and still don’t understand all its capabilities. From detecting fraud, improving security to chatbots, and enhanced customer service, AI will significantly change the experiences we all have with banks.
Disclaimer: The author of this text, Robin Trehan, has an undergraduate degree in Economics, Masters in international business and finance, and MBA in electronic business. Trehan is Senior VP at Deltec International www.deltecbank.com. The views, thoughts, and opinions expressed in this text are solely the views of the author, and not necessarily reflecting the views of Deltec International Group, its subsidiaries, and/or employees.
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