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How AI Is Rewriting the Future of Banking

Bank of America (BoA) invests annually over $3 billion on new technology and digital transformation. Most other banking giants are doing the same.

According to the results of different surveys, more than 80 percent of global banks have started implementing digital transformation strategies in 2018. The primary focus of these strategies is to upgrade security, cut compliance costs, compete for younger consumer groups and develop more personalized product offerings and customer services. Advances in technology are delivering on their promise across all bank departments and suctions.

More recently, BoA has implemented an AI-powered virtual assistant that applies cognitive abilities when serving clients. The Bank gave it the name “Erica,” humanizing the technology and contributing to the overall brand. Erica’s artificial intelligence (AI) engine now offers customers real-time tips on investing, answers to their instructions and accurately addresses their requests.

A customer survey by Accenture has found that the younger a customer’s age, the more technology they expect to find when engaging banks. They expect these technologically supported services to be intelligent and they see them as a reward for sharing their data, which banks analyze and exploit for strategic ends.

The banks utilize data to deliver more personalized services. Technology allows them to acquire more profound insight into how customers behave financially and interact with the banking systems. This makes the bank-bank-customer relationship mutually rewarding.

The financial industry had begun its automation revolution long before AI became a buzzword. The shift started with automating routine tasks, which included updating savings books and carrying out cash deposits, customer verifications, salary uploads and more.

It was only in the last decade or so that AI and its different applications would become the go-to transformative technologies for accomplishing leaps in customer service, risk and wealth management. The use cases of AI in the financial industry are diverse and many, and their applications are invading almost every facet of services, from core banking to customer relations, security and investment.

In return for the customers’ behavioral data and profile attributes, AI systems offer clients a seamless proactive and personalized user experience. This allows banks to deliver targeted and personalized products to customers. The approach allows banks to increase a customer’s connection with the brand and their long-term loyalty.  The different banking systems, including payments, compliance, and profiling are all integrated seamlessly. The AI systems in place cross-analyze the massive streams of data to extract values that deliver effective customer and market insights.

Regulatory agencies have actively been encouraging the financial industry to adopt AI technology in compliance management. Only through analyzing data can banks trace and detect suspicious transactions, manage trade based compliance and anti-fraud. By applying machine learning and predictive modeling, advanced anti-fraud solutions can predict fraudulent transactions in real-time catching hackers in the act.

Through machine learning systems banks develop behavioral models that can identify suspicious activities with higher accuracy. Future technologies can do even more as they link IoT with AI systems giving them data feeds to base their machine outputs upon. An example would be a client claiming to have deposited funds himself at an ATM in London and another in Paris at different times. The AI-powered compliance system can validate client claims by analyzing them against facial recognition data from ATM cameras.

Intelligent machines do not collude with criminals, and neither do they make emotionally biased judgments. They also do not need constant supervision to operate day and night. Such qualities make machine intelligence a welcome upgrade for managing banking operations efficiently all the time.

Furthermore, AI systems do not stop working and can handle an infinite number of tasks or routines while also analyzing and cross-examining data sets from different sources, structured and unstructured. This translates to substantial cost savings for banks as the systems replace thousands of human hours spent on routine functions. New banking concept, like that of ICICI, Yes, HDFC, Axis are pushing these new applications to market fast.

It’s not just financial institutions that have adapted AI technology for powering up their economic ecosystems. Digital market giants like Amazon, Google, Facebook, and Apple collaborate with different banks to allow customers to interact with their bank accounts directly.

Through Amazon’s Alexa, Apple's Siri and Google's Assistant, users can manage their accounts through voice instructions. By linking to bank accounts, these intelligent assistants allow customers to check their balances and pay bills. Those cyber giants are also working toward giving users the facility to wire money using their voices.

Some are beginning to wonder if Facebook or Google are building toward dominating the future financial service industry. Those socially-driven market powerhouses already own the behavioral data of the global customer-base they are serving. They can put it to use to compete with any of the banks out there.

The new profile of customers is nomadic. They rely on the power afforded to them via mobile devices to transact financially and socially. This emerging market reality is changing the way banks have done business for as long as one remembers.

Even with all these changes in technology, AI is still in its baby steps across all industries. In time this technology is expected to roll out across most industries. When this happens, a super mashup of data sources will follow.

Technology is creating a new holistic digital realm interconnecting businesses, industries, and financial transactions. One can only imagine the quality and quantity of business intelligence and insight offered by this future web of intelligent systems.

Belal Hejawi                                                                                              

Content Development  

 

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