Deep Learning is considered part of a broader family of artificial intelligence methods used to learn and process data to output required decisions. The process is mirrored in the way a human thinks and is a phenomenon that’s being used by key financial institutions today. The concept of its artificial intelligence is to ensure that the concept mirrors how a human learns, processes, thinks and performs. The difference is that deep learning algorithms use data to output predictions through the interpretation and analysis of data fed into the technology and delivering the structured and repetitive output faster. It can be thought of predictive analytics, learning data and identifying trends where the prediction is the answer.
Consider the contents of a TV, where the algorithm goes through a process of expanding its knowledge on what the contents of the TV are. Through iterations, data is fed into the technology continuously, recycles outputs until it gets to the point where the required output is accurate. Data Scientists enact this process in the background through the following procedure; the technology understands the problem, learns the input against the chosen algorithm, labels the data sets to train the algorithm and tests the output against unlabelled data. Remember, the algorithm needs to learn and deliver accurate output without support (labeled data). This is called semi-supervised learning, a concept commonly used in deep learning.
Deep learning has revolutionized the banking sector, even though most institutions are at an early stage to adopt the technologies, it is predicted that most if not all banking institutions will be taken over by AI. Here are some example use cases where this capability is impacting the banking sector:
- Smart Customer Support – Banking services are essential to customers. Customers nowadays want on-demand service and real-time updates. Through automation and accessibility of banking services through mobile, for example, customers will be satisfied in optimizing banking resources on the go. Automated customer service also helps limit any needless conversation that can be handled efficiently through virtual assistants, or chatbots.
- Real-Time Fraud Detection – Nowadays, customers that access mobile banking and perform an unknown transaction, such as paying into a bank with a high amount, triggers an automated fraud detection service where customers need to confirm payment before processing. This is known as on-demand security where instead of halting a transaction to contact the fraud departments, most now include the capability of confirming a transaction through a text message or email. AI firms have selling fraud detection systems to banking institutions, such as Teradata.
- Credit Choices – Credit scoring through AI helps utilizes sophisticated rules compared to traditional credit scoring. The use of deep learning algorithms allows for accurate assessments for borrowing, determines bankers’ credit rates and make accurate decisions based on credit history. Deep learning algorithms can continuously learn and process credit scoring over until it acts as an accurate credit scoring system.
- Regulatory Compliance – Mobile banking has been crying out for compliance with online activity to increase security. For example, fraudulent cases are a regular occurrence online and banking institutions have to guard themselves and customers against it. According to Deltec Bank, Bahamas, “Through smart analytics, AI can use data to observe behavior patterns of mobile banking users to identify suspicious activity. In return, banking institutions can align their compliance according to mobile banking activity.”
To sum up, deep learning and AI are beginning to become engraved in banking sector operations and it is predicted to take over, leading to a fall out of human necessity where something small as administration tasks can be performed by virtual assistants and chatbots. Because of AI, banking activity is available on the go in real-time and on-demand. Deep Learning can be trained to perform interpretation and analysis (in technical terms) to output accurate response, maybe more accurate compared to a human. In time, the world will be surrounded by smart AI to deliver efficient customer experience.
Disclaimer: The author of this text, Robin Trehan, has an undergraduate degree in Economics, Masters in international business and finance and an 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.
About Deltec Bank
Headquartered in The Bahamas, Deltec is an independent financial services group that delivers bespoke solutions to meet clients’ unique needs. The Deltec group of companies includes Deltec Bank & Trust Limited, Deltec Fund Services Limited, and Deltec Investment Advisers Limited, Deltec Securities Ltd. and Long Cay Captive Management.