Ramping Up AI Adoption

A recent survey by the World Economic Forum and the Cambridge Centre for Alternative Finance reports that a large number of executives say they will become mass adopters of AI in the next two years, and that AI will be a key business driver for them. Among the findings:

• 85 percent of financial services organizations are currently using AI in some form
• 77 percent believe AI will become essential to their business in the next two years
• 64 percent will be mass adopters of AI in the next two years
• 52 percent have created AI-enabled products and services
• 50 percent believe AI to be a competitive threat as others enter the market

Where AI Fits in the Banking Industry

AI has the unique ability to process massive amounts of customer and market information and make it readily available for analysis by financial teams, and it can continue to learn as information and circumstances change. According to a recent study by Deloitte, financial services companies are using to AI to:

Improve Strategic Plans

By embedding AI into strategic forecasting and planning, financial companies can develop more intelligent enterprise-wide strategies that have a big impact on operations, and that other business segments can follow.

Grow Revenue

AI is a great tool to improve the client experience and build engagement opportunities, especially online, which is a growing opportunity. AI makes it easy to track user behavior and provides metrics that banks can use to track progress.

Keep Options Open

Leading banks are looking to employ multiple approaches to using AI applications, allowing them to accelerate the adoption of AI initiatives and solutions.

Another big reason for increasing the adoption of AI is cost savings: the aggregate potential cost savings for financial institutions from AI applications will be an estimated $447 billion by 2023.

Using AI in Fraud Detection

One of the most prevalent use cases for AI in financial services is in consumer finance, particularly with fraud and cyber attack prevention. According to Business Insider, online payment fraud losses are expected to reach $48 billion by 2023. AI’s powerful analytical capabilities can identify anomalous patterns in online banking activity that would usually go unnoticed by people.

An example highlighted by Business Insider is Chase, for which consumer banking represents over half of its net income. The bank has adopted fraud detection to protect their business, using proprietary AI algorithms to detect fraud patterns. Details of every credit card transaction are transmitted to a Chase datacenter where they can determine whether or not the transaction is potentially fraudulent. The technology has been so successful that the bank scored second place in Business Insider Intelligence’s 2020 US Banking Digital Trust Survey for security and reliability.

AI in Risk Management

According to a study by EY, risk management is the domain with the highest rate of implementation by financial institutions to date, at 56 percent. The following examples highlight how risk can be analyzed by AI to improve lending and investment practices:

• One new AI platform offers a “collective intelligence” solution, providing a range of services in risk management, portfolio management, investment operations, and trade execution. The firm is managing trillions of dollars in assets.
• Another solution uses AI, blockchain, and big data analytics for a variety of products offered to Chinese financial institutions. It has a client base of 3,600 financial services companies.
• AI is used by a third company to create alternative datasets that are used to customize loans for small and midsize enterprises.

Creating Customer Service Excellence

Financial services is a highly competitive industry, so banks are always on the lookout for differentiators that set them apart in the eyes of customers. AI-driven apps can help automate processes to improve customer service and satisfaction while also lowering expenses. A few examples recently highlighted by CIO Magazine:

• Online AI-powered chatbots use natural language processing and voice analytics to manage customer interactions without human intervention. They can help customers check account balances and apply for loans, among many other activities.
• AI-driven voice recognition and natural language processing are also used to help improve the quality of customer interactions. AI can detect both the words customers use and the tone and sentiment behind the words, giving the bank deeper insights into customer needs.
• AI is used on the back-end of banking systems to provide analysis of consumer behavior, predict customer preferences, and provide a tailored, customized user experience for each individual.

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Raise Your Profile in Financial Services AI

Financial services companies are eyeing massive growth as they adopt exciting new technologies like AI. Whether you’re studying up on becoming an AI engineer, a machine learning expert, or want to master the nuances of deep learning and TensorFlow, there are ample upskilling opportunities available. Get started today and see how fast you can accelerate your career in the financial services sector.