December 6, 2023

The banking industry has changed dramatically over the decades. ATMs were introduced in the 1960s, and PIN and electronic card payments in the 1970s. The steady adoption of 24/7 online banking in the 2000s was followed by mobile banking in the 2010s.

The latest change for banks is their entry into the AI-driven digital age, fueled by falling data storage and processing costs, increased access and connectivity for all, and the rapid development of AI technologies, especially RPA.

RPA (Robotic Process Automation) is already simplifying time-consuming operations, reducing organizational costs, reducing or even eliminating human errors, and automating human activities such as data entry and simple customer service communications.

The shift to artificial intelligence

Now, digital transformation is driving incumbent banks to completely reimagine their businesses, moving away from legacy processes and changing their previously siled thinking to take full advantage of the benefits AI can bring.

The devastation of the health crisis of the past two years spurred them into action, and there is now no turning back.

The current technological disruption and consumer shift puts the financial services industry at a critical time.

This is a double-edged challenge for banks. To compete, they need to achieve the speed, agility and flexibility demonstrated by their fintech peers. But at the same time, they must continue to manage the scale, security standards and regulatory requirements of traditional financial services businesses.

As a result, for many financial services firms, the use of AI is fragmented and focused on specific use cases. But a growing number of forward-thinking companies are taking a more holistic approach to deploying advanced AI and embedding it across the lifecycle from the front office to the back office.

New business models, cost savings and revenue generation

Advances in artificial intelligence (AI) technology in financial services offer them the potential to grow revenue more cost-effectively by engaging and serving customers in entirely new ways.

In a short period of time, the industry has come to rely on the technology to power its data aggregation, security, authentication, products and services.

As AI gains a foothold in banking, financial institutions are building on existing solutions to solve increasingly complex challenges and deliver the seamless experience customers now expect.

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The three main areas where banks can use AI to save costs and improve efficiency are the front office (customer-facing banking), middle office (fraud detection and risk management), and back office (underwriting).

Choose the right field to use artificial intelligence

While a true “AI bank of the future” does not yet exist, many aspects of it are already in place. Here are six of them:

Customer-centric: AI and ML are starting to drive a better understanding of customer habits and preferences, enabling banks to personalize services at scale to create exceptional customer experiences.

Transaction and risk analysis: Financial institutions are using AI technology to identify fraudulent and unusual transactions, make decisions about creditworthiness, use natural language processing on text documents, and for cybersecurity and general risk management.

Bank Everywhere: Artificial intelligence capabilities in mobile apps are becoming more advanced and personalized, revealing services, offers and insights based on user search patterns. Thanks to AI, the bank has seen a nearly 66% increase in revenue from mobile banking users to brick-and-mortar users (visiting brick-and-mortar banks has dropped 30% since 2017).

Dialogue Facilitation: AI chatbots are communicating with customers for banks, simplifying customer identification and authentication, saving time and human resources. Research estimates that financial institutions save four minutes for each communication handled by chatbots.

Fighting financial crime: AI is collecting and analyzing data on millions of business transactions every day. AI-driven systems are being used to assess risk, detect and prevent payment fraud, improve anti-money laundering (AML) processes, and perform know-your-customer (KYC) regulatory checks by assessing customer credit histories to avoid defaults and predict risk vs. In connection with the disbursement of loans, such as customer bankruptcy or threats of fraud.

With approximately 1 billion credit card transactions per day, banks have access to one of the largest collections of customer data in any industry. Using artificial intelligence, banks can leverage this information to unlock unparalleled insight and growth.

All of these changes are part of the evolution of artificial intelligence. Step by step, the future of banking will look very different from today, but only if…

…As McKinsey predicts: “In order to successfully compete and prosper, incumbent banks must become ‘AI-first’ institutions, adopting AI technologies as the foundation for new value propositions and unique customer experiences.”