Banking on AI: the true value of AI in Financial Services

In a matter of decades, banking has changed fast. ATMs were introduced in the 1960s and PINs and electronic card-based payments in the 1970s. The 2000s saw steady adoption of 24/7 online banking, quickly followed by mobile banking in the 2010s.

The latest change for banks is their entry into the AI-powered digital age, facilitated by falling costs for data storage and processing, increasing access and connectivity for all, and rapid advances in AI technologies, notably RPA.

RPA (robotic processes automation) is already streamlining time-heavy operations, reducing organizational costs, reducing or even eliminating human error, and automating human activities such as data entry and simple customer service communications.

The shift to AI

Now, digital transformation is driving incumbent banks to totally reimagine their operations, break away from legacy processes and alter their previous siloed thinking to fully exploit the advantages that AI brings.

Their actions have been catalyzed by the monumental disruption of the health crisis over the past two years and now there is no looking back.

The current technology disruption and consumer shifts have placed the financial services sector at a pivotal moment.

This represents a double-edged challenge for banks. To compete, they need to achieve the speed, agility, and flexibility that their fintech peers have shown. But at the same time, they have to continue managing the scale, security standards and regulatory requirements of a traditional financial-services enterprise.

For many financial services firms, therefore, the use of AI is patchy and focused on specific use cases. But a growing number of forward-thinking firms are taking a more holistic approach to deploying advanced AI, and embedding it across the full lifecycle, right from the front- to the back-office.

New business models, cost savings and revenue generation

Development of artificial intelligence (AI) technologies within financial services is offering them the potential to increase revenue more cost-effectively by engaging and serving customers in radically new ways.

In a very short period of time, the sector has already become reliant on the technology to power its data aggregation, security, authentication, products and services.

As AI is increasing its foothold in banking, financial institutions are building on their existing solutions to solve increasingly complex challenges and to deliver the seamless experiences their customers now expect.

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

Selecting the right areas to use AI

While the true ‘AI bank of the future’ does not yet exist, many aspects of it are in place. Here are six ways in which they are:

Customer-centricity: AI and ML are starting to drive a superior understanding of customers’ habits and preferences, enabling banks to deliver personalization at scale to create superior customer experiences.

Transaction and risk analysis: Financial organizations are using AI technologies to identify fraud and unusual transactions, make decisions on creditworthiness, using natural language processing on text documents, and for cybersecurity and general risk management.

Ubiquitous banking: AI functionality in mobile apps is becoming more advanced and personalized, showing services, offers, and insights based on user search patterns. Thanks to AI, banks are generating almost 66% more revenue from mobile banking users to physical users (visits to physical banks have fallen 30% since 2017).

Conversation facilitation: AI chat bots are communicating with customers for the bank, smoothing customer identification and authentication and saving time and human resources. Research estimates that financial institutions save four minutes for each communication that the chat bot handles.

Financial crime fighting: AI is collecting and analyzing the data of millions of business transactions every day. AI powered systems are being used to assess risks, detect and prevent payments fraud, improve processes for anti-money laundering (AML) and perform know-your-customer (KYC) regulatory checks by appraising customer credit histories to avoid default and anticipate the risks associated with issuing loans, such as customer insolvency or the threat of fraud.

With around a billion credit card transactions every day, banks have access to one of the largest volumes of customer data of any industry. Using AI, banks can harness this information to unlock unparalleled insights and growth.

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

… as MckInsey predicts: “To compete successfully and thrive, incumbent banks must become 'AI-first' institutions, adopting AI technologies as the foundation for new value propositions and distinctive customer experiences.”