If you've been keeping up with the news lately, you've probably noticed that AI is everywhere. From the concept of self-driving cars to newcomers like voice generation, deepfake videos, and OpenAI (Midjourney and ChatGPT), AI is changing the way we live and work. But it's not all sunshine and rainbows – there are also concerns about the ethical implications of AI, particularly when it comes to fraud. The first question we must ask ourselves is: why is AI a dangerous fraud trend in banking? AI has the power to automate and streamline banking processes, which can be exploited by fraudsters.

From restaurants to retail, industries where customer service is an integral part their business continue to deal with major staffing shortages. This includes financial services and financial institutions, and by extension, credit unions. Securing reliable and long-term frontline help devoted to providing member service was difficult even before the COVID outbreak. Following the tidal wave of closures of physical branches that accompanied pandemic lockdown, many member service representatives left for other positions, or simply never came back. With no end in sight to the staffing crunch, and members demanding a more personalized service experience, credit unions must consider an option many previously thought was too expensive, 'impersonal', and too complex to maintain.

Jamie Dimon, chief executive officer of JPMorgan Chase & Co., speaks virtually during a webcast ... [ ] event on a mobile phone. If you want to know which technologies will be hot in the banking industry in 2023, heed the advice of Deep Throat. In the movie All The President's Men, Woodward and Bernstein's informant--whom they refer to as Deep Throat--tells them: "Follow the money." A new study from Cornerstone Advisors, What's Going On in Banking 2023, follows the money and reveals where banks and credit unions will place their technology bets in this uncertain year. Uncertain not just because of the economic conditions, but because of the vagaries of the organizational and technological environments in which banks operate.

No two customers are alike, and each consumer expects you to know them, understand them and reward them with a level of contextual experiences that extend from product creation to service delivery… across the entire customer journey. Effectively executed, this level of personalization will support proactive engagement at the time and in the channel where the customer benefits the most. Organizations in every industry are making major investments to improve customer experiences. An estimated $6.8 trillion of direct investments in the digital experience is expected through the next two years, according to IDC, with 75% of organizations pursuing comprehensive digital transformation. Differentiating an organization requires customized solutions that can deliver contextual experiences.

ChatGPT is causing waves in just about every industry, and there's no doubt it will be a powerful tool in assisting roles that involve written and verbal communication. But will it replace a universal associate? Compare it to digital/mobile banking, and the benefits and drawbacks of the technology. While ChatGPT presents the possibility of efficiency and scaling, and there are security concerns and it's never going to completely replace your staff members and human interaction and unique problem-solving skills they bring to the table. Digital banking and ChatGPT are solutions for scaling.

The financial services industry has seen a great deal of disruption from digital-based alternatives. Many of these challengers use advanced technology and expanded data sets to offer apps that provide financial solutions at a lower cost, with less friction and greater personalization than traditional bank or credit union offerings. Toronto-based startup Flybits believes that the best way to compete in the future is not just by developing innovative products and services, but by becoming the repository of choice for data in addition to money. "I definitely see that banks are in a perfect position, if they innovate right, to be the perfect data vaults for the future – managing the privacy and also the data of their customers," says Hossein Rahnama, CEO and Co-Founder of Flybits, in an exclusive interview for Banking Transformed, a new podcast from Jim Marous and The Financial Brand. "Using AI and machine learning, there is the potential to build a'data marketplace' for banks, fintechs and other data providers to partner and build more services together."

Artificial intelligence and machine learning have become vital to many aspects of financial services, from powering chatbots to improving fraud detection. But one area where AI has not gained as much traction, particularly with community financial institutions, is in sales and marketing. Its use has been steadily ramping up, though: SouthState Bank and Eglin Federal Credit Union are among those using AI to parse data in ways that have resulted in much greater impact for their marketing efforts. Rather than targeting people based on simple demographics like age or gender, they combine internal data with information available beyond their own databases to surface a much more telling -- read: predictive -- combination of details. The key benefit has been the ability to more accurately identify when customers are ready to buy a particular financial product and deliver the appropriate messaging to them.

The problem with banking's use of artificial intelligence technology is not always in a bank's inability or unwillingness to invest in it. In fact, more financial institutions are spending on AI and related technologies as banking leaders strive to build out customer personalization. The problem instead can lie in a financial institution's failure to align the technology with the bank's strategy. As a result, a bank or credit union might buy (or build) the technology, but then abandon it shortly after or fail to follow through with it, a McKinsey report points out. The report uses an unnamed large retail bank as an example, one that has set aside resources in the budget for machine-learning (ML) technology -- one part of AI -- to automate marketing and customer personalization campaigns.

Throughout 2021 many banks and credit unions implemented AI and virtual agents for the first time, and many more plan to follow suit this year. While sometimes slow to adopt new technology like this, financial institutions needed to be more rigorous in their approach to problem-solving in a socially-distanced world. While AI started to permeate member-serving businesses even before COVID, its use in the financial sector is reorienting the digital trajectory of the industry as a whole. AI has allowed financial institutions to remain competitive and provide high-quality customer experiences throughout the disruption of the last two years. It is clear more than ever that member bases will continue to seek the digital-first experiences they've come to enjoy.

Artificial Intelligence in financial services is still largely filled with untapped potential. While many bankers may think of things like chatbots and fraud monitoring when it comes to AI, in reality the technology can be used in just about any conceivable part of a bank or credit union. For the most part the industry has not even scratched the surface of how AI can transform banking. Here are some of the top ways financial institutions can deploy artificial intelligence in 2022 and beyond. Let's start with the most obvious application first.