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Home Retail and Marketing

How Marketing Leaders Are Experimenting with, and Benefitting from, Artificial Intelligence in Banking

December 1, 2024
Reading Time: 7 mins read
What’s Your Bank’s Digital Maturity?

SPONSORED CONTENT PRESENTED BY ALKAMI TECHNOLOGY

By: Marla Pieton, Sr. Director, Research & Thought Leadership Strategy for Alkami

When I first began my banking career just over ten years ago as a marketing leader for an Ohio-based regional bank, I had no idea the impact that artificial intelligence would have on our industry, or my own career. After transitioning out of the bank and into tech, specifically with a company excelling at building artificial intelligence (AI) solutions for banks and credit unions, I believe that AI is the scientific method for financial institutions looking to enhance account holder engagement and is required for successful data-driven marketing and decision-making.

For Chief Marketing Officers (CMOs) and marketing teams in banks and credit unions today, understanding AI’s capabilities needs to be fundamental to the overall strategy of maintaining and acquiring account holders. Unlocking growth, elevating the account holder experience, and refining targeted campaigns are just some of the major key outcomes from leveraging this science. Responsibly mastering data usage and AI use cases will be a standout trait of the future leaders in banking, those known as data-informed digital bankers, who meet and exceed account holder expectations, exceed benchmarks in growth, and build lasting brand trust.

Exploring the Potential: AI-Driven Personalization in Marketing

AI’s power lies in its ability to personalize marketing at an unprecedented scale, creating new avenues for meaningful, data-informed customer or member interactions. According to recent research from Alkami, Application and Consumer Perception of Artificial Intelligence in Banking, 78% of financial institutions see AI as a catalyst for identifying new business opportunities, while 75% of banks and credit unions are experimenting with AI tools; 28% of those report they are leveraging AI specifically in their marketing. AI uncovers account holder behaviors, enabling marketing teams to target campaigns with next-best product suggestions and real-time offers that resonate personally with account holders. Some include:

  • Develop customized campaigns reflecting individual behaviors and preferences
  • Use predictive analytics to forecast account holder needs, enhancing cross-sell and up-sell success
  • Streamline account holder journeys with timely, relevant content that boosts engagement and satisfaction
  • Build audiences for competitive take-away campaigns

CMOs or leaders should consider AI-driven full-funnel marketing automation tools that offer hyper-personalization, crafting individualized interactions that convey distinct, relevant messaging rather than mass-marketing tactics.

Case Study Highlight: Leominster Credit Union’s partnership with Alkami demonstrates the transformative power of AI-driven personalization. By modernizing their digital banking offerings, Leominster significantly enhanced member experience, leading to an impressive adoption rate of the new platform within just a week. This success underscores the impact of using AI to create personalized, seamless customer journeys.

Data-Driven Marketing: Moving from Intuition to Intelligence

Data-driven decision-making is essential for modern marketing success, and AI facilitates this shift by making large-scale data set analysis manageable and actionable. Research indicates that digitally mature institutions, or “Data-First” organizations, execute an advanced approach and investment in data to guide strategic decisions. This analytical power combined with tools like AI predictive models can reveal critical patterns, enabling CMOs to make more informed decisions about their marketing initiatives:

  • Identify high-value account holders and segment audiences for targeted campaigns
  • Forecast churn, allowing for proactive retention efforts with at-risk account holders
  • Track marketing return-on-investment (ROI), supporting agile, data-informed campaign adjustments
  • Refine campaign performance by continuously learning and adapting based on data
  • Facilitate the creation of personalized, impactful content

Prioritizing data-led decisions enhances marketing impact, and for CMOs, AI’s automation capabilities can streamline and scale operations, freeing time for strategic efforts. Leveraging clean, well-organized data is the foundation for a marketing tech stack that integrates AI-driven data tools. By combining AI with the human element, automating content creation, campaign management, and optimization empowers marketing teams to focus on revenue-growing initiatives while maintaining high engagement with their account holders.

Case Study Highlight: Capital Credit Union Testing Standard Audience Segmentation vs. AI Powered Audience Segmentation “At Capital Credit Union, we really like the AI cross sell models as it helps target the members that we may have missed with the initial list. The AI cross sell models almost act as a safety net. Without this AI Model, we would’ve missed out on those prospects.” -Will Johnston, Marketing Analyst, Capital Credit Union

Building Trust in AI: Balancing Personalization with Relevancy

Alkami’s recent market study, “Application and Consumer Perception of Artificial Intelligence in Banking” revealed that while 96% of financial institutions consider AI critical for their future. However, their AI proficiency when self-assessed is in its infancy, a significant 75% of regional and community financial institutions are at least experimenting with AI in four operational areas – one of those being marketing (customer service, data insights, and/or security and fraud protection) with at least 88% of regional and community financial institutions saying their initiative has been mostly or very successful.

For AI-enabled marketing to resonate effectively, the financial services industry has room for improvement when it comes to relevant products and services recommendations. The study also revealed that consumers are much less inclined to believe marketing use cases (such as receiving relevant offers from their primary financial provider for new deposits, loans, and/or credit card accounts based on financial account history) will have an immediate impact to their digital banking experience. CMOs and marketing leaders can foster trust around the use of AI by:

  • Utilizing predictive AI models to offer insights into the right recommendations
  • Crafting transparent privacy policies to clarify data usage
  • Develop a communication strategy that emphasizes secure and ethical AI use in marketing, educating customers on how AI enhances their experience while safeguarding their data.

In Alkami’s study, 54% of financial institutions expressed concern that AI might negatively impact account holder trust, highlighting the importance of transparent AI communication to bridge the gap between consumer expectations and AI’s transformative potential.

Capturing Millennials with AI

AI offers a unique opportunity to cater to the demands of younger, digitally-savvy generations. Over half of millennials are open to AI’s role in delivering a personalized banking experience. This generation seeks real-time, customized digital interactions, positioning AI as a valuable tool for building loyalty among younger demographics.

Surfacing from the market study is a digital banking use case that younger consumers (aged 22-35) have a positive perspective on when it comes to AI usage – financial wellness. Twenty-one percent of them would be comfortable with AI informing financial tips on how to reach their financial goals, increase their credit score, pay down debt, and the like. This was the second most popular, right behind security and fraud protection (35%). Financial institutions can support financial wellness by providing personalized savings and budgeting advice or simply providing wellness education to account holders. While only 11% of RCFIs have applied AI in financial wellness, with just 14% indicating it as a next potential area of experimentation, this in lies an opportunity to capture this generation through an engagement that is welcomed and relevant to their financial journey.

As AI continues to gain traction across the industry from experimentation to implementation, financial institutions will be pushed to create a path for this evolving technology. Digital banking consumers (61%), including millennials, say in five years that AI will have dramatically changed how they do business with their bank or credit union.* Marketing leaders should embrace the vast potential it holds for improving customer engagement, personalization, and campaign effectiveness.

Case Study Highlight: First National Bank of Las Animas utilized Alkami’s digital banking solutions to introduce mobile-first onboarding and real-time funding. This not only streamlined their customer acquisition process but also enhanced their operational efficiency through automated identity verification and seamless data integration into core systems. This example illustrates how a strategic AI roadmap can successfully transform customer experience and operational workflows.

The Path Forward

Positive outcomes with the use of AI starts with educating all organizational levels on the fundamentals of the technology. A strategic framework from clean data to implementation and monitoring will build the roadmap for financial institutions to use the power of AI, and create both efficiencies and business opportunities across the organization.

Leominster Credit Union, Direct Federal Credit Union, and First National Bank of Las Animas exemplify how AI-driven solutions can reshape digital banking, delivering personalization, improving account holder journeys, and enhancing operational efficiency. CMOs can take inspiration from these successful transformations to leverage AI effectively in their own marketing strategies.

*The Center for Generational Kinetics – National Research Study 2024, commissioned by Alkami, included 1,500 U.S. participants ages 22-65 weighted to the 2020 US Census for age, gender, region, and ethnicity. The survey was conducted online from January 12, 2024, to January 30, 2024

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