Harnessing Artificial Intelligence in Banking to Boost Marketing ROI
The integration of humans and artificial intelligence (AI) in banking is proving essential for maximizing AI’s return on investment (ROI). At an Alkami Co:lab 2024 session, Nate Shahan, vice president, product management and Joan Clark, director, product management from Alkami shared key insights into the marriage of AI with human intelligence, showing the profound impact of data analytics in banking on marketing strategies.
AI and Collaborative Intelligence: A Strategic Imperative
The session titled “Humans and AI: How to Maximize Marketing ROI,” delved into the concept of collaborative intelligence, where AI complements human skills with its automation, speed, scalability, and quantitative capabilities. This blend is crucial for enhancing data-driven marketing strategies, particularly in leveraging artificial intelligence and data analytics in banking to improve marketing precision and efficiency.
Artificial Intelligence in Banking as a Strategic Ally
AI and data analytics in banking emerge as crucial tools in addressing silent attrition, with its success hinging on the quality of underlying data. AI can provide insights into account holder behaviors, predict disengagement, and help target outreach to re-engage individuals. However, the implementation of AI must be approached with diligence, ensuring data accuracy and system integration. Moreover, striking a balance between digital innovation and human interaction is essential; personalized, AI-driven engagements must complement, not replace, the personalized touch that fosters deep connections with account holders.
In the banking world, blending AI with human intelligence is imperative because of the sensitivity of the decisions made by financial institutions (FIs). FIs help their account holders maintain and grow their wealth, necessitating decisions and engagements that incorporate empathy and emotional intelligence – qualities that AI alone cannot deliver. This is why Alkami is uniquely built for regional community banks and credit unions, ensuring that human oversight and AI work together to provide the best possible outcomes.
Leveraging AI and Data Analytics in Banking
Alkami utilizes a variety of AI approaches, such as machine learning models including predictive and classification models. These technologies play a pivotal role in creating accurate account holder profiles, predicting future banking needs, and personalizing marketing efforts to cater to individual preferences. For example, Alkami’s use of insights derived from transaction data enables financial institutions to target their marketing efforts more effectively by deeply understanding account holder behaviors and preferences.
Predictive Model: Predicts future outcomes based on past data patterns. An example is the next best offer from Alkami Data & Marketing.
Classification Model: Sorts data into different classes. An example is a tag derived from transaction data that describes account holders’ financial behaviors.
Real-World Impact of AI on Marketing Outcomes
The tangible benefits of integrating AI into marketing were highlighted with real-world success stories from Capital Credit Union. In a 60-day period, Capital Credit Union deployed a certificate of deposit (CD) cross-sell strategy that delivered two campaigns. The first, a human generated campaign and the second an AI generated campaign.
The human-generated selection focused on traditional financial metrics like business spending and investment portfolios, achieving $11.2 million in conversions. The AI-generated selection, which emphasized trends in deposits and competitive savings options, generated $32.3 million in conversions.
Overall, the two campaigns realized a combined total of $43.5 million in conversions, showcasing the impact AI can have on refining marketing strategies and driving substantial financial growth. This success not only highlights the potential of AI in enhancing cross-sell opportunities but also sets a benchmark for integrating technology into financial marketing strategies.
Hear more from Rachel O’Neill, Principal Solutions Engineer, Alkami, and Will Johnston, Marketing Analyst, Capital Credit Union.
AI as a Tool for Deepening Account Holder Insights
The session also highlighted how AI can extend beyond just marketing to provide a comprehensive view of account holder interactions and preferences. Alkami aids institutions with data analytics in banking to segment their account holders more effectively, thereby tailoring their offerings to meet the unique needs of different groups. This strategy not only improves satisfaction but also boosts overall marketing ROI by ensuring that the right products are offered to the right people at the right time.
Enhancing Operational Efficiency and Strategic Decision-Making
Artificial intelligence in banking isn’t limited to interacting with account holders; it also enhances operational efficiency and strategic decision-making. By automating routine data analyses and providing insights into trends and behaviors, you can save time and allocate teams and resources to more complex and strategic tasks. This shift not only optimizes operational costs but also enhances the strategic capabilities of financial institutions.
Future-Proofing Banking with AI and Collaborative Intelligence
Looking forward, the integration of AI and data analytics into marketing strategies represents what will become a pivotal transformation in how financial institutions interact with and serve their account holders. AI and data analytics in banking are crucial for the development of more personalized, responsive, and efficient services that meet the increasingly complex demands of today’s account holders. Embracing AI in conjunction with human intelligence is not just a trend but a forward-looking approach that cutting edge financial institutions are already adopting.
Is your financial institution ready to take advantage of AI predictive models?