How can Banks Leverage an AI-based Deposit Growth Engine

Deposit growth has become a priority for top-tier banks in the face of a challenging economy. The sharp increase in inflation and the collapse of the Silicon Valley Bank caused a downturn in deposit growth in 2023. With numerous high-yielding alternatives available, checking accounts became less attractive and less stable for depositors.

As a result, the 2024 BAI Banking Outlook survey found that banks have shifted their focus to acquiring new customers, retaining the existing base, and providing superior digital experience. However, some banks have increased interest rates to attract new depositors, they are prepared to incur the high cost of retaining existing deposits.

The Need to Prioritize Deposit Growth 

Deposit growth has become a significant concern for banks. In a recent survey, 80% of bankers considered deposit growth and retention as a top priority. This underscores the urgent need for banks to optimize their deposit management processes with advanced technologies like artificial intelligence (AI).

According to the BAI forecast, deposit growth in 2024 is expected to decline by 2.4%. While acquiring new deposits can be a challenge, advancements in AI can allow financial institutions to drive deposit growth without paying exorbitant interest rates.

How AI-based Deposit Growth Engines Support Financial Institutions 

AI serves as a vital catalyst for deposit growth, transforming the way it is managed. With advanced algorithms, AI systems can quickly and accurately identify trends and patterns in deposit transactions, detect potential issues, and ensure regulatory compliance. Having an AI-based growth engine for deposits can help enhance customer acquisition, retention, and overall deposit growth.

Data Collection and Integration: Banks can significantly benefit from data collection. AI capabilities can help banks gather customer data from multiple interactions, transactions, and feedback to obtain a detailed understanding of the customer. The engine can integrate external data such as economic indicators, market trends, and competitor analysis to contextualize deposit strategies. Banks can analyze behavioral patterns, preferences, and needs to tailor deposit growth strategies that align with customer expectations.

Advanced Analytics: By leveraging machine learning algorithms, banks can segment customers based on their behavior, demographics, and potential value. The engine, with the help of AI, can develop models to predict customer behavior, such as the likelihood of opening new accounts, switching banks, or making additional deposits. AI can assess and mitigate risks related to deposits, such as fraud detection and credit risk evaluation. 

Personalized Marketing: Based on the customer segment and predictive models, banks can develop targeted campaigns. They can personalize content at an individual level and improve offers sent to customers through emails, mobile apps, and other digital channels. Having an AI-driven A/B testing feature can enable banks to optimize marketing messages and strategies. 

Customer Experience Optimization:  According to a McKinsey survey of U.S. retail banking customers, banks with the highest level of customer satisfaction experienced deposit growth that was 84% faster than those with low satisfaction ratings. AI-based growth engines can improve customer experience through various features. By deploying AI-powered chatbots, banks can offer instant support to customers. Additionally, AI capabilities can recommend financial products and services tailored to individual customer needs. Leveraging natural language processing (NLP) allows banks to analyze customer feedback, identify areas of improvement, and respond in a proactive manner.

Another new area of exploration is combination of AI and Gen AI to create models from bank’s historical data and empower strategy officers to interact with data in natural language. Example asking AI on the target segment for a new savings account for high deposit balance customers with a probability of success. With AI focusing on responsibility and explainability while presenting results, it is a game changer for banks looking for deposit/loan growth.

Operational Efficiency: An AI-based growth deposit engine can enhance operational efficiency by automating routine tasks such as account opening, document classification, verification, data extraction and transaction processing through robotic processing automation (RPA). It can also improve security with real-time fraud detection systems, protecting customer deposits from fraudulent activities. Predictive maintenance powered by AI will help foresee and prevent system failures, ensuring seamless banking operations. 

Performance Monitoring and Optimization: Banks can track the success of their growth deposit initiatives and key performance indicators (KPIs) with real-time analytics. AI-driven tools can continuously identify patterns and insights from data, and enable banks to refine strategies and processes. Furthermore, they can analyze customer retention rates to develop strategies aimed at decreasing churn and enhancing customer loyalty. 

Implementation Considerations: Integrating AI into the system will help banks ensure data privacy and security by complying with regulatory requirements. The AI-powered engine is designed to be scalable and accommodate increasing data values and customer bases.  Furthermore, the engine can train the staff to effectively use AI tools and interpret their insights.

To Sum Up

An AI-based growth engine for deposits leverages data analytics, machine learning, and automation to enhance customer acquisition, retention, and overall deposit growth. By personalizing customer experiences, optimizing marketing efforts, and improving operational efficiency, banks can achieve sustainable growth and realistic benefits by using AI for deposits.