Artificial Intelligence (AI) has made significant waves in the banking industry. It has impacted all facets of banking making it more efficient, secure, and personalized. As banking gets more competitive, creating personalized experiences has never been more important.
By leveraging the power of AI systems, banks can create highly personalized offers that perfectly resonate with their customers’ needs and preferences. This helps not only to bring in more customers but also to retain them and foster loyalty. This post will dive into the transformative potential of AI to personalize banking offers, exploring the benefits, and the concerns associated with utilizing AI for banking offers.
To begin, here is why personalization in banking offers matters.
Why personalization in banking offers matters
In an industry with low entry restrictions on new banks and easy exit conditions for unprofitable banking institutions, banks are pressured to behave competitively [1]. This stems from state and global policies that promote healthy competition between banks to improve the economy and the rise of fintech companies alongside retail and corporate banks [2].
Source: Intelligent HQ
With banking getting more competitive, there is a severe need for banks to retain customers and have as many long-term customers as possible. This means that personalized offerings are no longer a luxury, especially for banks that want to ensure longevity.
According to research, 70% of customers prefer personalized banking offers [3]. Customers value tailored experiences from their financial institutions. Why is that?
Personalized offers cater to customers’ specific needs, preferences, and spending habits. These offers cut right through the marketing noise directly to the customers who might need them. For instance, investment opportunities like retirement planning offers will only be shown to working members of the older demographic (middle-aged or senior citizens), not the youth. Customers are more likely to engage with personalized offers [4] and become loyal to banks that have these types of offers. This increases the profitability of banks in the long term.
Source: Investopedia
Despite a strong customer preference for personalized banking offers, only 14% of banks have embraced it. This shows that there is a significant gap between customer expectations and the services currently being offered. Fortunately, AI systems can play a crucial role in bridging this gap.
How AI enhances personalization in banking offers
The use of AI in banking services is nothing new. This powerful technology is already being utilized to:
Create adaptive security systems to prevent fraud.
Enhance operational efficiency and risk management solutions like loan underwriting and algorithmic trading.
Automate KYC (Know Your Customer) and other compliance services.
That aside, personalization of banking offers stands a chance to benefit the most from AI since it equips banks with an extensive understanding of their customers. Here is an overview of how it does it.
Background: Leveraging AI models in personalizing bank offers
Banks and other financial institutions have an edge when it comes to taking advantage of AI. This is because AI needs lots of data, and banks have lots of it [5]. Banks collect and manage a wide range of data, including but not limited to:
Personal customer information (retail banks) – Names, addresses, contact information, employment and income details, etc.
Business information (corporate banks) – Financial reports, financial projections, etc.
Account information – Transaction history, balances, and account preferences.
Other information – Credit bureau reports, industry trends, tax filings, etc.
AI enables banks to take full advantage of the data they collect to provide highly personalized offers for their customers. The new generation of AI models (multimodal generative AI models) can expertly process data in various formats including text, image, and audio, and combine them to gain a comprehensive understanding of customers [6].
Benefits of Multimodal AI technologies: Source: Daffodil
That’s not all, they can also understand the context behind data that banks have on customers’ financial status, spending habits, creditworthiness, and so on. As a result, they can generate relevant recommendations that are highly specific to different customers.
The bottom line is that AI helps to comprehensively analyze large amounts of data collected and managed by banks – useful in generating personalized offers. Studies show that this can increase engagement by 53% [7].
Ways AI helps to personalize banking offers
The adoption of AI systems can help personalize product recommendations through targeted product offerings recommendations such as the following.
Special credit card offers
AI systems can perform advanced analytics on vast amounts of customer data, including specific spending habits, credit scores, transaction history, and online behavior. These systems can combine this data to suggest credit card offers that align with a customer’s preferences or financial goals.
Take a customer who travels regularly at specific times of the week or month and spends a significant portion of their income on plane tickets. The bank can leverage AI systems to analyze the customer’s transaction history and identify their spending patterns. Using this information, the bank can recommend credit card offers cashback or rewards specifically for plane ticket purchases. The customers will likely take up this offer and the bank can earn revenue via interest and other credit card fees.
Personalized customer service solutions
AI systems analyzing customer data also help banks to segment their customers based on their needs. They can then use this information to provide personalized customer service to different customer groups.
Personalization solutions for banks Powered by AI | Source: Emerline
For instance, banks that work with corporations can use AI systems to classify their clientele based on metrics like size, financial profile, relationship level, and risk profile. When these clients reach out for guidance, they can be automatically forwarded to customer service personnel who deal with their specific issues.
Personalized predictive analysis services
Some banks, especially those dealing with corporate clients, provide clients access to industry reports and market analyses that can be used to inform business forecasting. However, these reports are typically not tailored to a company’s specific situation.
By investing in AI and machine learning technologies, banks can provide customers with in-house forecasting solutions tailored to their company’s specific needs. AI has the power to combine enterprise and market trends data to make accurate predictions for specific enterprises.
Dynamic account offers
Different customers tend to have different financial goals. Banks can leverage AI to analyze customer’s data and identify customers’ specific financial goals. The new AI models have natural language processing capabilities, allowing them to analyze customer interactions via email, chatbots (available in mobile banking apps), and surveys.
After identifying the financial goals of specific customers, dynamically show them account offers depending on these goals. For instance, recommending high-yield savings accounts when customers have a windfall (a large sum received or won unexpectedly).
Overall, AI technologies enable banks to leverage customer data to understand their needs, preferences, and financial goals better. With this information, they can create personalized offers that suit their customers individually.
Concerns: Innovating with AI transparently
AI algorithms are quite complex and customers will likely not understand how their data is used as they receive specific offers. This is why it is important to be transparent, communicate clearly what their data will be used for, and ask for their consent. Even when AI is used to automate these processes, human oversight and accountability is essential. This helps to set up and maintain ethical frameworks that ensure AI is used responsibly in its implementation to create personalized offers.
Conclusion
There is a growing need for banks to retain as many customers as possible to stay afloat in the cut-throat banking industry. Crafting personalized experiences is a proven way for banks to keep customers engaging with their business. AI enables banks to utilize the full potential of the data they collect to create highly personalized offers for their customers. Banks utilizing AI to create personalized experiences should consider transparency and accountability to ensure AI technologies are used responsibly.