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If you work for financial institutions and your day-to-day tasks revolve around customer engagement or improving customer experience, the last few years would’ve been interesting- to say the least.

Evolving customer expectations and the emerging possibilities of leveraging technologies such as Artificial Intelligence (AI) and Machine Learning (ML) can overwhelm you while opening doors to the scope of AI in retail banking, corporate banking, and investment banking. Read on to see everyday artificial intelligence applications to improve operational efficiency, decision-making, and customer service.

How Can Artificial Intelligence Improve Customer Engagement in Banking?

On paper, the endless possibilities of AI excite banking professionals. But in reality, banks are hesitant to be early adopters of AI. This ‘waiting game’ can heavily cost financial institutions competitive advantage and customer loyalty. Today’s customers expect banks to be proactive and deliver personalized services.

Research also suggests that customers will likely end their business with your brand if you don’t meet their expectations.

Here are four ways in which AI can improve customer engagement:

1. Increase ROI from upsell and cross-sell campaigns 
2. Reduce acquisition costs and drive more revenue from existing customers
3. Optimize conversion rates with better experimentation frameworks
4. Analyze data quickly and improve decision-making without investing in third-party agencies or experts.

Technological Pre-Requisites for the Banking and Financial Sector to Improve Customer Engagement

AI technologies can help banks immensely with data analysis, automate repetitive tasks, improve customer services and decision-making processes, help financial service brands stay on top of market trends, and simplify seemingly complex tasks.

However, AI is not a magical bullet. While its potential is infinite, much of its ROI depends on data quality, cohesiveness, and completeness.

Before considering how AI systems can transform how you engage with new and existing customers, you must consider your organization’s data collection, storage, and management protocol.

Current Scope of AI Technologies in Banking Services

Artificial intelligence brings a myriad of possibilities to the banking and finance sector. Financial brands can build AI models to improve engagement across all customer life cycle stages- customer acquisition, onboarding, first-time conversion, retention, and loyalty.

AI can help financial institutions predict overall market trends and conduct predictive analytics to uncover hidden patterns in customer behavior. These insights can significantly improve client engagement.

Machine learning techniques can also help companies in the banking sector responsibly extract insights from unstructured data. AI models can help financial service companies analyze large data sets more accurately to make loan and credit decisions based on customer behavior patterns.

Generative AI technologies can help financial service brands create innovative and compelling campaigns that simplify complex financial industry concepts like investment research, wealth management, cyber-attacks, and ways to improve credit scoring.

Together, predictive AI and generative AI can help send the right message to the right customer at the right time, helping your banking brand analyze vast amounts of customer data, automate processes, and improve efficiency and brand-customer interactions across touchpoints.

For your brand to get the best out of AI, your banking brand needs to understand the fundamentals of customer engagement and retention. What you will be reading through the rest of the blog will give you a detailed rundown of how to execute a particular use-case using the fundamentals of customer engagement and personalization while also giving you information on utilizing AI capabilities to create superior experiences for your banking customers.

Everyday Use-cases to Leverage AI and ML in the Banking Sector

Financial service brands spend thousands of dollars monthly to acquire customers through avenues like paid marketing, community engagement, referrals, App Store Optimization (ASO), etc, to download the banking app or open a bank account on the website.

However, all these avenues do only a fraction of the ‘customer acquisition’ because most digital customer journeys are disjointed and fragmented, creating friction that negatively impacts the customer journey.

Goal: Optimize the Customer Onboarding Process

Right from acquisition, every step of the customer journey needs to be carefully designed with a clear end goal. You risk losing new customers to competition if the ‘next steps’ are vague or confusing, product information is missing, and the call to action is unclear. Additionally, if you are engaging with customers outside their preferred channels, expect low engagement rates and increased churn risk to add to the operational costs.

While this is part of the problem, financial service providers struggle to derive meaningful insights from sources, including internal data sources (call centers, kiosks, bank branches, etc.), online channels, and data management platform partners to optimize the customer journey.

Potential obstacles in your way:

• Customers lack clarity about the next steps,
• Fragmented CX,
• High drop-off rates,
• Zero-visibility into friction points across the onboarding journey

Solution:

1. Set up and automate omnichannel onboarding flows
2. Analyze campaign performance of flows to understand points of friction, conversions, etc
3. Run multivariate tests to discover the best-performing variant of the onboarding flow

How to supercharge customer onboarding with AI?

1. Leverage AI to create micro-segments based on actions performed by newly registered customers. E.g., ‘Haven’t opened the app in 7 days’, ‘Dropped off before the first transaction in last 24 hours’, etc.
2. Connect with your customer on their preferred channel rather than bombarding them with messages on every channel using predictive AI.
3. Communicate with your customers when they are most receptive using predictive AI.
4. Optimize messaging and content based on insights from past interactions or transactions with your bank with generative AI.

Goal: Provide Personalized Customer Experience to Anonymous and Returning Website Visitors

While mobile banking is on the rise globally, there is still an audience for Internet banking, especially in the current banking ecosystem where web-based and mobile banking are both in demand, and most brands want to strengthen both mobile and website banking to offer truly omnichannel experiences to customers.

However, most financial service brands struggle to provide personalized web experiences to anonymous visitors and registered customers.

Potential obstacles in your way:

• Dependency on website developers and/or tech team to make changes to the webpage
• Dependency on the design team to personalize website banners
• Increase in go-live timelines resulting in slower execution of website personalization

Solution:

1. Leveraging in-session attributes and behavior can personalize the home page for a first-time visitor even when no data is available or a user profile has been created. Some attributes that can be used include query parameters, geolocation, time of day, day of the week, OS type, platform used, etc.
2. With time, you can create customized campaigns based on traffic sources and pages viewed. For example, if a visitor clicks on an Instagram ad about credit card offers, you can show the same offer on your website homepage.
3. Your customer engagement platform must offer website personalization capabilities that include server-side and client-side personalization for greater flexibility in personalization and experimentation.

How to supercharge website personalization with AI?

• Optimize and personalize website copy and graphics based on location/ language and in-session behavior using Generative AI solutions.
• Leverage Sherpa AI to create the right customer segments.
• Build AI-generated product/ service recommendations to boost product/ service upsells.
  

Goal: Drive App Adoption/ Promote Educational Content

By the time a customer has completed onboarding, you’d have invested a significant amount of dollars and man-hours in acquiring and guiding them through the onboarding process. Ensuring that your customers understand how to navigate the app and access products/ services offered by your bank is critical for customer retention.

Create omnichannel flows to educate your newly onboarded customer on wealth management, the bank’s processes, and the portfolio of financial products highly relevant for each customer.

Potential Obstacles in your way:

• Customers haven’t gotten back into the app after completing onboarding.
• There is insufficient data about friction points in the onboarding process.
• No clear roadmap is explained to the customers about navigating the app.
• The customers are overwhelmed with too much information regarding the app.

Solution:

1. Create a series of ‘help guides’ using in-app messages that prompt helpful pop-ups to appear as the customer navigates the app. These pop-up messages must proactively address potential friction points in the customer journey.
2. Provide customers with options to personalize their app experience, such as updating their profile information, choosing the time and channel to receive communications, or changing the app display colors to suit their preferences.
3. Reward good behavior with gamification elements such as progress bars, badges, or levels to build positive customer habits.
4. Provide personalized coupons and discounts to boost first conversions.

How to supercharge app adoption with AI?

1. Leverage Generative AI to create campaign copies for app adoption wherein you can calibrate the tone and writing style to maximize engagement rate and app adoption.
2. Generative AI can be used to build micro-segments of customers based on their app activity post-onboarding. This level of granular segmentation can drive better personalization.

Goal: Build Personalized Customer Journeys Across the Customer Lifecycle

Every action and inaction from your customer’s end adds more details and updates your customer database in real time. These details help your brand create consistent and personalized customer experiences across channels and devices, enhancing customer service, which improves business opportunities and revenue for financial institutions.

Potential Obstacles in Your Way:

1. Customer journey touchpoints across the website and app are inconsistent, generic, and irrelevant, increasing customer friction.
2. Increased friction on the website and app can result in customer drop-offs, leading to higher uninstalls, negative reviews on the app store, lower brand trust scores, etc.

Solution:

1. Personalize all digital touchpoints in real time using insights from in-session behavior, browsing behavior, and geolocation.

How to supercharge customer journey personalization with AI?

• Leverage Generative AI to create hyper-personalized campaigns. First, determine the desired outcome for all cohorts of customers. AI model will then determine the best action for each customer and deduce the best journey to get the best outcome.

Goal: Build a Recommendation Model/ Suggest the Next Best Offer (NBO)/ Next Best Product (NBP)

Most financial service brands find having a product recommendation model crucial to growing their revenue. Banks can boost their upsell/ cross-sell revenues by boosting product discoverability for relevant customers.

If an existing customer intends to explore financial products on your company’s website, you can welcome them with personalized product recommendations based on their previous interactions and preferences.

However, for new customers, you can dynamically personalize the website based on the customer’s browsing behavior and entry points. Further, you can guide customers through key features of your website, thereby educating and engaging the customer while they are exploring the company’s offerings.

Potential Obstacles in Your Way:

1. Lack of insights into customer behavior.
2. The recommendation engine needs to be built and optimized manually.
3. The customers might have received irrelevant and generic product recommendations.

Solution:

1. Build smart recommendations based on past interactions and product attributes like “high interest rates” or “5-year maturity.”

How to supercharge your recommendation model with AI?

• Leverage deep learning and recommend items that are frequently viewed together or are similar in product attributes (Eg, low-interest car loans, low-interest home loans, etc.)

Goal: Retarget and Reactivate Dormant Customers

Sometimes, your customers download your bank’s app and forget about all the tasks that can be done via the app. To address this, you can send regular reminders and updates via push notifications and emails, highlighting available services like bill payments, fund transfers, and account management, ensuring customers stay informed and engaged with digital banking capabilities.

Potential Obstacles In Your Way:

1. Customers don’t understand how to navigate the app.
2. Customers aren’t aware of all the app’s capabilities.

Solution:

1. Target customers based on the content consumed. For example, Retarget customers who started reading the blog but didn’t apply for a credit card. Highlight rewards and benefits to encourage customers to apply for Credit Cards.
2. Personalize the app page by providing them tailored recommendations based on their preferences and past browsing activity.
3. Segment customers using RFM (Recency, Frequency, Monetary) analysis and establish omnichannel flows that engage customers categorized as ‘dormant,’ ‘inactive,’ at risk of attrition,’ or ‘lost,’ aiming to move them into higher engagement and activity levels. 

Supercharge customer reactivation with AI:

• Leverage ML capabilities to identify the right customer audience, messaging, timing, and channel and optimize your retargeting campaigns
• Optimize messaging and content based on insights from past interactions or transactions with your bank with generative AI.

Conclusion:

The true differentiator for brands competing in the investment banking, retail banking, central banking, cooperative banking, or credit union industry is customer experience. Leveraging artificial intelligence helps companies in the banking sector humanize the banking experience while automating processes, speeding up campaign execution, and upholding high-quality experiences at all levels of the customer journey.