Customer Segmentation at Banks with ML & AI

As we accelerate into a digital world, the understanding of customers’ banking patterns online and segmenting them based on their preferences to predict and serve them banking services has become a top priority for banks worldwide. Aspire Systems specializes in Artificial Intelligence and Machine Learning techniques for banks to provide superior customer experiences.

Vital Role of Customer Segmentation at Banks

Customers are diverse in nature and require personalized services from banks, on the other hand, banks need to shift from a traditional mindset and accept the new kinds of customer preferences. No customer is obviously the same. A few attributes about one customer can match with another customer thereby helping banks better serve the segment of customers by predicting their wants and needs well in advance. Banks need to tap into the potential of understanding customers’ data by segmentation using artificial intelligence and machine learning techniques. Segmenting customers’ data helps banks personalize customer experiences while enhancing and defining products making them quickly adapt to customer needs, habits and interests.

The Reality of Customers’ Data Classification at Banks

While segmenting customers around character patterns, it highlights the fact that traditional classifications are becoming increasingly irrelevant and agrees to the claim of banks not knowing their customers well enough. Instead, banks need to identify their top 5 most distinct character patterns that receive 360 degree perspectives on customers and thereby predicting their customers’ needs.

According to EY’s ‘How well do you know Your Customers?’ Report, basic segmentation prevailing at banks is not enough. Banks fail to have an in depth understanding of the customers because they are often categorized on traditional parameters instead of life stages, lifestyle, behaviors and attitudes.

Hassle of tracking that one customer’s multiple relationships with the bank

Low product penetration and customer churn rates

Insufficient data collected for useful insights

What is Customer Segmentation?

Customer segmentation reveals specific intelligence for banks to understand customers on a deeper level. To deliver the services customers are expecting, segmenting customers by their level of digital sophistication and financial acumen can helps banks stay on a competitive edge. When applied in combination with other segmental analyses, these insights open up subtler and more sophisticated ways to approach customers as their shift to digital accelerates.

Common customer segmentation attributes can include

Income generated by Customers - The past, current and the predicted future of a customer’s purchase along with the revenue generated by the bank
Demographics – This information about the customer will include age, geography, gender, generation, income level and marital status
Stages of Life – Focused primarily on various milestones achieved by the customer during journey with the bank – for example – graduating college or retirement
Attitude – Customers’ opinions on the banking industry, online and mobile banking, and their satisfaction with the bank
Behavior – Interactions between customers and banks, the channels and the frequency of their usage, and which products they adopt

How can Customer Segmentation help at Banks?

Discover critical data points for customer segmentation

Identifying key data points that can give insights to segment customers is a powerful exercise. Data points can be as simple as age, gender to something highly evolved as lifestyle patterns and interests

Profile new customers into user specific segments

When a new customer signs up with your bank, they automatically belong to a segment that has already been defined based on various data connections.

Support constant learning about each customer

Whether a customer has a loan account or a savings account, constant learning about them can help your bank understand and identify their relationships across all banking services and maintain a one true version of the customer.

Real time monitoring and reallocation of segments

A customer action’s needs to be constantly monitored for change in interests and needs. Movement of the customers profile to the new segment can be made seamless with continuous observation.

Benefits of Customer Segmentation at Banks

Establish one master version for each customer

Predict next best action for each customer

Profile new customers as soon as they sign up

Achieve smarter cross sell and up sell of products

About Aspire Systems

Aspire Systems serves top banking and financial services industry clients worldwide. The company’s AI & ML Practice supports services around Customer Intelligence, RPA and Machine Learning. With over 2750 employees, Aspire Systems aims to stay ahead when it comes to providing cognitive technologies for banks.