Customer Data Intelligence for BFSI Industry

Customer data is the lifeblood of the Banking, Financial Services, and Insurance (BFSI) industry. Decision-makers can make the right business decisions, only if they have access to the right data at the right time.

Any enterprise, irrespective of size, collects and stores customer and prospect data. The problem with storing large amounts of customer data over extended periods is that it becomes obsolete or decays quickly. Stale customer data can compromise the efficiency of banks, financial institutions, and insurance companies. 

Data Intelligence in BFSI

Data on its own is relatively useless. Customer data has meaning only when it is used to identify patterns and predict how a customer will behave in the future. In the BFSI sector, data is collected in large volumes through multiple channels like call logs, emails, websites, social media, and real-time market feeds. But to lend meaningful insight and support to processes, this data needs to be analyzed and reported using customer data intelligence. More and more BFSI players are starting to realize the significance of customer data intelligence to improve their overall service delivery and performance.

Customer data intelligence includes collecting, organizing, and analyzing large and varied sets of data to uncover useful insights. It helps reveal unknown correlations and market trends and dissect customer preferences for the institutions to make informed business decisions. The data is gathered through various sources, including social networks, sales records, videos, digital images, sensors, and others.

Before we discuss the applications of customer data intelligence in the BFSI industry, let us first learn about the different types of intelligence that banks and insurance companies collect about borrowers:

• Human Intelligence – Human sources are used to derive this intelligence. These sources may include an employee in the borrowing company or the borrower’s competitor. A sector analyst or another banker who has worked with the borrower in the past can also be a source.

• Technology Intelligence – Technology Intelligence goes beyond a simple Google search. Some companies offer an intelligence as a service. They collect information on the borrowers and identify the borrower as a high-risk individual based on various risk parameters.

• Raw Intelligence – When the information collected about the borrower is not supported by evidence and needs to be corroborated with the financial or other information available with the bank, it is known as raw intelligence.

• Actionable Intelligence – This is information that can be followed-up on. It is complete and accurate and is supported by substantial evidence. Strategic plans can be devised based on this information. Companies that provide customer data intelligence as a service, work with regulatory bodies and credit bureaus and can offer useful insights about the borrowers. 

Customer data intelligence is the key to enhanced customer lifecycle management. It paves the way for new sourcing mechanisms, better customer monitoring, and a smooth collection process. Customer data intelligence can be used to understand consumer behavior, for segmentation, and to develop the right product, service, or offer for the right customer. Following stringent fraud management methods and collection models can get in the way of maintaining a pleasant customer experience. With customer data intelligence, banks, financial institutions, and insurance companies can strike the perfect balance between the two. 

Some of the most common applications of customer data intelligence in the BFSI Industry are explained in detail below. 

Target Marketing

Understanding customers’ buying patterns can help banks and financial institutions determine which products to advertise and sell. Customer data intelligence provides them with this critical insight. It analyzes every customer profile so that banks and financial institutions can run targeted messaging campaigns and generate a higher response rate. When brands know what customers want next and if they can succeed in meeting these expectations, they can achieve effective cross-selling of products and services. This leads to increased profitability and prolonged customer relationships. With customer data intelligence, they know what to sell to an existing customer, and when to sell it.

Retaining Customers

While acquiring new customers is always the goal, retaining existing customers is equally important. Customer data intelligence identifies customer churn patterns and generates comprehensive reports. These reports can help banks, financial institutions, and insurance companies identify and fill in gaps. For instance, using customer data intelligence, they can identify which customers are looking to switch banks and what the reason is. They can then personalize and restructure their customer retention strategy, based on the customer’s spending and behavior patterns. If corrective measures are taken timely and effectively, attrition can be prevented.

Increasing Customer Loyalty and Engagement

Using customer data intelligence, BFSI players can analyze the customer’s transaction history and profile to identify buying patterns and offer personalized and differentiated products, services, and customer experiences. Customer engagement can be increased by delivering targeted and contextually appropriate offers through channels that the customer prefers. 

Customers are now using digital platforms to interact with banks and financial institutions. By using customer data intelligence to dissect the data collected from digital platforms such as social media, BFSI institutions can gauge a better understanding of customer pain points, preferences, and needs. They can then use these insights to enhance the quality of their products and services. Customer data intelligence is crucial not only to improve the customer experience but also to stay ahead of the ever-increasing competition. 

With the financial environment changing more drastically than ever, the BFSI Industry is continuously evolving. Banks, financial institutions, and insurance companies are doubling down on the use of technologies like customer data intelligence, artificial intelligence, and machine learning to power their core operations. It is no longer a novelty but a necessity, as banks and financial institutions need to be more agile and flexible to be able to meet the rising expectations of a growing base of customers who are digitally empowered and technology savvy.