Analytics has become an important part of every core function around us. Banks and financial institutions are also understanding the immense value that data driven insights bring in. With much of the data revolving around customer behaviour, analytics gives us key insights into understanding our target audience better. As a result, banks and insurance companies can improve their product offering, enhance customer loyalty, dish out relevant up-sell and cross-sell offerings, reinvent customer retention schemes, screen applications, simplify documentation, put a check on fraud detection and so much more.
Going a step ahead, predictive analytics helps banks and insurance companies to analyse current data and predict future outcomes. Having better control over future planning is definitely of significant value.
A good data analytics software, augmented by interactive visualisations, can help you tell a cohesive story from extracted insights.
Let’s understand how predictive analytics is revolutionising the banking sector:
1. Fraud Detection
Fraud is a huge and growing concern for the banking and financial industry. Digitisation has led to more increase in the number of bank-related cyber crimes taking place. This puts customer identity at risk as well as adds to the cost for banks and insurance companies. Financial institutions are increasingly using advanced algorithms and big data tools to reduce the number of frauds. By studying existing fraud patterns and customer behaviour, banks are using predictive analytics to detect possible frauds and take preventive action to stop them from taking place.
2. Customer Engagement
Collecting data for banks and financial institutions is a great way to encash on it with optimized targeting. Based on predictive analytics, banks and insurance companies can map out hot targets and potential customer segments. This enhances the customer acquisition rate to about 10% when backed with data insights. Also, with analytics banks can reshape their customer retention strategy by defining loyalty methods well in advance. Analytics also provides reports on customer churn patterns which helps financial institutions to identify the gaps. Customer Loyalty is a growing challenge. While new customers are always the focus, how to retain old customers is also equally important. Using predictive analysis, banks can identify which customers are willing to switch to any other bank and the reason behind their decision. It further examines customer’s spending and behavior patterns to predict the next step.
3. Customer Targeting
Once you know the buying patterns of your customers you know which product to take to them or what to sell. Analytical dashboards provide banks and financial institutions with this critical insight. By analyzing every customer profile, they can run targeting messaging campaigns resulting in a higher response rate. You know what your customer is expecting next and if you succeed in meeting his expectation, you have won yourself a client! This further enables banks to conduct effective cross-selling of products, which leads to more profitability and longer customer relationships. With predictive analytics, you know when to make your next sales move to your existing customers.
4. Collections Management
Banks are in the business of lending money and hence, collections becomes another important area of concern. Maintaining records of all the customers who owe you money to segment those who pay on time and those who default is a strenuous exercise. With analytics banks can get a better control on the portfolio risk and find out in advance which customers can cause more risk with collections. Banks can be prepared to take action in the right time and improve the productivity of their collections function.
5. Cash Liquidity Planning
Banks have their branches and ATMs spread across different areas. Both branches and ATMs need to have enough cash liquidity to service the customer base using it. Predictive analytics can help banks in tracking the patterns of the in-and-out payments happening at branches and ATMs and draw up a dashboard for banks to understand how to distribute their liquidity. Optimal planning of liquid assets ensures banks and financial institutions have a better control on future demand.
6. Targeted Marketing
With predictive analytics, banks and financial institutions can plan their marketing campaigns with more precision. Analytics provides critical insights into customer behaviour giving banks and financial institutions the complete trend of customer’s banking patterns. Banks can use this data store to time their messaging to their customers by offering them suitable plans, offers, schemes and programs.
7. Feedback Analysis
Feedback management makes a great base for analytical procedures especially in the banking domain.Banks and insurance companies gain a lot of momentum with the kind of customer relationships they are able to maintain. Customers expect their banks to care for their needs. Here is where predictive analytics can be of great use. By collecting customer feedback, banks are in a better position to fine tune their financial offerings in line with customer expectations. This proactive approach is a good way to help your banking business grow. Feedback management makes a great base for analytical procedures especially in the banking industry.
8. Customer Value
How to retain customers for a long time? This is often a challenge for banks and insurance companies. Predictive analytics helps banks to improve customer’s lifetime value. Focusing on best customers and improving service to potential clients can be done effortlessly by gathering the right customer data. By analyzing past customer trends, banks can map out what worked with their customers and accordingly churn out new customer engagement efforts. By evaluating customer response over the years, banks can zero down on factors essential to enhance customer lifetime value.
With a data-driven tool or software, banks and insurance companies can greatly leverage their data assets to redefine their customer engagement not just in the present, but also scope out their future plan of action.
