How Predictive Analytics can help banking institutions

In today’s competitive world, growing customer base and satisfying them is considered the most challenging task. They demand on being treated as individuals and not as a general lot. To get over this, banks have been implementing various tools over time. But important issues like ensuring long-term loyalty from high-valued customers, retaining and attracting different types of customers or cross-selling of which products exactly to whom, fraud detection, application screening, credit and collections has always been an area of concern. Predictive Analytics comes into the picture here. It helps banks to fetch the relevant data of customers, identify fraudulent activities, helps in application screening, capture relationships between predicted and explanatory variables from past happenings and uses it to predict future outcomes.

But in order to discover the set of critical success factors that will help banks reach their strategic goals, they need to move beyond standard business reporting and sales forecasting. By applying data mining and predictive analytics to extract actionable intelligent insights and quantifiable predictions, banks can gain insights that encompass all types of customer behavior, including channel transactions, account opening and closing, default, fraud and customer departure.

Here are the  ways in which predictive analytics is helping the banking sector.

  1. Through Analytics one can recognize unobvious frauds and then to analyze it further predictive analytics is used.  

2.Through predictive analysis one can help across huge volumes of applications, without  excluding important variables, without delays or errors, without growing tired- all of it with regularity and steadiness in banking sector and its results are very much authentic and accurate to be used.

3.Through Predictive analytics it is easier for banks to instantly identify the customer base can further expand by acquiring the right type of customer and also helped in the process for optimized targeting.

4.Predictive analytics helps examine customers’ usage, spending, and other behavior and leads to effective cross-selling of the right product at the right time.


5.Banks can track the past usage patterns and the daily coordination between the in- and out- payments at their branches and ATM’s , through predictive analytics , hence predicting the future needs of their potential customers .

6. By providing an insight into customer behavior and attitudes, and a complete, current view of your customers, analytics help marketers to plan marketing campaigns and programs and monitor the results closely. Also it will help your marketing team deliver the right message at the right time to the right customers.

Banks are realizing the importance of analytics and data-savvy competitors like Amazon and American Express are sure to push banks to get better at customer analytics, it’s just a matter of time.

We at Daphnis Labs are currently working on exciting Predictive Analytics Products for Financial Institutions, Interested in harnessing Data Analytics for your firm, please drop in a mail or ping us on Skype.


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