Analytics In Customer Life Cycle Management
So now the account has been sourced and the bank has a new customer
. What happens next varies depending on the type of product/ service. But there are a certain things that may happen irrespective of all that. For example- the account may churn out after a limited time thereby denying the bank precious revenues and a relationship, the account may go delinquent on its payments resulting in losses for the bank. There are also many hidden opportunities that the bank has no way to figure out, for example ""potential cross sell/ up sell opportunities- it might happen that the same guy needs some other banking services and competition"s marketing tapped into it before our bank could. The bank was at an advantage of already having a relationship with the customer thereby enabling them an access to precious information about him. All these opportunities directly result in revenue leaks and direct losses, and analytics can help fix these.
Churn Reduction
To go through all the above discussed cases one by one and how analytics could save the day, we start with Churn Reduction. With the help of predictive analytics on relationship data and profile information, we can develop churn prediction models to help identify customers with high possibility to churn in the near future. We can then treat them to segment specific retention programs and contain churn. This information can also be used to develop lifetime value prediction models which can be clubbed with churn prediction models to identify potential high revenue customers who have high propensity to churn. They can be exposed to targeted programs to earn loyalty and maximize lifetime revenues.
These are just some examples of smart usage of analytics in the banking operations. New ideas are emerging everyday on how to best leverage analytics at each and every node of business process flow and a discussion of this broad nature can never cover everything. The objective is to give an idea of the applicability (and necessity!) of data mining and analytics in the day to day operations of a bank.
Collection and Recovery
Moving on, we come to delinquency management aspect of credit risk management. Delinquency prediction scorecards are pretty standard in the banking industry now. Such model scorecards help in identification of potential delinquent accounts and that enables the delinquency management teams to timely treat these accounts with appropriate collection strategies to minimize delinquencies and to use collection resources optimally. A new advancement in this area has been to help identify the reasons behind a delinquency. To explain- a delinquency might be because of many reasons- intentional, habitual or genuine problem among many other things. Analytics and data mining are being used to segregate these groups and to treat them differently. For example, an intentional fraud customer (should ideally be identified at the time of application itself) should be exposed to the most severe collection treatments as soon as possible and the credit exposure should be minimized. While a genuine delinquency customer (lost a job, hit by recession etc.) wants to make the payment but is unable to. This customer needs to be treated differently- probably given comfortable payment options; he will bounce back and be a good and loyal customer again. By using analytics and data mining on historical collection data, banks also fine tune treatment strategies, for example "" which segment should be exposed to what treatments (message/ calls/ personal visits etc.), and with what intensities / at what time of the payment cycle etc..
Analytics also comes handy in the non performing assets (NPA) management/ recovery processes. By leveraging historical data and decisioning tools, banks can identify "juicy" pieces from their NPA portfolio and maximize recoveries and ROI on recovery budgets.
Cross selling
Now, coming on to cross sell and up sell opportunities. In today"s tough business environment, acquiring a new customer is way more difficult (read costly) than selling to an existing customer. And given that you already have a relationship with the guy, you have access to a lot of information about him that your competition doesn"t, and this gives you a clear cut advantage. Analytics helps banks tap into this opportunity and make the best of an existing relationship. Banks use cross-sell models to sell their products to their other portfolios, and to up sell their higher range products to existing customers. Analytics helps them identify who among their existing customers are most likely to buy a different service- based on customer profile, preference and service features. This way you don"t need to market your service to the entire universe, but only to those who are most likely to buy. This helps in "" marketing ROI maximization, enhancing customer loyalty and unleashing the full potential of a relationship.
Also, a lot of banking is now real time just "" "a swipe of card", "a click of button" based allowing no time to the bank for judicious decisions ""whether to authorize the transaction or mark as risky/ fraudulent and stop it. Analytics helps institutions to develop tools to assess transactions in real time and take a call on whether the transaction is fraudulent or not. This comes under Fraud Risk Management function of the bank.
With this, we come to the end of application of analytics in the consumer banking industry- the first part of this series. We have broadly tried to touch upon most of the important dimensions of tactical and strategic decision making process and how analytics is being used to gain a competitive advantage. As we said earlier, this is not all, in fact far from it. But it gives you just a fair amount of idea on how analytics is shaping the way business is run in today"s world. And how it continues to evolve every day. And with high emphasis on "focus on the core business" and let the specialists do the rest, it only makes sense that more and more businesses will look out for outsourcing tasks from their data analytics and data mining functions.
Hope you liked it. Do post feedback/ comments/ questions.
Stay tuned for more!
by: Gmid Associates
Services Of The Best Dedicated Hosting Providers Convenience Of Cargo Services In India For Freight Transportation Quality Of Commercial Electrician Services Matters The Most Employ The Appropriate Rubbish Removal Services For You! Choose The Right Psd To Html Service Provider Giving A Finished Look To Exteriors With Good Painting Services Services For Landlords How Do It Consulting Services Benefit A Company? Why To Consider Outsource Call Center Services? Commercial Cleaning Services That In Reality Perform Emergency Plumbing Service: Important To Handle Urgent Plumbing Requirements All About Dumpster Rental Services How To Find A Cleaning Service In In Brisbane