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Solving the customer insight problem

Shridar Jayakumar, program director for Oracle Business Analytics, AP, feels understanding the cost of acquiring and maintaining a customer, associated risks, and customer lifecycle potential are key to identifying profitability.

November 04, 2014 | Shridar Jayakumar

Roughly 80% of customers in most large retail banks fail to turn a profit, but, in this era of increased regulation and tighter margins, financial institutions can no longer afford to tolerate this status quo, thus forcing them to focus on solving this increasingly perilous puzzle to achieve new levels of profitability.

Banks try to figure out the customers’ worth by endeavoring to achieve a ‘single view’ of each customer and their multiple relationships with the bank. They measure the current value of a customer relationship trying to understand the customers’ profitability, and most importantly how to optimize its potentials.

To gain a clearer, more comprehensive picture of the customers’ profitability, financial institutions are seeking to look above and beyond the monetary value of a relationship. This involves understanding on the cost of acquiring and maintaining a customer, the associated risks, as well as the customers’ lifecycle potentials. Herein, lies the major challenges that many financial institutions face to seek extensive insights on customers.

The Customer Insight Quandary

1. Data Gathering and Integration Complexity –To understand a customer’s entire relationship with a bank, bankers must deal with multiple banking platforms, systems, and other channels including social media. These disparate datasets lead to multiple versions of the “truth” and preclude a 360-degree customer view. Even when organizations bring all of their customer data together through complex integrations, it must be married in a way that is readily usable and transact-able.

2. No Common Language – Today’s financial firms, which have many lines of business and operate across numerous global regions, often lack a common lexicon across their organizations. The product definitions may not be standardized across geographic regions. For example, some firms...

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Categories:

Data & Analytics, Data Management, Risk & Performance

Keywords:Scotland, England, UK, Eurozone, Market Risk


Solving the customer insight problem

Shridar Jayakumar, program director for Oracle Business Analytics, AP, feels understanding the cost of acquiring and maintaining a customer, associated risks, and customer lifecycle potential are key to identifying profitability.

November 04, 2014 | Shridar Jayakumar

Roughly 80% of customers in most large retail banks fail to turn a profit, but, in this era of increased regulation and tighter margins, financial institutions can no longer afford to tolerate this status quo, thus forcing them to focus on solving this increasingly perilous puzzle to achieve new levels of profitability.

Banks try to figure out the customers’ worth by endeavoring to achieve a ‘single view’ of each customer and their multiple relationships with the bank. They measure the current value of a customer relationship trying to understand the customers’ profitability, and most importantly how to optimize its potentials.

To gain a clearer, more comprehensive picture of the customers’ profitability, financial institutions are seeking to look above and beyond the monetary value of a relationship. This involves understanding on the cost of acquiring and maintaining a customer, the associated risks, as well as the customers’ lifecycle potentials. Herein, lies the major challenges that many financial institutions face to seek extensive insights on customers.

The Customer Insight Quandary

1. Data Gathering and Integration Complexity –To understand a customer’s entire relationship with a bank, bankers must deal with multiple banking platforms, systems, and other channels including social media. These disparate datasets lead to multiple versions of the “truth” and preclude a 360-degree customer view. Even when organizations bring all of their customer data together through complex integrations, it must be married in a way that is readily usable and transact-able.

2. No Common Language – Today’s financial firms, which have many lines of business and operate across numerous global regions, often lack a common lexicon across their organizations. The product definitions may not be standardized across geographic regions. For example, some firms...

Please login to read the complete article. If you already have an account, you can login now or subscribe/register.

Categories:

Data & Analytics, Data Management, Risk & Performance

Keywords:Scotland, England, UK, Eurozone, Market Risk


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