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Data Management Key To Banking Analytics
Banks aren't doing enough to mine customer data in search of new sources of profit.
1 Min Read
As they recover from years of crisis mode, banks are discovering that they're behind in customer-focused, profit-optimized services. The February issue of our sister publication Bank Systems Technology shares some of the challenges and opportunities banks face in normalizing their data and phasing in advanced analytics.
Associate editor Jon Camhi cites an SAP survey that illustrates how banks lag behind other industries, especially retail, in customer analytics. The survey reveals that:
Only 46% of banks can analyze external data about customers.
Only 32% can analyze social media activity.
Data volume and analytics complexity are the most common challenges cited by respondents.
Cloud and predictive analytics technologies will be "extremely valuable" to around 60% of respondents' strategies in the next 24 months.
Some of the experts Camhi spoke with said unstructured data is overwhelming for legacy systems in banks, and even internal data management protocols are often in conflict. The first step for banks today is to get their database structures normalized and standardized, before they introduce new data sources into the mix.
Read the rest of this story on All Analytics.
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