The Future of … Big Data Use by Financial Services

Would it surprise you to learn that 83 percent of financial services firms report that data is their most valuable strategic asset? Read on to learn more.




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    The Future of … Big Data Use by Financial Services

    The Future of … Big Data Use by Financial Services

    Would it surprise you to learn that 83 percent of financial services firms say that data is their most valuable strategic asset?1

    The massive accumulation of data, along with sophisticated analytics tools and advances in machine learning, have placed data on par with the importance of the three traditional cornerstones of business: people, process and technology.

    The uses of data are far ranging, including gaining insights into customers, competitors, markets, risks and employees. Among the primary ways financial firms are using big data include:

    1. Fraud Detection—Banks and other financial services firms can better identify transactions that may be fraudulent based on a customer’s historical behavior, potentially stopping fraud before it occurs. For example, a bank sees an ATM transaction in process in one city, while the mobile phone of the customer attached to that account indicates he is in a different city.


    1. Customer Segmentation—By better understanding customer demographics, past transactions, and interactions online and with customer service centers, firms can more efficiently and effectively gear more relevant marketing messages and product promotions to customers.


    1. Personalized Marketing—Knowledge of specific events in a customer’s life can help firms promote products and services at the time when the customer need arises. This can be done via information gathering from a customer’s social media or by partnering with retailers, travel sites and other providers to gain insight into what may be going on in their customers’ lives. A posting, for instance, about a new child may prompt communications about loans to finance a new home or expand the existing one, or perhaps a 529 savings plan.


    1. Risk Management—Risk management related to monitoring bank capital requirements, proprietary risk exposures and customer risk is vastly improved as the amount of available data increases. For instance, big data can provide continuous stress testing as financial and economic conditions change.


    1. Smarter Portfolio Management—Big data is allowing asset managers to seek alpha in an increasingly alpha-stingy investment landscape by tapping new sources of input. These inputs may include transaction data, satellite imagery, weather patterns, and social media conversations and trends. For instance, rather than wait on government-sourced information about economic activity, big data can provide insight well before traditional monthly economic reports are released.


    Though leveraging big data is a key priority for financial firms, obstacles still remain: e.g., regulation and privacy concerns, lack of a clear vision about what it is that a firm wants to accomplish, legacy systems that stifle introduction of new technology and a shortage of workers with the proper skill set; however, these are not show-stoppers.



    See referenced disclosure (2) at 





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