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Helping Banks Meet Regulatory Compliance with Big Data

Helping Banks Meet Regulatory Compliance with Big Data

"Big ‍10 ‍banks fined $43bn over seven years for failures in customer reporting” reads yesterday’s headline in Financial Times and I wonder how the power of big data could have helped in saving these billions of dollars. The report goes further: "Failures in customer reporting have cost the world’s top investment ‍banks $43bn in fines over the past seven years, making it the single most expensive compliance issue”.  

In the age of advanced reporting capabilities enabled by big data, this seems shockingly backwards. This is especially true when you consider how many industries are increasing profits by using customer data to upsell-cross sell and targeted marketing. By using robust technologies like the MapR Converged Data Platform to build a 360 degree view of the customer, I reckon that banks could have saved billions of dollars on regulatory fines in addition to generating profits and cutting costs.  

Compared with other industries like telco and retail, financial services are playing a bit of catch-up on big data and digitalization wave in APAC. While they may some years behind other industries, interest in the possibilities of big data have cranked up enormously across financial services in APAC region now. Much of the hesitation to adopt this new technology has been attributed to conservative and cautious nature of banking industry. 

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But revenue constraining fines and stringent regulatory frameworks have increased pressure on banks to meet regulatory requirements as quickly and as promptly as possible. The power of big data - correctly applied - can help banks reduce regulatory compliance risks, and avoid potential problems in real time. Big data for the banking industry the world over is becoming more of a necessity than a matter of choice.

Big data analytics can help build new compliance reports and perform regulatory stress tests. The annual stress tests by regulators require banks to aggregate data that is scattered across systems, servers, apps, RDBMSs, lines of business, and separate legal entities. Hence, updating data and sourcing the adequate data are crucial to the stress-testing process. The MapR Converged Data Platform plays a key role in empowering the banks to easily ingest data from both new and legacy sources. As banks maximize the value of their data by feeding it into a variety of application and analytical models, they should use both internal and external data source to consider these models from regulator’s perspective. The client fines that are hitting these banks are also due to investor protection, transparency and transaction accuracy as well. Including misleading communication or fraudulent agent activity.

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