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Harnessing the power of data analytics
Challenges and opportunities faced by banks looking to be customer-centric
29 Jan 2021 | Darryl Yu

For many banks across the globe, the ongoing pandemic has been a wake-up call or an affirmation of the importance of embracing digital tools, not only for efficiency but also for business development in the post-Covid world.

As more and more individuals and companies rely on digital financial tools, the amount of data captured by banks grows exponentially. Whether it be through the number of times you log in to a mobile app or your search history on stock prices, financial institutions acquire a better picture of your tendencies, preferences and habits, thereby giving them the opportunity to calibrate their services and make them more relevant to their clients’ needs.

 “Banks that make greater use of data to proactively adapt their product offering to meet the needs of more uncertain customers — to help them spend, save, invest, and ultimately build their financial security — can help boost customers’ confidence while strengthening their own competitiveness,” accounting giant EY  maintains in its global banking outlook 2021 report.

The question now for banks is how best to harness this deluge of data for business development. For most firms, the conversation around data usage has been going on for the past several years. Needless to say, key challenges still remain for many organizations in that journey, specifically when it comes to consolidating the data into a centralized location, also called a “data lake”.

Often working in siloed units, many banks struggle to fuse these disparate sources of data to get a 360-degree view of their clients and their commercial relationships. In supply chain financing, a unified data approach could be useful in mapping out the financing needs of a corporate client, as in the case of a bank  that has a business relationship with the suppliers/distributors of the main anchor corporate.   

This involves not just the bank’s data but overall relevant data. As such, banks need to carefully evaluate which information would be useful for internal customer analysis, including data coming from, say, government agencies and news sources.

Internal banking applications relying on various sources of data would be useful for bank relationship managers, for instance, who often need to conduct market research into the pain points of their clients before meeting up with them.

Building a robust data analytics machine is important, but the next challenge for any bank is training its staff to make use of the data and act upon it as they see fit. The last thing any bank would want is to spend huge amounts of capital on creating a data dashboard only to find it unable to contribute to business development.

With the growing focus on data analytics, banks have started to make sizable investments and forge partnerships in adopting cloud technology which can help manage large sets of data.  Amazon Web Services, one of the largest cloud service providers, for instance, has announced a data management deal with HSBC. Google has also unveiled partnerships with Deutsche Bank and Goldman Sachs to help them make better use of data in mapping out their respective business strategies. 

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