Data is king. Banks that know how to effectively harness it, manage it and monetize it can derive far better business insights, create significant growth opportunities and stay ahead of regulatory demands. Huge benefits can be reaped by developing a clear data strategy that defines how to access, ingest and connect the essential data that can drive positive business outcomes.
Data is the lifeblood of financial services organizations. Whether a community bank or a high-level global powerhouse, all banks, insurance companies, asset managers, wealth managers and capital markets firms deal with extraordinarily large amounts of data. From the trading desk to the underwriting teams, to account opening, to advancing loans, to staff recruitment, to regulatory reporting… the list is endless. In the banking industry, data drives the business.
Data can be leveraged in many powerful ways, and the digitization of financial business processes has opened new opportunities to turn data into information, glean insights and generate new value from it. However, the ability to gain insights from data is often hindered by the presence of non-standardized and inefficient processes to go along with aging infrastructure and disparate legacy applications, sometimes referred to as “technical debt.”
All organizations, especially tier-one banks, face the challenge of how best to optimize their technology landscape to make it more cost efficient, business effective, and secure when leveraging the ever-increasing flow of available data. They are challenged to find efficient and effective ways to use data to be more relevant with the new and cross-sell products they introduce to customers, manage security threats and report relevant information to their various constituencies.
Embedding a sustainable data strategy – and executing it – across financial services’ business practices and reporting requirements is a critical first step. To do this successfully, banks require access to data from a myriad of internal and external data sources, both structured and unstructured. Increasingly, they need the ability to do this in real-time, as well as to store and analyze the data in such a way that they can make timely and informed decisions. The end goal is to arrive at a data strategy and data platform that can facilitate growth and meet the needs of internal and external customers.
About the authors
About the authors
Jeremy Donaldson, managing director of Banking & Capital Markets (EMEA) at DXC Technology. He has more than 25 years of experience in applying technology solutions to solving complex business challenges in numerous management and consulting roles. Connect with Jeremy on LinkedIn.
Andrew Haigh, head of Banking & Capital Markets (EMEA) at DXC Technology. He is focused on helping customers derive value from data and delivering innovative solutions across the banking and capital markets spectrum.
Paul Hewitt is director and head of the Data, Analytics and Machine Learning practice at Luxoft, a DXC Technology company. Paul has spent most of his career focused on helping organizations derive value from analytics in the BCM and financial services industry.
Sunil Menon is managing director and Head of Manufacturing and Life Sciences (EMEA) at DXC Technology, and has expertise in areas such as helping organizations implement best practices for data-driven manufacturing.