Accelerating data analytics: How financial services can learn from other sectors

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Digital Reinvention
28/11/2022 Study

Through one-to-one interviews supported with online questionnaires, Teradata and Qorus have researched the opinions and actions of leaders in data analytics working at some of the world’s largest financial services organizations. The findings highlight areas of significant progress, ongoing innovation and leadership. but they also illustrate areas in which the sector can still adopt best practices which are fueling greater flexibility, resilience and growth in other sectors.

This report paints a picture of an industry in the midst of rapid change. Data analytics has evolved from fringe exercise to a core element in day-to-day operations for most financial services firms. Teams have grown in size, importance and reputation within the business – leading, in many cases, to skills shortages. The leaders are already embarking on the next wave of development, embedding data analytics in more departments and processes while also automating and reusing analytical models to maximize the impact of scare data science resources.

Overall, the study reveals a high degree of consistency across the sector. At the same time, it highlights where financial services would do well to look outside of the industry to plan their next steps to drive growth, stay ahead of emerging players from within and outside the industry and continue to meet the demands of customers.

Regulation can no longer be used as an excuse for slow adoption of innovations in data analytics. Indeed, the area of ‘RegTech,’ using analytics to improve, streamline, automate and future-proof responses to increasing regulation, provides an informative case study of ways in which an enterprise-wide approach to data analytics can drive savings, growth and innovation across an entire organization.

Using data analytics more effectively than your nearest rival is no longer enough. In a digital economy every brand seeking to capture attention and engagement with customers is a potential customer. Financial services need to offer the same personalization, in-the-moment responsiveness, and agility to react to rapidly changing circumstances that customers now expect from any brand they chose to do business with. Acceleration of adoption of data analytics at speed and scale is fundamental to growth and success in this environment.

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