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Synechron Report: The Overlooked Foundation of Data Innovation – Or, why great innovations fail

The surge of data-driven innovation

Demand for data-driven innovation has been skyrocketing, as data rapidly takes an increasingly pivotal role in the Financial Services’ industry’s strategy for the digital era. From fraud prevention, to customer retention, to process optimisation, data-driven technology has become the go-to solution for a wide array of challenges that the sector currently faces, if not for all. And with their promising results, it is no wonder that banks and insurers have been pushing to implement tooling, hire datascientists, and monetize data where possible. Financial Services firms are hungry to leverage their data in big ways. Yet, as their focus lies mainly on implementing technology and data science capabilities, limited data quality and availability remain inadequately addressed. What’s often overlooked is that the success of these technologies hinge on the foundations of the data landscape.

Data management as the foundation

Just as constructing a building starts with robust architecture and a solid foundation, so does data management form the underlying base of data innovation. What we see is that Financial Services firms invest heavily in datadriven solutions in support of fraud detection, risk-management and compliance, to name a few. Despite the importance of tools for enabling data capabilities, without high quality data the tools will not deliver desired results. In order to effectively process and monetize information, organisations need their data to be up-to-date, accurate and reliable.

A classic example of this is where tooling — whether for reporting, client onboarding, or other data-driven process — requires customer data, but the available flow is incomplete or inaccurate. A common interim solution is having teams manually reconcile and correct data deficiencies. We frequently receive questions from businesses that are in the process of solution implementation when they start facing such data governance challenges. This is often only recognized when innovation output does not meet expected results.

Download the full report below. Find out more about Synechron here.

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