Data can be an excellent resource for firms that are concerned with operational performance and consumer engagement. After all, this type of information provides critical feedback about how companies engage with their customers and employees. Yet like most other resources, data must be managed effectively in order to make sure it delivers its maximum value.
Today’s financial companies track millions of pieces of trade-related data. This information is often highly relevant to the customer experience, and it may provide insight into how operations can be improved. Despite the potential usefulness of this data, many firms struggle to utilize the trade-related information they gather in a way that can improve operations. Industry experts suggest that companies should be proactive in using the trade-related data they collect as a tool to facilitate improvements within the company. However, with the struggles many financial firms still face in managing operational data effectively, recommendations such as these may be more easily said than done.
Data Creates Implicit Value
The financial industry is one of the most highly-regulated economic activities in the world. Banks and investment companies are required to track and do data management of huge amounts of data as a matter of law, but many financial firms have fallen behind when it comes to implementing data collection practices that make good use of this information.
Financial companies maintain broad and in-depth stores of customer and trading information. This data generally cannot be disclosed to anyone other than regulatory agencies, but this fact does not make it valueless. Rather, financial firms should implement processes that allow them to benefit from data collected and maintained in-house. Thus, even though trade-related data cannot be bought or sold, it can be used in a manner that creates value for the company by increasing the efficiency of internal operations. Companies that utilize the data they collect for regulatory compliance purposes to boost efficiency and improve customer experience can experience meaningful long-term revenue growth as a result.
Data Management Challenges in the Real World
Paul North, Head of Project Management EMEA at BNY Mellon, explains the multi-faceted challenges associated with turning electronic data into information that is helpful to real-world business operations. As North explains, “as firms look at the need to reduce costs or to replace a middle-office system or a front-office system, then that data challenge comes into play because there’s another driver to make the investment into a more sophisticated data management platform.”
In other words, one of the main issues facing financial firms seeking to boost data management practices is the practical challenge associated with implementing new processes in a complex operational environment. Change is risky, and implementing new data management programs in companies as large as most of today’s financial conglomerates requires a major investment of time and resources. This is particularly true at a time when consumer data and online privacy protections are increasing, and firms that collect and maintain personal or financial information about their customers face increasing reputational risk. After all, even the appearance that consumer financial information is being used inappropriately could cost firms customers, reputation, and revenue.
The complexity, risk, and cost of building new systems that utilize customer and trade-related information in a way that improves company performance deter many financial companies from tackling data management head-on. However, in the increasingly-competitive European financial services market, effective data management could mean the difference between reinvention and obsolescence.
Competition Drives Creative Data Management Solutions
Modern challenges in data collection and utilization call for innovative solutions. Regulators across Europe and the UK are encouraging enterprises to use the data they’re collecting to improve operations across the industry in the hopes of facilitating the development of a more efficient and robust financial system across the continent. This sandbox approach is already encouraging innovation in data collection and management in regulated firms, many of which are using sophisticated data-driven modeling to cut a new competitive edge in European financial services.
Progressive financial institutions already have begun to reap the rewards of their investments in advanced data management tools and policies. For example, one of the largest banks in the Middle East recently deployed advanced data collection technology to build its customer base. The bank designed a data management system that allowed the company to access trade-related and investment data in real time from every transaction that went through its network of ATMs. The bank’s sophisticated data management practices improved operations that had previously taken days or even weeks. This is possible only because the bank’s data collection and management technology allows it to respond to customer needs faster and more directly than ever before. As a result, customer experience significantly improved, and the bank has been able to improve the overall quality of service.
This early evidence may be anecdotal, but seasoned financial professionals recognize that customer and trade-related data is valuable as a way to help companies improve performance and lower costs. Making good use of the growing amounts of data financial firms are required to collect can boost operational efficiency, reduce costs, and improve customer experiences. This strategy is not without its risks, however, as building effective data collection and management in the real world often requires a substantial investment of company resources. The bottom line is that firms that do not utilize the data they have at their disposal risk becoming obsolete in today’s technology-driven financial services market.