As fintech continues to expand and financial institutions turn to technologies like mobile wallets, Smart ATMs, and apps to serve customers, the retail branch banking experience could become obsolete. Innovations like artificial intelligence (AI), big data and analytics, and the Internet of Things (IoT), have led to what many have called the “fintech revolution,” an era spearheaded by technology that elevates the customer experience.
Despite these innovations, some things remain the same. A recent study revealed that the majority of consumers still believe safety, security and fairness are of utmost importance when considering a financial institution to bank with. According to Shameek Kundo, Chief Data Officer for Standard Chartered Bank, “What’s changed with recent advances in technology and data science is that now we are able to use that data much more effectively, to understand our customers better, to serve them better and help them achieve their financial aspirations and goals.”
But many organizations, both traditional financial institutions and fintech startups, still struggle when it comes to utilizing big data and analytics to their advantage. The Forbes Insights and KPMG “2016 Global CEO Outlook,” found that 84% of CEOs are concerned about the quality of the data they’re basing their decisions on. If that weren’t enough, Gartner measures the average financial impact of poor data on businesses at $9.7 million per year. Following these statistics, high quality data has become a differentiator for organizations everywhere, especially within financial services, where the legitimacy and security of personal and financial information is critical. Here are some ways the experts at Forbes believe data can be used as a differentiator:
Customer Experience: As organizations look at ways to differentiate themselves from the competition, high quality data provides a single customer view so companies can deliver a more personalized experience.
New Products and Revenue Streams: Having accurate data can help designers and engineers refine products or launch entirely new ones.
Operational Efficiency: Improving data quality can improve efficiencies in many ways, including the de-duplication of customer records, which could result in lowered mailing costs for organizations.
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