The storing of sensitive information, particularly consumer data, is a known but challenging cybersecurity risk to overcome, as financial services providers, like all companies, increasingly drown in data. Complicating big data issues for banks and credit unions is that they have to maintain certain information about their customers and members, not only for regulatory compliance and account security, but also for customer relationship management. Data lakes are often used as overflow repositories for data that no one knows what to do with but can’t be completely removed. But they put cyber teams in a precarious position, because more data always equates to more risk, more privacy compliance scrutiny and more expense. Transforming data lakes into data rivers, where information can be “streamed” and categorized, requires data thought leadership, planning, and data pre-processing. This report outlines the risks inherent in an over-reliance on data lakes and offers an alternative approach for data storage and categorization tailored specifically for financial services companies. Javelin Strategy & Research addresses the “why” and “how” of increasing reliance on data rivers, and introduces the term “data harbor,” which Javelin deems to be a viable alternative for data lakes, with a specific focus on heightened security.
Key questions discussed in this report:
- How can cybersecurity teams leverage exponentially growing amounts of data to identify threats in real time?
- What are the risks of relying too heavily on data lakes for storing sensitive data and personally identifiable information?
- How can financial institutions retain and leverage data without hurting their cybersecurity postures?
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