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Blockhouse

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🔐Breaking Free from Data Shackles: Unleashing Your Firm’s True Potential Front office, middle office, and back office. Excel files, Powerpoints, APIs, databases, and more. Financial institutions have mountains of data all stored in different places by different teams, making the process of sharing information and automating workflows extremely difficult and manual. This issue is known as data siloing, and in this post we dive into its causes, unpack its impacts, and explore strategies to alleviate this issue. 👨🏻🌾 Understanding the Roots of Data Siloes: Legacy systems of recording data, like Excel, often lack the ability to perform real-time data syncing and API support, standing as a significant contributor to data siloes. A Capgemini survey revealed that 95% of banks grapple with growth challenges due to the inaccessibility of data residing in legacy systems. Additionally, data incompatibility, manual processes, lack of governance, and the high complexity and cost of managing these siloes compound the issue. 🔄Unpacking the Impacts of Data Siloes: These isolated data pockets impact various facets of financial institution operations. Customer experience takes a hit as data siloes hinder a comprehensive view of customers, introducing friction and frustration in their journey. Risk management faces obstacles, limiting the identification and mitigation of diverse risks and impeding compliance. Moreover, operational efficiency suffers, resulting in increased time and cost for data and analytics processes. According to reports by McKinsey and BCG, financial institutions adopting data unification strategies can potentially reduce operational costs from 40 - 80%. 💡Strategies for Overcoming Data Siloes: To break free from these constrictions, financial institutions can adopt strategic approaches: 1) Data Unification: By integrating data from various sources together, financial institutions can create a unified source of truth and a common logic layer for data and analytics. This not only fosters collaboration but also empowers automation and AI/ML workflows, driving streamlined operations, enhanced customer experiences, and a competitive edge in the industry. 2) Data Migration: The process of transferring data from legacy systems to modern platforms, such as cloud, on-premises, or hybrid, holds the potential to improve data performance, scalability, and security. It opens doors to new capabilities like real-time data syncing, API support, and microservices architecture. 🔮Stay tuned for further insights into overcoming data challenges in the ever-evolving landscape of finance! 👉 #DataManagement #FinancialInnovation #BreakingDataSiloes

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