A regional bank in the US faced challenges in managing a vast array of sensitive data, encountering regulatory scrutiny and client dissatisfaction. Initially, bank executives were hesitant but recognized the need for automated data management to meet compliance audits.
The bank’s IT department and business analysts struggled with effective data access and sharing, complicating data analysis and reporting. Sprinterra was tasked with automating data analysis and reporting, enhancing data quality, securing sensitive information, and providing seamless data access across various departments, in line with the latest regulatory demands.
Sprinterra initiated a comprehensive discovery phase to define a strategic data management plan, including organizational structures and roles. This phase involved an in-depth assessment of the bank’s data infrastructure across finance, business, and IT. To tackle data discovery and literacy issues, Sprinterra implemented a user-friendly data management tool that simplified data governance through data cataloging, metadata management, and collaborative data handling. We integrated leading data platforms like Snowflake and Salesforce to create a unified data source that automated and streamlined data processes across the bank, enhancing regulatory compliance and operational efficiency. In addition, Sprinterra focused on improving data reporting and dashboard capabilities, providing real-time insights, and facilitating data-driven decision-making.
Enhanced Data Governance: Implemented stringent pre-extraction rules that reduced processing times and standardized data use across the bank.
Increased Transparency: Established comprehensive documentation practices, enhancing workflow accountability and consistency.
Operational Efficiency: Enabled users to independently access and manipulate data, significantly reducing the analytics team’s workload.
Improved Data Privacy: Ensured compliance with multi-platform regulations, effectively safeguarding sensitive information.
This case study illustrates how strategic data governance and advanced technological integration can ensure compliance with regulatory requirements, boost the bank’s operational efficiency and data reliability, resolve compliance challenges, and improve operational efficiencies in the financial sector.
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Identify outdated systems and technologies that hinder agility and innovation.
Identify IT governance strategy. Evaluate IT architecture.
Build Business model diagram, process flows & organization map. Discover areas to streamline and automate processes.
Evaluate data quality and integration across systems and processes. Establish data principles and data modeling.
Identify Data Flows.
Maturity assessment. Build new Data Governance Framework, Organize Data Flows and target Data Architecture.
Application Communication diagrams; Application components diagram; Security and Data Privacy implementation
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