Empowering Financial Institutions with Data Integrity and Trust
In the BFSI sector, maintaining data accuracy is critical for regulatory compliance, customer trust, and risk management. Rakuten SixthSense's Data Observability ensures that financial institutions can trust the quality of their data, enabling them to make informed decisions quickly.
With real-time data monitoring, the platform detects anomalies and inconsistencies, ensuring that financial reports, risk assessments, and customer interactions are based on accurate, reliable data. This proactive approach enhances operational efficiency, reduces regulatory risks, and strengthens decision-making, making Data Observability a key enabler in the evolving financial landscape.
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Key Benefits
Streamlining Risk (Credit and Operational) in BSFI
Financial organizations must implement predictive analytics and high-quality data management to effectively address NPA rates (e.g. India s 5.9% NPA), improving credit assessments and profitability. It s also critical to employ rigorous monitoring and risk management for operational risks, ensuring excellence and protection against financial and reputational harms.
Data Observability’s AI based data quality monitoring can help financial services detect data quality and reliability issues before impacting business thereby improving decision-making and operational efficiency while reducing non-performing assets. Real-time anomaly detection and data pipeline oversight ensure accurate risk evaluation, mitigating financial and reputational risks.
Maximizing Marketing and Sales Efficiency in BSFI
In the finance domain, optimizing marketing and sales efficiency is paramount for success, especially amidst the evolution of Neobanking. Traditional financial institutions encounter challenges in seamlessly integrating customer data across channels to deliver services affecting marketing and sales efforts.
Rakuten Data Observability offers a comprehensive suite to tackle these challenges, featuring real-time monitoring for immediate anomaly detection, data pipeline visibility to prevent integrity issues, and volume and schema change tracking. These robust capabilities work in tandem to ensure that financial institutions can trust the data that underpins their compliance reporting, safeguarding against operational losses and reputational harm.
Optimizing Data Accuracy for Financial Insights
Critical decisions in the BFSI sector rest on the foundation of data accuracy. With 71% of financial firms & citing a competitive edge from analytics use, the value of precision in data is clear.
Data Observability combats these challenges with AI enabled Data Quality Monitors and Rules, ensuring analytics are based on accurate, high-quality data. This not only sharpens risk assessments but also enhances decision-making, securing a competitive edge in the swiftly evolving financial landscape.
Enhancing Regulatory Compliance and Reporting
The severe consequences of regulatory non-compliance in BFSI are highlighted by IBM's discovery that U.S. businesses lose $3.1 trillion each year because of low data quality. This emphasizes the costly results of mishandling data.
Rakuten Data Observability offers a comprehensive suite to tackle these challenges, featuring real-time monitoring for immediate anomaly detection, data pipeline visibility to prevent integrity issues, and volume and schema change tracking. These robust capabilities work in tandem to ensure that financial institutions can trust the data that underpins their compliance reporting, safeguarding against operational losses and reputational harm.
Strengthening Data Governance
The financial sector faces significant data governance challenges, affecting privacy, accuracy, and compliance. AIOps technology presents a forward-thinking approach to detecting deviations post-compliance changes, safeguarding privacy, accuracy, and regulatory adherence.
Cognitive AIOps integrates Prometheus data source ingestion, Advanced analytics and AI correlations to monitor over frequent changes made in the system contributing to robust data governance, ensuring privacy, accuracy, and compliance.
