Big Data & Cloud solutions for Banking & Insurance
Discover how Datumo leverages Hadoop-based solutions to create a secure and accessible central data platform for the banking industry.
Industry challenges
Regulatory Compliance
Strict banking regulations such as GDPR and PSD2 require rigorous control over data privacy, consent, and data residency.
Data Security & Privacy
Sensitive customer data is a prime target for cyberattacks. Encryption, access control, and secure data masking must be tightly integrated.
Legacy System Integration
Many banks operate on mature systems (e.g. mainframes) that are difficult to integrate with modern Big data tools.
Data Quality & Consistency
Data from disparate systems is often inconsistent or incomplete. Duplicate records, missing values, and unstructured data can undermine analytics.
Data Lineage & Traceability
It's critical to understand where data originates, how it has been transformed, and who has accessed it.
Data Availability & Resilience
Ensuring data availability and recoverability in the event of failures (e.g., ransomware attacks) is a complex challenge. High-availability architectures with robust replication, backups, and disaster recovery plans must be designed.
Benefits
Fraud Detection
Big data technologies enable real-time transaction monitoring, allowing to detect fraudulent behavior promptly. Advanced machine learning algorithms automate fraud detection processes and adapt to evolving fraud tactics.
Compliance and Regulatory Reporting
Big data technologies streamline compliance processes by automating data collection and enabling real-time monitoring. Data engineering ensures data quality, integrity, and security.
Real-time Investment & Financial Data Analytics
Real-time analytics allow to monitor market trends, enabling proactive investment strategies. By analyzing low-latency streaming data institutions can adjust investment strategies.
Risk Management
Real-time analytics enhance risk management practices by enabling to monitor portfolio performance in real time. They support the development of reliable risk models based on portfolio metrics enriched with real market data and economic indicators.
Customer Insights and Personalization
Analyze customer data, transaction history and demographic information to gain valuable insights into customer preferences. Data can be used to personalize marketing campaigns and product offerings.
Operational Efficiency
By centralizing data management and implementing scalable data processing pipelines, organizations can improve operational efficiency.
Read our success stories
Centralized Big Data platform
A multinational bank with expansive goals needed a data platform upgrade to manage surging global transactions and demanding report processes. The existing Big Data setup couldn't handle rapidly increasing data loads efficiently. Datumo stepped in to create a centralized, scalable system that ensured smooth data flow and better security. Datumo's solutions unified data sources, optimized the platform through migration to the Cloudera Data Platform, and enhanced reporting speed and reliability. This collaboration fortified data integrity, security standards, and future scalability for the bank's ambitions.
Read moreMake BIG data breakthrough!
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