AWS Cloud Infrastructure Optimization for Financial Data Aggregation and Risk Assessment

The organization faces difficulty in aggregating and analyzing client financial data due to inconsistencies in client identification across diverse data providers. Additionally, the existing cloud infrastructure underperforms, leading to slow data retrieval, increased operational costs, and delayed underwriting decisions. Fragmented data structures impede real-time analytics, affecting risk assessments and decision speed.

A large global financial institution specializing in commercial lending and risk mitigation, utilizing multiple third-party data sources for underwriting and decision-making processes.

• Achieve a 20% reduction in data ingestion time to enable faster integration of financial data.
• Improve query performance by at least 30% to facilitate real-time insights for underwriting and risk management.
• Standardize client identification across multiple data sources to ensure data consistency and accuracy.
• Optimize AWS cloud infrastructure to reduce unnecessary costs and enhance data retrieval speed.
• Enhance overall data aggregation processes to support smarter, faster financial decision-making.

• Database assessment and restructuring to improve query execution and retrieval speeds.
• Implementation of data standardization framework for consistent client identification.
• Provision of a redesigned data warehouse for rapid debtor/client analytics and summarization.
• Optimization of cloud resource allocations and setup of indexing and caching mechanisms.
• Establishment of scalable data ingestion pipelines for efficient financial data processing.

• Third-party data providers for client information
• Data analytics tools for real-time reporting
• Monitoring and cloud management services

• Reduce data ingestion time by 20%
• Achieve at least 30% faster query performance for analytics
• Ensure data consistency and accuracy across all sources
• Optimize cloud resource usage for cost savings
• Guarantee system scalability for future data volume growth

The project aims to significantly improve data retrieval speeds by 30%, reduce data ingestion times by 20%, and standardize client data, leading to more accurate risk assessments. Cost-efficient cloud utilization will lower operational expenses, enabling the organization to operate with faster decision-making capabilities, improved data quality, and overall enhanced analytical responsiveness, ultimately supporting smarter financial and risk management decisions.