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Finance

IT Automation and Operational Efficiency Enhancement for a Wealth Management Firm

Focus Areas

Data Transformation

IT Infrastructure

Automation

Business Problem

A major bank had a very slow financial reporting process because they were facing substantial inefficiencies with transforming and validating huge volumes of transaction data. The current SQL Server environment delayed data processing and resulted in slow query performance because of a lack of proper indexing. To improve the performance of its database environment, the bank was looking for a comprehensive solution that would optimize data transformation and streamline its financial reporting.

Key challenges:

  • Poor Database Performance: Large transaction datasets were not being processed efficiently because the bank’s SQL Server environment lacked effective indexing and query optimization. This led to poor database performance which impacted the seed of financial reporting.

  • Slow Data Transformation: The bank’s existing process for transaction data transformation was slow, manual, and prone to error, The large volumes of data and inefficiencies in data validation and transformation delayed the accessibility of accurate financial reports.

  • Limited Reporting Capabilities: The inefficiencies in data processing and transformation led to delays in the financial reporting process and impacted internal decision-making and regulatory compliance

  • Lack of Automation: Data transformation and validation were not automated which introduced operational bottlenecks, increased the probability of errors, and affected the accuracy of financial reports. 

The Approach

Curate consultants identified several opportunities for optimization, automation, and acceleration of reporting through close collaboration with the bank’s internal teams and assessment of the current processes.

Key components of the solution:

  • Discovery and Requirements Gathering: Through a detailed assessment of the existing SQL Server environment and reporting processes and a series of discovery sessions and system audits in conjunction with the bank’s IT, data management, and finance teams, Curate identified the following optimization opportunities:

    • Improve SQL Server performance by implementing indexing and query optimization techniques.

    • Automate data transformation and validation using dynamic SSIS (SQL Server Integration Services) packages.

    • Reduce delays in financial reporting by streamlining the data transformation process.

    • To handle future growth in data, ensure that the system can scale efficiently.

  • Optimizing the SQL Server: Curate implemented a series of optimization techniques to enhance the bank’s SQL Server environment.

    • Indexing Optimization: After performing a detailed analysis of the bank’s database schema and query patterns, Curate implemented proper indexing strategies such as clustered and non-clustered indexes. This significantly improved query execution times and overall database performance.

    • Query Optimization: Curate reviewed and optimized the bank’s frequently used SQL queries such as complex queries involving large joins and aggregations. This reduced query execution time and improved data retrieval speed.

    • Partitioning for Performance: Partitioning enables faster access to relevant data by dividing large tables into smaller, more manageable segments. To improve performance and scalability, Curate recommended partitioning large transaction tables.

  • Automating Data Transformation with SSIS: To automate the transfer, transformation, and validation of large transaction datasets and streamline the data process, Curate developed dynamic SSIS packages.

    • Dynamic SSIS Packages: The packages automated the extraction, transformation, and loading (ETL) of transaction data from various sources into the SQL Server, were tailored to the bank’s data transformation needs, and ensured accurate and consistent data transformation.

    • Automated Validation: Data validation scripts were integrated into the SSIS packages to automatically validate transaction data during the transformation process. The automated validation reduced the probability of errors in data and enhanced the overall accuracy of the financial reports.

  • Optimizing Performance and Accelerating Reporting: To ensure faster data transformation and reporting, Curate focused on improving the system’s performance through different techniques

    • Batch Processing for Large Datasets: By introducing batch processing techniques to handle large volumes of transaction data, the system was able to efficiently manage high data volumes without swamping the SQL Server environment.

    • Parallel Processing: To handle multiple data streams simultaneously, Curate implemented parallel processing techniques which substantially decreased the time required for data transformation and improved the speed of financial reporting. 

    • Real-Time Reporting Capability: Curate integrated real-time reporting tools in collaboration with the bank’s internal teams, which allowed quicker access to updated transaction data and reports for financial decision-makers.

    To ensure faster data transformation and reporting, Curate focused on improving the system’s performance through different techniques. 
  • Stakeholder Engagement and Change Management: Curate worked closely with the bank’s internal teams and external vendors to ensure smooth implementation and operational alignment throughout the project.

    • Collaboration with IT and Data Teams: Curate aligned optimization techniques with the bank’s existing infrastructure and data handling requirements by regularly engaging with the bank’s IT and Data Management teams.

    • Vendor Coordination: Through close collaboration with the bank’s third-party vendors, Curate ensured that the necessary software and infrastructure updates were applied smoothly without disrupting day-to-day operations.

    • Change Management and Training: Curate trained the bank’s IT and finance teams post-deployment to ensure they were well-equipped to manage the new SSIS packages and maintain the optimized SQL Server environment.

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Business Outcomes

Improved Database Performance


The bank saw a significant improvement in SQL Server performance with optimized indexing, query tuning, and partitioning. Queries were now executed in seconds versus minutes, reducing delays in data retrieval.

Quicker Data Transformation


The automation of data transformation processes using SSIS packages led to quicker financial reporting and faster decision-making. It reduced the time required to transform and validate large transaction datasets by 60%.

Reduced Manual Intervention


Curate reduced the need for manual intervention and cut down on errors and operational costs by automating the data transformation and validation processes. The bank’s internal teams could now focus on more strategic tasks.

Enhanced Reporting Speed


Financial reports were now generated in half the time providing decision-makers with more timely and accurate financial insights. It also enabled the bank to meet regulatory deadlines.

Sample KPIs

Here’s a quick summary of the kinds of KPI’s and goals teams were working towards**:

Metric Before After Improvement
Query execution time (avg) 5 minutes 30 seconds 90% reduction
Data transformation time 10 hours 4 hours 60% reduction
Financial report generation time 48 hours 24 hours 50% reduction
Manual intervention in data validation 100% 10% 90% reduction
Data accuracy (errors in reports) 12 errors/month 2 errors/month 83% reduction
**Disclaimer: The set of KPI’s are for illustration only and do not reference any specific client data or actual results – they have been modified and anonymized to protect confidentiality and avoid disclosing client data.

List of skills, tools, and technologies

The following set of skills, resources, tools, and technologies were used:

  • Database Administrators: Expertise in SQL Server optimization, indexing strategies, and query tuning.

  • Data Engineers: Skilled in SSIS package development, ETL processes, and data transformation techniques.

  • Performance Analysts: Experienced in identifying and resolving performance bottlenecks in database environments.

  • DevOps Engineers: Proficient in automating data workflows, implementing CI/CD pipelines, and optimizing system performance.

  • Project Managers: Expertise in managing cross-functional teams, ensuring timely delivery of complex technical projects, and vendor coordination.

  • Change Management Specialists: Skilled in training and supporting internal teams during infrastructure changes and process automation.

Tools & Technologies

  • Database Platforms: Microsoft SQL Server, SSIS (SQL Server Integration Services)

  • Data Transformation Tools: SQL Server Integration Services (SSIS), Apache Kafka, Talend

  • Data Validation & Automation: Python scripts for automated data validation, PowerShell for process automation

  • Performance Monitoring & Optimization: SQL Server Profiler, Azure Monitor, Splunk

  • Collaboration & Project Management: Jira, Confluence, Microsoft Teams

Conclusion

Curate helped the institution overcome precarious performance bottlenecks and reporting delays by optimizing the bank’s SQL Server environment and automating data transformation processes. Curate’s expertise allowed the bank to streamline operations, meet regulatory deadlines, and make decisions that were better informed with the help of real-time financial data. The new indexing strategies and dynamic SSIS packages brought about a significant reduction in data transformation time and improved the accuracy of financial reports.

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