Aokumo helped a FinTech client achieve a 70% reduction in report generation time for regulatory reporting and a 99.96% improvement in SLA.
The client was facing issues with their daily reporting being slow, prone to errors, and lacking regulatory requirements.
Aokumo helped a FinTech client achieve a 70% reduction in report generation time for regulatory reporting and a 99.96% improvement in SLA.
faster deployment time
time-saving for regulatory filings
better data quality
improved SLA
The client provides trading services through multiple trading systems with their own data structure and way of doing transactions. The client generates daily regulatory reports for compliance and filing purpose. However, due to the inefficiencies in the existing reporting system, they were lagging to meet deadlines.
The client wanted to build a data pipeline and reporting system to satisfy the regulatory requirements with minimum development efforts and time. The client also wanted to ensure that data collected from different sources gets converted to the correct format and accessed securely. However, they were short on time and didn’t have the required skill set in their team.
Aokumo designed and implemented the modern Data Lake, enabling and empowering developers to quickly build jobs for automatic reports generation.
Since the data comes from different systems and in different formats, it was essential to standardize it and store it in a coherent way.
The client had no experience in Data Lakes, so we needed to ensure that they had proper training after implementation.
Reporting was required to be accurate, time-sensitive, and secure to meet regulatory requirements and SLA.
Data security challenges need to be addressed in order to protect confidentiality.
The team at Aokumo used AWS Lake Formation for ease of data infrastructure deployment.
Aokumo implemented a centralized repository of data to enable efficient cataloging, search, and access.
We integrated suitable tools for data validation, incident alerting, and disaster recovery.
We also implemented other cloud-native AWS services to ensure the integrity and authenticity of data.
The client is now able to ship new data & analytics capabilities 4 times faster than before.
Improved data capturing, sanitization, and reporting are saving more than 70% of the client’s time while filing regulatory reports.
Data validation tools and proactive alerts have achieved higher data quality and more accurate insights.
Cloud-native data & analytics infrastructure has dramatically improved the client’s SLA adherence with high performance, availability, and security.
- Allows users to easily provision their AWS resources by automating the creation and termination of infrastructure, services, and applications.
- A highly scalable, fast, and durable solution for any data type object-level storage accessed anywhere via the Internet through the Amazon Console and S3 API.
- A managed cloud service that makes it easy for customers to prepare data for analysis through automated extract, transform, and load (ETL) processes.
- A compute service that lets you run code without provisioning or managing servers.
- A serverless interactive analytics service offered by Amazon that can be readily used to gain insights on data residing in S3.
- A managed database service that combines the performance and availability of traditional enterprise databases with the simplicity and cost-effectiveness of open source databases.
- A cloud-based business intelligence platform that allows users to build visualizations and dashboards and perform ad-hoc analysis.
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