About Our Client
Our client is a US based law firm that recovers damages for shareholders who have fallen victim to securities fraud and directors' and officers' breaches of fiduciary duty. The firm focuses specifically on securities class actions and shareholder litigation, making their attorneys experts in complex financial litigation. The firm has recovered over $400 million USD for their clients over the last 2 years.
Challenge
The firm receives hundreds of plaintiff submissions per month, with documentation being uploaded to their system in many formats, such as pdfs, images, transaction receipts, and screenshots. Attorneys were required to manually read through the many different files to extract important information from them. Their system didn’t have any capacity to read the documents submitted, using precious time from the lawyers to sort through and get the crucial information.
The firm needed a solution that would save manual input hours for their attorneys. This new system needed to be able to sort, automate reading of documents, and validate submissions from clients.
Apption's Solution
Our team designed and implemented sophisticated architecture to handle transaction data processing, validation, and reporting. Leveraging a combination of Microsoft Azure services and modern web technologies, we ensured robust data handling and reporting capabilities.
Architecture
Data Processing Pipeline
File upload & metadata extraction
This solution begins with users uploading transaction data files. These files are enriched with metadata that specifies the class type and associated client. Metadata is crucial for data categorization and efficient processing.
The files are stored securely in Azure Data Storage, facilitating streamlined access for subsequent processing steps.
Triggering Azure Data Factory (ADF):
The file upload process triggers Azure Data Factory, which orchestrates the data processing workflow.
Integration with Databricks & Azure AI Document Intelligence:
ADF initiates data transformation tasks within Databricks, which performs data processing and validation.
Simultaneously, Azure AI Document Intelligence extracts and validates transaction data from the uploaded files.
Data storage & management:
Once processed, validated data and extracted metadata are stored in a database. This database serves as a centralized repository for high-quality data that supports further analysis and reporting.
Portfolio Management & Reporting Website
Core Capabilities
The custom-built portfolio management website provides CRUD (create, read, update, delete) functionalities for data related to class actions, associated clients, and transactions. Users can perform data modifications and access comprehensive reports.
Economic loss sheets and other relevant reports can be generated directly through the website.
.NET Clean Architecture
The website is built using the .NET clean architecture framework. This design pattern ensures a clear separation of concerns, improving maintainability, testability, and scalability of the codebase. Read more about .NET clean architecture here or listen to our podcast here.
Enhanced UI with Mudblazor
Mudblazor enriches UI, providing responsive and modern components that enhance UX.
Key Features & Benefits
Automated data validation
Seamless data processing workflow
User-friendly reporting website
Scalability and maintainability
Outcome
The implementation of phases one and two has been successful, delivering benefits to attorneys and stakeholders. The automation and optimization of manual processes have resulted in significant time and cost savings, empowering attorneys to focus on higher-value tasks. As we move into phase three, the foundation laid by the previous phases continues to demonstrate the solution's effectiveness.
