Hybrid Solution for Entity Registration Data

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Hybrid Solution for Entity Registration Data

Mojo Case Study

Problem Statement

A leading US financial services company needs an efficient solution to collect registration data, including legal names, addresses, and incorporation details. The solution should combine automated scraping and manual verification to ensure accuracy, gathering information from various sources and cross-referencing data. This streamlined process aims to reduce time and effort while maintaining data integrity and compliance with regulations.

Our solution

Comprehensive Source Identification: Identify and integrate over 200 data sources to cover all data needs, ensuring a wide-ranging and thorough data collection process.
Intelligent Bot Development: Develop advanced intelligent bots for automated data extraction, enhancing efficiency and accuracy in gathering information from identified sources.
Proprietary NLP-Based Name Matching Tool: Utilize TechMobius’ proprietary NLP-based name matching tool to accurately identify and map entities within the database, ensuring precise entity recognition and data mapping.
Scalable Processing Platform: Implement a scalable platform capable of processing up to 2 million entities monthly, accommodating large-scale data operations and ensuring robust performance.
Continuous Improvement in Data Fill Rate: Focus on consistent enhancement of fill rates across all data categories, leveraging ongoing improvements and optimizations to ensure comprehensive data coverage and quality.

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Benefits

Comprehensive Data Collection: A repository of registration authorities ensures thorough collection of registration data, including legal name, registered address, registered date, and other incorporation details, providing a complete and accurate dataset.
Enhanced Efficiency and Accuracy: Combining automated scraping with manual verification narrows down search results using the full legal name and identifier, leading to more precise data collection and reducing the likelihood of errors.
Improved Data Reliability: The integration of a manual process to match and collect data ensures that the information gathered is accurate and reliable, enhancing the overall quality and trustworthiness of the dataset.