Data Verification for Financial Advisory Firm

Data verification revolutionized portfolios, empowering customer-centric investment strategies..

Project Overview

Business Needs

The firm gathered reliable investment intelligence for EDOs worldwide, facilitating Foreign Direct Investment-FDI. They faced challenges in standardizing, updating, and verifying vast amounts of financial data. To maintain an accurate and flawless database crucial for informed business decisions and avoiding financial losses, they were seeking a partner for efficient data verification.

Challenges of Financial Data Collection

  • The financial data verification process involved thousands of data records with extensive details spanning over 80 fields, including employee count, revenue, phone numbers, addresses, foundation year, and headquarters location.
  • Managing various verification sources led to inconsistencies within the data. Identifying the most reliable source was challenging.
  • Additionally, the rapid deterioration of customer information posed difficulties in effectively verifying datasets.

Solutions and Results

Make your financial data accurate and reliable.

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In this ongoing project of data verification for financial advisory firm, Hitech BPO curates and verifies financial datasets muddled with duplicate and inconsistent data. To ensure a high-quality and integrated database, we utilize macros, customized bots, and rule-based scripts, improving accuracy and efficiency.

  • A structured workflow was implemented, dividing the data specialists into two teams based on task complexity and resource competency.
  • Fields were classified and assigned to different teams for verification according to their complexity.
  • Combining manual methods and ML-based models, duplicates were identified and eliminated.
  • Details such as company name, locations, phone numbers, revenue, and employee count were verified and validated by scanning multiple websites, extracting precise addresses of global headquarters, and gathering relevant data.
  • Rule-driven algorithms played a vital role in verifying and identifying genuine records across multiple sources. The verified and validated data was consolidated into a structured database and subjected to automated rules for data cleansing and standardization.
  • Finally, the refined data was presented in a visually appealing, interactive, and user-friendly investment portfolio format for easy access and comprehension by the financial advisory firm.

Business Impact

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Business Data Challenges

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