Project Overview
Tennessee-based property data solutions provider
Real Estate
Business Needs
A Tennessee-based property data-solutions provider needed accurate, current, and comprehensive property information for its customers. Data capture from thousands of transactional and other property documents including assignment, discharge, foreclosure agreements, warranty deeds, contract sales, mortgages, auctions, etc. available in multiple formats was a challenge for the company.
Also collecting data from online sources such as property websites across three states and 195 counties required resources and infrastructure.
To manage voluminous data aggregation activities and ensure that the quality, relevance, and currency of data were constantly maintained, the company partnered with HitechBPO.
The Challenges
- Domain expertise and a deep understanding of property terminology to identify and capture relevant property data points from thousands of property records
- Capturing relevant data points from the unstructured documents with data points positioned differently in document
- Decoding data from handwritten documents
- Different counties and states had different requirements in terms of regulations and compliances
- Maintaining data security and confidentiality of Property documents that contained sensitive property information
Solutions and Results
Want to enhance your property database?
Speak to us today- A workflow was designed with a blend of manual and automated data capture and validation processes for the ongoing capture of huge volumes of data points from multiple online and offline sources.
- A team of experienced data specialists was hired, and capabilities were built for processing hundreds of property document types.
- The team was trained in understanding property types and associated terms, comprehending complex property documents, state and county compliances, regulations, etc.
- Data extraction
- Data were extracted manually from documents shared by the client in pdf, word, or image formats and input into a robust database in CSV format.
- Missing data fields were added by doing web research.
- Data were standardized to maintain format consistency.
- Data Collection from online sources
- Custom crawlers were developed using Python-based scripts and were trained to recognize and capture specific property data points.
- The crawlers fetched property records from online property websites across three states and 195 county websites and imported them into a robust CSV database.
- Audit and Quality Check
- Ran a double-layered audit to ensure the accuracy of records.
- This included manual quality checks based on random sampling and rule-based validation for the complete dataset.
- Validated and standardized data captured from online and document sources was uploaded onto the client portal using Access DB through secured credentials.
- Tools and Technology Used: Python, Scripts, and Macros
Business Impact
40% increase in operational profitability
4M+ records pushed into the database annually.
99% accuracy of property data aggregated.
