Paradatec Inc., a provider of AI (artificial intelligence)-based document analysis technology for the lending and real estate industries, announced the availability of a new analytics module that automatically compares system-of-record data from different systems with extracted and calculated data from source documents and datasets.
Returning fully traceable and auditable results, the analytics module in Paradatec’s AI-cloud platform aims to improve overall data accuracy and flags unusual data, therefore enabling organizations to significantly reduce labor costs, improve the quality of loan files, and enhance fraud detection capabilities.
“Our new analytics module is another example of our ongoing investment to deliver customer-requested practical, tangible innovation for our valued clients and the mortgage industry," Neil Fraser, director of U.S. operations at Paradatec, said in a release. “Customers have told us they are investing in their own capabilities or third-party systems to automate complex workflows, and they are depending on Paradatec to help them identify, cleanse and translate the data those workflow automation systems require.”
Manually comparing extracted data from multiple source documents to data stored in various operational systems is time-consuming, labor-intensive and prone to errors. Paradatec’s new analytics module reportedly bridges these gaps and accelerates the process of data harmonization by automating data review, enabling lenders and servicers to make informed decisions with confidence while streamlining their operations and lowering costs.
The analytics module uses a flexible rules engine, allowing clients to augment Paradatec’s rules with their own business rules for data comparison purposes. Leveraging Paradatec’s AI-based document classification, versioning and data extraction capabilities, the analytics module uses data from multiple sources and automates data calculations and comparisons. Once an audit is complete, whether within a process or for the whole file, Paradatec’s API returns results and data using configurable triggers and translation formats into customers’ downstream systems.