Textual data has always been an essential element in the finance sector as it facilitates timely decisions. However, tapping into textual data for insights is a challenge because it is mostly unstructured.
Unstructured data in financial institutions is text-heavy, like the data from scanned loan documents. Therefore, to analyze textual data, it has to be extracted from the documents. The manual processes currently in use are time-consuming, expensive, resource-intensive, and often delivers inaccurate data. Hence, many financial institutions are looking to automate the process of extracting textual data from scanned loan documents.
However, a standard automated, rule-based solution is not the answer as loan documents are in diverse formats or templates. Therefore, an intelligent solution that can handle various formats and deliver analytics-ready integratable data is the need of the hour.
Straive’s text intelligence solution can help financial institutions overcome the challenges associated with extracting data from text-heavy documents. Our solution ensures:
Accurate data
Faster data processing
Improved employee productivity
Cost savings
Enabled by the Straive Data Platform (SDP), Straive’s text intelligence solution helps customers by extracting, enriching, and delivering data and actionable insights from text-heavy documents in any format (PDFs, emails, Word files, and scanned images/documents).
Our solution helps enterprises in their knowledge discovery processes by ingesting source documents, leveraging cognitive technologies, and the inputs of SMEs. The result is highly accurate structured datasets.
Download our text intelligence case study to learn how we helped a full-service bank in the US with over 150 branches accelerate data extraction from complex documents with Straive’s automated text intelligence solution.
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