Document Validation for FinServ Risk Management
Table of Contents
Financial Document Recognition
The financial services sector is increasingly recognizing the importance of data quality for risk identification and compliance management. Deloitte listed the major challenges facing QA teams in the financial sector, recommending that using automation to assist in quality control processes “can enable better controls over completeness and timely resolution.”
Still, much of the data that fuels organizations like asset management firms and mortgage servicers is trapped inside documents. From handwritten forms and pdfs to driver’s licenses and payment letters, financial documents are the most subject to error or corruption and the hardest files to extract structured data from.
Financial documents are the most subject to error or corruption and the hardest files to extract structured data from.
Thus, advanced document recognition capabilities are critical to the success of data quality initiatives. While Optical Character Recognition (OCR) has been around for years, new technologies are layering automation, validation, and version control into their document validation tools. These innovations help financial institutions grapple with rapidly increasing data volumes and complexity.
Here’s everything you need to know about the role of document recognition in enterprise data validation efforts.
The Power of OCR and ACR in Data Extraction
![insurance agent helping clients](https://basecapanalytics.com/wp-content/uploads/2023/10/Insurance-1024x640.png)
Optical Character Recognition (OCR) and Advanced Character Recognition (ACR) are essential technologies for converting various text formats, such as scanned documents, PDFs, and handwritten notes, into machine-readable data. BaseCap Analytics integrates with sophisticated OCR and ACR capabilities that go beyond simple text conversion. Combining document recognition with a sophisticated data validation engine allows financial institutions to extract and index vast amounts of data efficiently. Often, this results in lower QA/QC costs and better scalability as data volumes fluctuate.
Combining document recognition with a sophisticated data validation engine allows financial institutions to extract and index vast amounts of data efficiently.
1) OCR for Image Recognition
BaseCap’s OCR processes can handle complex datasets, such as mortgage documents, tax forms, and contracts, which are common in the financial services sector. This capability is crucial for institutions that manage high volumes of documentation and need to process this information accurately and swiftly.
Read: Unlocking Self-Serve OCR
2) ACR for Enhanced Accuracy
Advanced Character Recognition (ACR) further improves the accuracy of data extraction by recognizing characters in more challenging scenarios, such as distorted or low-quality images. This ensures that even the most difficult-to-read documents are accurately digitized.
![](https://basecapanalytics.com/wp-content/uploads/2024/04/data-health-1024x683.jpg)
To avoid penalties, fees, and complaints to the CFPB, banks leverage BaseCap’s automated compliance management capabilities.
Data Transformation and Automation
Extracting structure data from documents only takes you so far. For example, a mortgage servicer may store a hundred documents for one loan. Once they’ve run ACR on those docs, they still need to ensure the data matches across those documents and maintain version control as they move between origination and servicing systems.
That’s where data transformation and workflow automation come into play. By transforming, or standardizing data for comparison to a system of record and then automating that comparison, enterprises can improve the speed and accuracy of their QA functions. This is particularly important for firms that must meet strict regulatory standards.
1) Data Transformation
After extraction, data often needs to be cleaned, normalized, and structured. The BaseCap platform provides robust tools to transform raw data into structured formats that can be easily integrated into existing systems. This transformation is critical for ensuring that the data can be compared across systems.
2) Automation Capabilities
Automation eliminates the need for manual intervention in rote processes, speeding up workflows and reducing human error. BaseCap’s platform automates repetitive tasks, such as data entry and validation, allowing staff to focus on more strategic activities.
Conclusion
Enterprises looking to lower QC costs and create new competitive advantages will seek to combine the power of document recognition technology and data validation software. With the right technology stack, financial services organizations can substantially lower QC costs while improving accuracy in risk management processes.
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About BaseCap
BaseCap is the intuitive data validation platform that operations teams use to accelerate compliance and risk management processes.
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