Does your OCR technology make sense of the data that is extracted? Traditional OCR technology provides less accuracy as it does not understand what is being extracted and hence a considerable amount of errors occur. To remove such errors it needs manual fixing which is time-consuming and will require significant resources. The AI-powered Infrrd OCR removes all such difficulties by implementing machine learning algorithms to understand the data that has been extracted and improves the output automatically.
Thinking About Switching From Your Current data extraction technology To an intelligent one?
Here Are 7 Questions To Consider First:
- How Accurate is your OCR Data Extraction?
When it comes to choosing an OCR app, accuracy is one of the most important criteria. Infrrd OCR is different from other OCR software as it works on significantly improving the accuracy of the extracted data. It achieves this by learning from existing business records and extracting data in categorical context using machine learning and NLP. Infrrd OCR thus fills in the missing gaps that traditional OCR engines miss and fine tunes the extracted results. - How Cost-Effective and Time-Saving is your OCR Reader?
Most companies, even after implementing an OCR, spend a lot of time and labor on manual tasks. Infrrd uses machine learning and NLP to understand the extracted data and make sense out of it. Hence, it saves a lot of time and cost which would be otherwise be spend on manual data entry tasks. - Does it Auto-Classify the Documents?
When dealing with huge volumes of documents, it gets difficult to classify them as invoices, receipts, contracts and so on. Using Natural Language Processing, Infrrd OCR is capable of automatically classifying and sub classifying these documents and having them neatly stacked by different categories. - Does it provide a correction module?
Since we encounter different types of documents, the quality of each varies. So there are chances that the OCR application extracts wrong information from low-quality documents. Therefore, to avoid such errors in future, Infrrd provides a correction module that allows users to rectify the errors. - Can it extract information from logos?
Receipts & invoices come in different formats. Some have the merchant names while others may have only logos instead of actual names. Our deep learning based logo detection algorithm is able to identify the merchant names across the globe even if the documents just contain logos or trademarks. - How does your OCR scanner handle long receipts?
Not all receipts are of standard size. Extracting information from longer receipts has always been a problem for traditional Optical Character Recognition platform. Infrrd OCR tool has the ability to implement image stitching for long receipts. Our computer vision and image processing technique stitches together individual images, each containing a partial view of the document, into a mosaic view of the entire document. - Can you customize your OCR specifically for different needs?
Most of the tools are generic and may not be specific to your needs. Infrrd ensures that we customize the OCR specifically for different needs. Infrrd provides their assistance in all phases, including pre-project consulting and on-site requirements analysis, implementation and testing, on-site deployment, and technical support. Hence before you get a new OCR technology or change your existing one consider the 7 questions provided above. Analyzing requirements and a perfect fit in terms of a solution are imperative for a successful project execution. Chat with us at www.infrrd.ai to schedule a meeting to discuss further.
FAQs
A pre-fund QC checklist is helpful because it ensures that a mortgage loan meets all regulatory and internal requirements before funding. Catching errors, inconsistencies, or compliance issues early reduces the risk of loan defects, fraud, and potential legal problems. This proactive approach enhances loan quality, minimizes costly delays, and improves investor confidence.
A pre-fund QC checklist is a set of guidelines and criteria used to review and verify the accuracy, compliance, and completeness of a mortgage loan before funds are disbursed. It ensures that the loan meets regulatory requirements and internal standards, reducing the risk of errors and fraud.
Using AI for pre-fund QC audits offers the advantage of quickly verifying that loans meet all regulatory and internal guidelines without any errors. AI enhances accuracy, reduces the risk of errors or fraud, reduces the audit time by half, and streamlines the review process, ensuring compliance before disbursing funds.
Choose software that offers advanced automation technology for efficient audits, strong compliance features, customizable audit trails, and real-time reporting. Ensure it integrates well with your existing systems and offers scalability, reliable customer support, and positive user reviews.
Audit Quality Control (QC) is crucial for mortgage companies to ensure regulatory compliance, reduce risks, and maintain investor confidence. It helps identify and correct errors, fraud, or discrepancies, preventing legal issues and defaults. QC also boosts operational efficiency by uncovering inefficiencies and enhancing overall loan quality.
Mortgage review/audit QC software is a collective term for tools designed to automate and streamline the process of evaluating loans. It helps financial institutions assess the quality, compliance, and risk of loans by analyzing loan data, documents, and borrower information. This software ensures that loans meet regulatory standards, reduces the risk of errors, and speeds up the review process, making it more efficient and accurate.
