OCR … OC WHAT? What is Optical Character Recognition?

OCR OC WHAT What is Optical Character Recognition Informed

Optical Character Recognition or OCR is a technology enabling computers to “read” text off of documents. It is usually priced per page and is often riddled with mistakes. The poor accuracy makes it of little practical value for organizations looking for a clear picture of the data in the documents. In order to get the true picture, you often need a team of people. This team, also known as “human in the loop (HITL)” augments the accuracy and completeness of the result. And those humans receive a salary, so costs increase.

OCR has a long way to go, especially in the auto industry where forms change constantly and new document types are added regularly. However, by combining state-of-the-art OCR technology, with applied intelligence ”learned” from a purpose-built large language model (LLM) and subject matter experts, solutions like InformedIQ can intelligently “read” the document, turn it into actionable insights and perform complex calculations.

It is important to accurately parse the data. With the power of AI, you can get accuracy rates of 99% on known document types. For lesser known document types, accuracy rises quickly over time. Until the “machine’s” accuracy is where you need, you control, based on your lending policies, which documents you feel comfortable accepting and others requiring manually review.

Proof of Income documents are so widely used that AI models have learned them well. They can extract data, classify the document, compare the data and determine if the document is based on a fraud template found on the dark web. In addition they calculate income based on your credit policies.

A More Advanced Solution

Quickly processing a consumer or auto loan is the ultimate goal of most lenders. So the more documents that can be instantly verified, without human input, the sooner the lender can make their decision. Lenders can “automatically” pass a loan that historically would have needed a person to manage the entire process. That includes data entry, classification, verification, calculation, compliance, or a fraud alert. For the small number of documents that a do require human review, the system shows exactly what pieces of information that need review. This includes things like missing a signature or required document.

Image quality is another complaint about OCR providers. If the image quality is bad the accuracy will be low. And lenders don’t want to invest in new processes to manage this since more and more documents are becoming digitized. Offering better ways to instantly receive digitized documents improves the consumer and dealer experience and addresses image quality issues.

OCR also cannot determine loan defects. OCR capabilities with the addition of machine learning ensures contracts are complete and accurate. Solutions that collect clearer documents ensure the lender gets what they need without disrupting their current workflow and provides the best solution from one financial technology provider. More options lead to customized streamlined solutions with better business outcomes.

Transforming documents and data into actionable insights and decisions is no easy task but we simplify it for you. Our machine learning models trained on millions of documents to support the auto, consumer lending, and mortgage loan industries.

Learn more on how to reduce front-of-house labor costs while improving accuracy and reducing errors. Request a Demo.

author avatar
Adine Deford VP of Marketing
Adine Deford is the VP of Marketing at Informed.IQ. She has more than 25 years of technology marketing experience serving industry leaders, world class marketing agencies and technology start-ups.

New: American Banker - Sharing information = best defense against AI fraud