Intelligent document processing (IDP) is a good example of a proper use of artificial intelligence (AI). Human eyes can only detect so many details in documents before fatigue affects their performance, but AI can stay effective for endless periods. Not only does this make AI ideal for digitization but also document classification and workflow automation.
One benefit worth noting is that IDP helps boost conversion rates. Companies that utilize accurate data to render quality products and services will benefit from the accuracy and versatility of AI-powered document processing. This is especially the case for roles that regularly use financial data, such as invoice processing and claims management.
The extent to which conversion rates increase depends on factors like the business’s niche or industry. Regardless, in a climate that will only grow more competitive, no advantage is too little or too much. Here’s how IDP can give any business the edge.
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AI-Enhanced Accuracy
To err may be human, but to err is also costly. History backs it up.
- 2005: An investment firm in Japan lost an estimated JP¥27 billion (USD$225 million at the time) to a typo, selling 610,000 shares for 1 yen (less than USD$0.01) instead of 1 share for JP¥610,000 (USD$5,041).
- 2006: An Italian airline forgot to add two zeroes to its promo for flights from Toronto to Cyprus. Fearing a backlash, the company decided to honor the USD$39 price tag for the around 2,000 bookings already made, losing over USD$7 million.
- 2015: The U.K. government struck the wrong company from its registrar after the mistake boiled down to a single missing letter. As said company went under, the court found the government liable for about USD$17 million in legal fees.
Overwork may or may not have caused these multiple-digit mistakes, but they show the risk of failing to catch them beforehand. In addition to financial loss, there’s also a loss of consumer confidence over the ability to produce quality deliverables. Correcting mistakes takes away people’s precious time (and, sometimes, money) from tasks that matter more.
IDP solutions are less likely to suffer these issues for several reasons, all revolving around document processing using AI. Combining automation and machine learning, it can maintain a high accuracy rate for as long as there’s a steady supply of good data. High accuracy translates to a low risk of clerical mistakes and better customer service.
This isn’t to say that IDP can capture and retrieve data flawlessly. As it stands, AI tech still has kinks to work out and requires some human input to facilitate them. A claim of 100% accuracy often discounts external factors like shifting details in documents such as legal contracts and the way the user interprets the results.
Automated Data Extraction and Analysis
Nothing degrades business productivity more than repetitive manual processing. In this case, it can be going through every paper file and cataloging them. Studies have shown that doing the same task hundreds of times over negatively impacts work performance.
As a result, such tasks have or are undergoing automation. In this case, vital to document processing is a process known as optical character recognition (OCR). To be accurate, it’s more of a series of processes that turn images of hand or typewritten text into digital data. After scanning the document, OCR typically consists of three steps.
- Pre-processing: The system clears the unstructured document of impurities (e.g., dark specks, improper alignment) to increase the chance of recognizing the content.
- Text recognition: The system uses pattern recognition, breaking down characters into more identifiable forms to better identify them.
- Post-processing: The system searches the file for spelling errors and corrects them through a generated list of possible corrections.
Although OCR uses algorithms, the industry doesn’t consider it AI anymore. IDP is the next stage of its evolution, doing everything its predecessor can do but with the added benefit of analyzing the file’s context. It uses more advanced AI algorithms that primarily harness natural language processing and machine/deep learning.
Understanding the document’s content goes a long way in enhancing conversion. First, it allows IDP solutions to assume more tasks, such as classifying like files and generating data-driven insights to help with business decision-making. The setup also frees up some personnel for responsibilities that require human critical thinking.
Reduction in Processing Delays
Documentation overload is responsible for inefficiencies that lead to issues in delivering timely service, mainly in healthcare and insurance. According to a paper published in the International Journal of Science and Research Archive (IJSRA), the billions of files the two industries go through every year have resulted in:
- Claim disputes in 22% of healthcare billing outcomes
- Time-consuming corrections in 25% of insurance claims
- Paperwork consuming 40% of a healthcare professional’s time
- Losses of more than USD$80 billion to fraudulent insurance claims
Among these outcomes, perhaps the most adverse is a delay in processing claims. A lack of an automated document management system prolongs processing times by weeks or even months. Industry leaders know that time is of the essence here because most claims involve people currently undergoing treatment or whose injuries render them unfit for work.
Such delays don’t inspire confidence among consumers, especially if people don’t receive routine updates. Imagine waiting for weeks or months for word about a loan application or medical claim, only to be denied due to error-laden medical documents. It becomes worse if the errors are committed on the insurance agency’s end.
IDP is the best technology for dealing with documentation overload. Aside from converting paper files into electronic ones, it can also configure their movement to the correct party or process across the document workflow. Files with discrepancies can be automatically flagged and forwarded to a staff member for manual review.
Because IDP uses machine learning, an IDP platform can continue to improve using data from previous outcomes. Granted, it won’t reach 100% due to external factors mentioned earlier, but it will grow more reliable over time.
Conclusion
Every business should invest in an IDP system, as it makes document-heavy processes more seamless while requiring minimal oversight. The result is improved customer experience, a key factor in boosting a business’s conversion rate, no matter the industry.
