Modern business means an ever-growing amount of digital information that, until recently, has been the job of a few poor souls to manually process into proper formats, analyze, and leverage in operations. Intelligent document processing (IDP), the caped hero, swooped in to help save employees from the painstaking process of converting unstructured data into actionable information.
The goal of IDP is to take data that lacks a defined format, such as information in emails, invoices, and contracts, and efficiently transform it into data that is organized in an easily searchable format, such as transaction records and customer information, so it’s easier to leverage and analyze. Reports show that 80% to 90% of data is unstructured, and only 18% of businesses utilize this data due to the inherent challenges that come with it. IDP helps organizations overcome these challenges.
While basic IDP has proven to be a transformative force in document processing, the rise of artificial intelligence (AI) has further increased its capabilities.
In this post, we look at the limitations of traditional IDP and how AI is pushing the envelope.
The Limitations of Traditional IDP
Traditional IDP works more as robotic process automation (RPA), which is based on a set of rules and templates to replicate manual data extraction. While it is still undoubtedly better than having someone spend hours on tedious work, traditional IDP is only as good as the rules that run it.
Because traditional IDP solutions work based on rules and templates, they struggle with unstructured data outside given parameters. That means documents with different layouts, languages, or any other variable need their own set of templates and rules – creating the same problem of time-intensive human processes eating up someone’s day.
Unstructured – and even semi-structured – data is, by definition, unorganized and non-uniform. This lack of uniformity creates a bit of a moving target when it comes to leveraging traditional IDP. Certain rules can limit the effectiveness of accurately extracting all relevant data from more complex content. This in turn results in exceptions that require human intervention to resolve.
At the end of the day, IDP is going to save businesses from wasting time and resources. However, traditional IDP can only do so much. That’s where AI-powered IDP steps in and steps up.
How Does AI-Powered Intelligent Document Processing Work?
AI-powered intelligent document processing solutions don’t reinvent the wheel, but they do supercharge it. By using machine learning, IDP technology is able to be trained and adapted to certain situations. The more it’s used, the better it becomes. This ability, in conjunction with the tools classic IDP utilizes, has resulted in a far more comprehensive and effective tool.
Taking a step back, it’s important to understand machine learning to better understand how effective an AI-powered IDP system can be. Machine learning is a subset of AI that allows it to analyze data and algorithms to identify patterns, and thus learn from experience and training sessions, in a way that’s very similar to humans. In this way, IDP is able to break the shackles of rules and formulas, as it can take what it knows and apply it to novel data. The more it does this, the more it improves and thus has the ability to push data-structuring to maximum efficiency.
While machine learning tools can be trained to perform tasks effectively and adapt based on experience, natural language processing (NLP) uses machine learning to understand and communicate human language. This is critical when it comes to IDP applications because it means that the AI is not limited to understanding clean text in a single language. That’s to say that NLP not only helps AI understand multiple languages, it can also help AI understand sentiments, colloquialisms, and all sorts of other elements of human language that simple rules and formulas never could.
Key Differences Between Traditional IDP & AI-Powered IDP
What specifically separates traditional IDP and AI-powered IDP is the machine learning that allows it to learn and adapt as it interacts with data. While old-school IDP was limited to rigid rules, IDP utilizing AI is able to learn and logically apply what it knows to new situations.
Flexibility & Adaptability
As we’ve highlighted, machine learning in AI-driven IDP has unlocked a new level of flexibility and adaptability when it comes to data structuring. Abnormal formats, different languages, and brand-new document types all become manageable assets without the need for extraneous human intervention.
Where traditional IDP would stumble when coming across any unknowns, AI-driven IDP has the power to problem solve. And better yet, the more it does this, the better it gets at completing tasks. Not only can it take on new challenges, it can continuously learn how to improve processes it already knows how to complete.
Accuracy & Efficiency
As discussed, traditional IDP still requires an abundance of human intervention — both in validating low-confidence results and in the constant reworking of rules to reduce said results. AI-powered IDP solves all of that. Because of its ability to be trained, AI-powered IDP reduces error rates and becomes more efficient, resulting in faster processing times.
Scalability & Productivity
With traditional IDP, limitations scale with any increases in document volume. So, the more documents, the more need for human intervention in data validation and formula-tweaking. These are the types of circumstances that create scalability issues and bottleneck operations.
Once again, AI-powered IDP is here to save the day. The issues that hamper traditional IDP aren’t issues when it comes to AI-powered IDP. Consistency is key, and AI-powered IDP is able to maintain efficient processing, so employees can keep productivity levels up even as document volume grows. In a recent survey, 64% of businesses said they expect AI to increase productivity and 42% believe it will streamline job processes for complex tasks.
3 Benefits of AI-Powered IDP for Businesses
The list of AI-powered IDP benefits for businesses is a long one. Here are a few key ones:
- Increased operational efficiency and cost savings
- Improved compliance and risk management
- Better customer experience and satisfaction
A study recently published by Forbes not only found that 64% of businesses expect AI to increase productivity, but that 59% expect it to reduce costs, 64% believe it will improve customer relationships, and 38% are already using it for risk management.
An example of these benefits can be found in almost any department in almost any organization in almost any industry. After all, AI-powered IDP solutions can process a wide range of documents and data – from invoices to proof of income files to typical correspondence documents, all of which are processed autonomously in record time with unmatched accuracy.
3 Intelligent Document Processing Applications
For IDP to be valuable, it has to be able to perform activities that are a regular part of day-to-day business.
Here are some of the most common IDP use cases:
Invoice Processing
Using IDP for invoice processing means important information, such as vendor details, invoice data, and line items, are all automatically captured in record time. This not only speeds up the accounts payable process but also reduces the occurrence of errors, improving overall invoice processing accuracy.
Customer Onboarding
Customer onboarding is another process that requires a large amount of document collection, verification, and management. As a business, you can never have too much information, especially when a technology like IDP software can quickly and automatically parse through all of the key data and convert it into an easily accessible and well-structured format. AI-driven IDP takes unstructured information and plugs it in where needed to simplify client information validation, streamline payment processing, and decrease the time it takes for businesses to deliver value to their clients.
Claims Processing
Claims processing requires insurance companies to handle a variety of documents, including claims forms and medical records. Manually managing and processing these types of documents inevitably results in slow response times and a slew of other issues. When looking at AI’s integration into medical claims processing, Forbes found that many denials were the result of errors and time limitations involved with manual processing. With the adoption of AI, Forbes reports that claims processing should “benefit from faster approvals, reimbursements, and overall turnaround times.”
Step Into the Future with MetaSource
It’s no secret: AI is here and it’s opening the door to a near-endless number of improvements throughout multiple business sectors. By upgrading to an AI-powered IDP tool, the time-wasting, resource-depleting era of manually structuring your data is soon to be a memory of the past. With over 30 years of intelligent document processing experience, MetaSource can help your business gain a competitive edge by eliminating manual data entry tasks, increasing productivity, and reducing costs.
Let MetaSource help your business step into the future and reap the benefits of top-tier intelligent document processing solutions.
Your Guide to Intelligent Document Processing
Uncover all there is to know about IDP solutions that combine advanced technology and human expertise to deliver invaluable benefits.
