With paper documents still used in over 60% of business processes, corporate technology and data leaders seek automation to transform their workflows. While rule-based RPA and OCR technologies alone can achieve some improvement, they cannot handle semi-structured and unstructured data. Intelligent document processing (IDP), however, can — considerably accelerating automation efficiency.
In our latest webinar, WorkFusion’s CTO Peter Cousins and Everest Group Partner Anil Vijayan reflect on the untapped potential for organizations to integrate IDP into new or existing automation layers. For example, with IDP, companies “cut in half — or more — the amount of time it takes to deal with email communications with their customers, which can be an enormously time-consuming endeavor if you’re a large bank,” Vijayan said.
If you missed the live webinar, you could still watch it on demand. Here are the five most important takeaways:
IDP complements your automation stack, enabling you to process complex documents
Technologies such as RPA, OCR, AI, and IDP do not necessarily compete, but rather they complement each other to provide robust automation results:
“IDP is essentially a solution that allows you to extract specific data items from documents using artificial intelligence, machine learning, or deep learning techniques. These documents are usually text documents such as forms, invoices, etc., typically stored in businesses as scanned images.”
IDP is different from RPA: RPA is rule-based and works with structured data, and IDP uses AI to work with unstructured data. RPA can complement IDP by processing this extracted data.
Enterprises adopt IDP at an accelerated pace
According to Vijayan, even though COVID-19 affected most markets, automation — and IDP in particular — is expected to accelerate in a post-COVID environment.
Banks and insurance companies are currently the biggest IDP users, followed by healthcare and manufacturing, with industry-specific use cases most deployed.
How to choose an IDP solution
Everest highlights multiple criteria for consideration (but cautions that what might work for one organization or process may not be the best solution for another):
- Product roadmap
- Workflow capabilities
- Pretrained models
- Analytics and metrics required
WorkFusion believes pre-trained models are one of the most crucial considerations: Not only do they significantly reduce time to value, but they deliver superior automation rates out of the box.
IDP solutions must be sustainable
Assuming companies deal with a growing number of documents each year, often with unstructured data, and ever-changing regulations, document processing can become quite cumbersome to maintain over time.
That’s why it’s important to select an IDP solution that learns and improves continuously. For example, a comprehensive solution enables human-in-the-loop when necessary. Analytics help ensure that automation results are constantly increasing, not decreasing. The right solution must be versatile, with an open framework for automation to adapt to new requirements. Lastly, the ability to use the knowledge accumulated through all model deployments via federated learning guarantees that new regulations do not go unaddressed. These are all strengths that WorkFusion’s IDP solution offers.
How WorkFusion Network put customer experience to work
Although companies have achieved great success with automation, we see there are still a few challenges across industries. First, there is the “cold start” problem and the “long tail” problem. Then there is managing the pace of change. Finally, there is fragmentation and friction — but these separated areas of expertise represent opportunities for growth both within and between companies. To address these problems, we offer a new approach, which we call the WorkFusion Network.”
This is a technique for introducing new solution content to customers in real time, so they can find new use cases that are packaged and ready to go with a one-click install into their environment. This isn’t just the overall use case, but an open system. So, you can see how it works and reuse individual components within it. This helps you get started much faster with pre-trained models and pre-built use cases and all of their components —like the workflows, the tasks, the machine learning models, the data connectors, and the data itself.
WorkFusion provides a federated learning engine that can offer synchronized training across multiple organizations to address this long tail problem. Having a place where the industry can collaborate to curate knowledge graphs for a particular domain or look at industry benchmarks for automation metrics or business outcomes can be very helpful. This is the WorkFusion Network.
This article covers only a few highlights from our conversation with Everest. We recommend watching the full webinar from our library of on-demand webinars. Also, in a bonus Q&A, CTO Peter Cousins answers more questions about IDP submitted by webinar attendees.
Feel free to contact us any time to learn more about how our innovative solutions can meet your needs.