The Healthcare Industry is Prime for Curing the Paper Problem with Context

The Paper Problem

Despite trillions of dollars of investment and decades of effort, healthcare still has a paper problem and most likely will for decades to come. 

One survey reports that 90% of healthcare providers still use paper and manual processes for patient collections, resulting in slower and less successful payment collection. In another study, 76% of healthcare organizations surveyed, that use a common EHR platform, still print consent forms instead of using electronic signature applications. And, according to an analysis by an IT consulting firm, the average 1,500-bed hospital prints 8 million paper pages a month, if that hospital is still using printed consent forms instead of electronic signatures.

Simply capturing the data or automating manual tasks with legacy data isn’t enough to significantly reduce the burden of paper on the back office. People are still struggling with finding the information they need.

It’s no secret that search engines and digital assistants, like Google and Alexa, have fundamentally changed the way people access information and get answers to their questions. It should then be no surprise that workers are being conditioned to search for exactly what they want and are now expecting answers tailored to their specific needs. Yet, these same semantic technologies that are powering search engines and digital assistants are still underleveraged in the workplace.

Building Context with Intelligent Document Processing (IDP)

IDP is a software service that extracts important data from digital and physical documents through data capture technology. Typically, the steps consist of ingestion, capture, classification, extraction, validation and exportation of the data into another system. This is often the first step to any digital transformation or hyperautomation project and it makes the data from documents usable, searchable and actionable. 

If we take IDP solutions a step further and use the data that is discovered, data scientists can create knowledge graphs to optimize data and create better outcomes within healthcare (and other industries). A knowledge graph represents a collection of entities, or data of interest, along with how those entities are related and information about them, known as metadata. Today, knowledge graphs are used extensively in anything from search engines and chatbots to product recommenders, cognitive automation and other AI-based services. They are the foundation for building context with your data.

While the use of linked data and knowledge graphs have been slowly growing in more sophisticated healthcare organizations, most of the focus has been around trying to help with making diagnosis and predicting outcomes. But advances in AI, semantic technologies and enterprise knowledge graphs hold the promise of radically transforming the back office of healthcare. Context holds the power to make healthcare more efficient and lower the costs of healthcare.  

As advances in AI have made search engines smarter, these breakthroughs have been fueled by ever-expanding knowledge graphs. Healthcare organizations can meet the growing productivity challenges by building and integrating their own knowledge graphs throughout the organization. Let’s look at several examples.

Use Case: Employee Onboarding

By 2030, the World Health Organization predicts a worldwide workforce shortage of about 18 million healthcare workers. Organizations are going to spend an increasing amount of effort and resources on recruiting and onboarding new hires. Welcoming new employees involves vast amounts of administration and record-keeping. Automating these processes lets you focus on finding the right employees for your healthcare organization without the hassle of lots of paperwork. Automating critical onboarding tasks will be vital.  

Collecting federal and state-specific government new hire documents from employees and validating against application data and past work history.

Before hiring any healthcare professional, it is an absolute must to conduct a sanction check. This is the only way to prevent hiring sanctioned individuals. Pre-employment background checks require validating data across multiple data silos. Knowledge graphs can be used to link data across state, federal and private data repositories to create a 360 degree view of the prospective employee backgrounds.

Use Case: Mailroom Automation

Many healthcare organizations are inundated with both physical and electronic mail, including invoices, contracts, administrative correspondence and many other types of documents. Digital mailroom automation can increase efficiency while delivering or processing mail and email quickly. 

Intelligent document processing solutions can not only identify the type of mail it is (invoice, lab results, records, etc.) but it can extract the data needed from that document type to expedite the delivery of it. 

When connections and semantic data is applied to the various types of mail, recipients can prioritize the type of mail it is to improve efficiency and boost customer experience. For example, patients can get test outcomes from outside labs faster and receive expedited treatment.

Use Case: Electronic Medical Records (EMR)

The EMR Adoption Model measures, from stage 0 to stage 7, show the degree to which a hospital system adopts EMR functions. Organizations that are not completely paperless cannot meet HIMSS Stage 7, which requires all clinical documents to be available electronically within 24 hours of creation or receipt. Due to the amount of paper still in use, most hospitals are in Stage 5 and Stage 6.

In the rush to be paperless, many hospitals have adopted a point of service (POS) approach to scan the documents into the EMR in near real-time. While this approach has helped to eliminate paper and expedite the creation of a single EMR, critical clinical information is now sitting unstructured and dark in the EMR – unavailable to the systems that need it to derive insights or create better patient outcomes.

By applying a semantic data-driven approach (using knowledge graphs) to capturing these clinical documents, we can map them to clinical taxonomies to understand the entities and relationships within the documents. This allows us to apply meaning to the entities and data elements and link to related data within the EMR and other data sources ultimately allowing us to create an enterprise knowledge graph on the patient. Having a 360-degree view of the patient can fuel a number of healthcare initiatives like Patient Engagement, Population Health Management, Precision Medicine and clinical decision-making.

The Bottom Line

The ramifications for using legacy systems, too much paper and resisting modernizing without context for your data can be steep. Not only in terms of costs but for patient care, employee well-being and the environment (beware: these statistics for 2022 may change your mind on why printing less paper will benefit the world). 

The first step towards automation should be done with the foresight of using an intelligent document processing solution that uses the power of AI and knowledge graphs to build context with your data. It’s ok to start small or even with one department to test the outcomes and value, just start.

Ike Kavas Wins “OCBJ Innovator of the Year Award 2022”

We are thrilled to announce that Ike Kavas was one of five Orange County innovative leaders to win this prestigious award last week. Ike’s entrepreneurial drive fuels him as a passionate technology innovator, AI and machine learning advocate, speaker and customer-obsessed trailblazer.

“It’s an honor to be recognized by the local community, judges and Orange County Business Journal as an Innovator of the Year,” said Ike Kavas. “The award comes at a time when Ephesoft was recently acquired by another Orange County-based company, Kofax. One of the highlights of the acquisition was our technology platform, including our new Semantik AI Engine™. I’m looking forward to helping incorporate Ephesoft’s innovative technology into the Kofax family of products to help customers with their hyperautomation journey in my new role as SVP AI & Data Science Innovation.”

As Ephesoft’s founder and leader since its inception in 2010, Ike has pushed the boundaries of innovating what was once a stagnant industry – document capture – into an AI-powered technology that is necessary to build the foundation of any digital transformation or hyperautomation initiative. He has taken a common process that is often complicated, time-consuming and inefficient and automated it, building AI into its inner workings to make it simple, fast and efficient. Workers no longer need to manually enter data, worry about mistakes or duplicate their efforts. Ephesoft is a solution that captures data, classifies it (organizes it), extracts the data, allows validation if necessary and exports that data into any other system or repository. IDP enables companies to be data-driven, quickly and without much effort. 

This past year demonstrated significant, breakthrough technology for Ephesoft’s intelligent document processing platform, Transact. The latest version of Transact features cutting-edge AI, computer vision and deep learning neural network technology, named Semantik AI Engine, which powers data extraction from both known and unknown document types. The Semantik AI Engine technology will change the industry for the better and will turn the world of automation into a world of data-driven companies across countries, languages and use cases.

One unique feature using the AI engine, Universal Document Automation, allows document automation out-of-the-box without the need to create a template, train the system or configure the solution. This has long been a challenge for many organizations because most document capture applications require major setup and configuration with templates. In fact, in a recent webinar, over 72% of businesses (in a survey to over 300 webinar attendees) responded that they had unknown documents. Universal Document Automation can automatically detect and extract critical document data, data mine and opportunistically explore any data from any document without configuration and enable data extraction projects that would otherwise be too costly or time-prohibitive. 

Another innovative capability of the new Semantik AI Engine is the Document Design Accelerator, which significantly speeds up the process of building index fields and extraction rules for new, known document types. All that is needed is to supply a sample document to the Document Design Accelerator and it will analyze the content and automate the conventional process for enumerating index fields and creating extraction rules. Results from the Early Adopter Program showed that setting up new documents was expedited by up to 90%. In simplified terms, processing documents has accelerated getting the data companies and the public sector need to be competitive, increase growth and make data-driven decisions.

A major success, which contributed to an overall sales growth of 25%, was the excitement around advanced cloud-native, AI-enabled handwriting recognition and extraction capabilities – Advanced Handwriting Recognition. The challenge is that many enterprises have to process large amounts of handwritten documents – from insurance claims to banking and college applications to customer complaints to government census documents. Entering this data manually means long processing times, human errors and ultimately a competitive disadvantage. Other solutions typically get less than 30% accuracy. Ephesoft’s innovative engineering team developed a way to read both printed and cursive writing at an average accuracy of 88% out-of-the-box, including handwriting that is not easily legible by human review. 

In summary, these are just some of the major ways that Ike Kavas is leading innovation in hopes of making customers able to scale, grow and exceed customer expectations. The culmination of Ike’s efforts and leadership enabled the company to grow during turbulent pandemic times. The future is bright for both Kofax and Ephesoft customers! 

Read the article here.

Making the case for IDP in Insurance: Mind-Boggling Statistics

Over the years, the insurance industry has developed a reputation for processing claims, reviewing documents, and performing virtually every other essential business task at a snail's pace. 

However, many people are unaware of how inundated with paperwork the entire industry is. This inefficiency pandemic impacts companies operating within every segment of the insurance industry, including the following:

  • Health
  • Home
  • Auto
  • Pet
  • Casualty
  • Travel
  • Life

The insurance industry is intrinsically slow and inefficient due to its business model. Before insurance companies deliver payment to providers or policyholders, they must verify the claim's legitimacy. This requires them to request significant amounts of paperwork from healthcare providers, medical treatment facilities and, of course, the policyholders or their beneficiaries.

For years, insurance companies, and the clients they serve, have had little recourse in dealing with these inefficiencies. Fortunately, the development and evolution of intelligent document processing (IDP) technologies provide insurance companies with a viable solution for clearing up the backlog of paperwork. IDP technology is software that can efficiently process documents and structure the data they contain into a digestible format. In turn, this can decrease claim processing times, reduce a company's reliance on labor-intensive manual processes and optimize organizational efficiency. 

Below, we make a case for IDP in insurance by highlighting some truly mind-boggling statistics and facts about this massive industry. 

5 Statistics that Demonstrate the Need for IDP in Insurance 

In recent years, it has become clear that the insurance industry's status quo of relying on labor-intensive and inefficient manual processes is untenable. Insurance companies that do not pivot and aggressively pursue digital transformation will face shrinking profit margins, declining customer satisfaction and legitimate business continuity concerns. 

As part of this digital transformation, insurance companies must automate as many inefficient processes as possible. Automating processes at scale is known as hyperautomation. IDP in insurance will serve as the cornerstone of these hyperautomation and digital transformation efforts. 

Still not sold on the need for IDP in insurance? The five statistics listed below will undoubtedly change your mind.

1. Car Insurance Claims Can Take 30 Days or More to Process

On average, car insurance claims can take 30 days or more to process. In the meantime, the insured party could potentially be left without a functional vehicle. This could be financially crippling, especially if the policyholder does not have rental car coverage, as they must pay out of pocket for any transportation costs.

In some instances, settling car insurance claims can take much longer. For example, in California, insurers have up to 40 days to accept or reject a claim. If they accept the claim, they have an additional 30 days to issue payment. These excessive claim processing times disservice policyholders and tarnishes an insurance company's reputation. 

Intelligent document processing solutions can expedite processing claims and forms by automatically classifying and extracting the data needed, thereby reducing the time it takes to process by as much as 95%. 

2. The Top Insurer Writes over $100 Billion in Premiums Annually 

Implementing IDP in insurance can do much more than simply reduce processing times. It can also help insurers keep up with the rapid increase in demand for services. In our modern society, consumers want insurance-based protection for as many of life's unexpected challenges as possible. This has led to an uptick in the number of health and life insurance policies written each year.

In 2020 alone, MetLife, the largest health and life insurance company in the United States, wrote over $103.3 billion in premiums. If these premiums were written using antiquated practices, the entire process would be incredibly labor-intensive, inefficient and costly for the company. However, IDP technologies would allow the insurer to process policy documents much more efficiently and eliminate the amount of manual labor required to write these premiums. 

3. Health Insurance Claim Errors Lead to $17 Billion in Waste

IDP in insurance not only improves efficiency; this technology drastically reduces the frequency of processing errors as well. The following statistic about the insurance industry demonstrates how desperately companies need a mechanism for lowering claims errors. 

According to the American Medical Association (AMA), health insurance claim errors contribute to more than $17 billion in waste annually. The AMA found that the average error rate in claims processing among health insurance companies was a staggering 19.3%. This means that nearly one out of every five claims processed contained errors. 

IDP technology helps eliminate human-based errors from manual data entry by automating the data extraction from documents, which reduces wasted time. Insurance organizations can also increase their profit margins by reducing the amount of error-correction-related administrative expenses.  

4. The Insurance Industry Employs Nearly 3 Million People

Cumulatively, the various insurance industry sectors employ nearly 3 million people in the United States. However, like many other sectors, the insurance industry is contending with an ongoing talent shortage. Put simply, insurance companies are struggling to fill critical vacancies. In turn, this decreases the quality of service they can provide policyholders and exacerbates existing backlogs of physical and electronic documents. 

Organizational leaders in the insurance sector are exploring ways to resolve this talent shortage. In the meantime, insurance companies must find ways to do more with less without compromising service quality. IDP in insurance offers a viable means of accomplishing both of those objectives amid the current talent scarcity. 

5. IDP in Insurance Can Lead to 87% Faster Processing 

The concept of leveraging IDP in insurance sectors is not new. Several insurance companies have been using intelligent document processing technologies for years and have experienced significant efficiency improvements. 

For instance, a pet insurance company with an average claims processing time of 45 to 75 days implemented IDP technology several years ago. At the time, the company could only process 100 claims a day but was receiving many more than that. This created a backlog that would have been impossible to resolve using manual processes. However, implementing IDP technologies allowed the insurer to boost claim processing speed by 87%. The company was able to process seven times more claims per day, clear up the existing backlog, and reduce the average processing time. As an added benefit, the company was able to reduce the administrative costs associated with processing a claim, which led to better profitability. 

If insurance companies hope to thrive in this rapidly evolving industry, they must consider adopting IDP technologies. By doing so, insurers can experience similar benefits to those outlined above while simultaneously avoiding falling victim to the inefficiency trends that have plagued this industry for decades. 

Data being extracted with computer vision

Ephesoft is Selected in KMWorld’s AI Top 50 Companies in 2022

KMWorld 2022 AI 50 awardEphesoft has always incorporated AI into its technology but over the past year, the company has demonstrated new innovative AI uses and enhancements for intelligent document processing (IDP). The award comes on the heels of Ephesoft Transact’s recent release as AI took the main stage with our proprietary Semantik AI Engine, based on machine learning, computer vision and deep learning neural network technologies.

Using AI, computer vision, patented machine learning and proprietary classification models, Ephesoft’s customizable and scalable platform turns any document type into structured, actionable data to accelerate business processes and data-driven decisions. The Semantik AI Engine launched a new way to process unknown documents without any configuration and extract the data in seconds for discovery. To extract data from known documents for specific workflows, the AI engine enables a 90% faster setup. And this is just the beginning. The technology sets the stage for expanding hyperautomation initiatives globally in multiple languages.

“AI and a host of related technologies such as augmented intelligence, machine learning, deep learning, process automation, and natural language processing are being deployed in areas as diverse as supply chain management, manufacturing, healthcare, medical research, and financial services,” said Tom Hogan, Group Publisher, KMWorld. “With organizations recognizing the great potential of AI, it is not surprising that the market size is also expected to increase dramatically. As part of our efforts to focus attention on the innovative knowledge management vendors that are imbuing their offerings with AI and automation, in this issue, KMWorld presents the KMWorld AI 50: The Companies Empowering Intelligent Knowledge Management.”

Ike Kavas, founder and CEO, has AI and innovation deeply ingrained in his DNA with a data-driven mentality and a quest to help customers future-proof their business. “AI is the tool that we can use to optimize every day at work so we can live our best lives. Taking away tedious, manual processes with AI automation technology will give us the power to do what we do best – be human and thrive.” Don't miss Ike's spotlight article here!

document automation

The Inside Scoop: IT and Business Leaders Weigh In on IDP Needs and AI Plans

We recently hosted two webinars discussing the capabilities of the latest release of Ephesoft’s intelligent document processing (IDP) platform, Transact 2022.1. The release features our new, proprietary technology, Semantik AI Engine™, which powers Universal Document Automation as well as a new Document Design Accelerator making new document set-ups a breeze. These two breakthrough advancements were revealed and demonstrated in the webinars. We also asked our audience of 300 business and IT leaders from dozens of industries all over the world about their IDP needs and AI plans.

Let’s see how our attendees weighed in and learn how your organization compares. 

Could you improve your processes, enhance customer experience and/or respond faster to requests if you could access your data faster?

> Yes, by 100% - [40%]

> Yes, by 75% or higher - [15%]

> Yes, by 50% or higher - [35%]

> Yes, by 25% or higher - [10%]

> No, I don’t think processing documents faster will help me - [0%]

The bottom line: Hands-down, without any exceptions, attendees believe that if they could access and find their data faster, a better overall experience would be achieved. In fact, 90% of the audience thought it would be 50% or greater to see improvements. Since we know that transforming documents and information into data is the foundation for any automation or hyperautomation initiative with IDP, the conclusion is that great value can be unlocked with IDP technology.

Does your organization handle “unknown documents”?

> Yes - [70%]

> No - [20%]

> I don’t know - [10%]

The bottom line: After debuting Universal Document Automation, which can pull out key-value pairs in seconds, with no set-up or training involved, the majority at 70% of the audience knew that this would be a feature that applies to their business. The key challenge to unknown documents is that most IDP solutions require some type of recognition of the document type, which is then configured or trained on the system ahead of time. But if you don’t know what type of documents you have, then Semantik AI Engine can take over.

Is AI-based, computer vision technology something that your company is investing in?

> Yes, we are already looking at it - [38%]

> Yes, we are considering it - [39%]

> Not yet, I don’t know much about it - [13%]

> Not at this time - [10%]

The bottom line: Here we see that 77% of the respondents are either considering or already looking into AI-based computer vision solutions to improve their data and their processes. Computer vision applications are gaining popularity because of the need to recognize visual images, videos, documents and other inputs. According to this article in Forbes, the value of the market in computer vision technology is predicted to hit $48 billion by the end of 2022. This AI-based technology should be something to consider as you invest in an IDP solution.

Are you considering using APIs or connectors in your tech stack?

> Yes, we are already looking at it - [38%]

> Yes, we are considering it - [27%]

> Not yet, I don’t know much about it - [24%]

> Not at this time - [11%]

The bottom line: Another exciting feature that was revealed in the launch of Transact 2022.1 was the addition of pre-built integrations and connectors with both MuleSoft and Workato, two of the leading iPaaS solutions and another critical part of hyperautomation. These pre-built integrations enable data flow even faster into any other application. This end-to-end automation enables the flow of data for better and faster decision-making, which 65% of the audience is already considering or looking at the benefits of this technology. 

If you haven’t attended the webinars, you can watch them on-demand by clicking the links below or contact us to schedule a demo or free trial

Watch the Replay: The Future of IDP: Universal Document Automation

Watch the Replay: What’s New in Transact 2022.1: The Future Starts Today

Helping the World with Every Step: The Ephesoft Team Walks to Help the Ukraine and Global Initiatives

Fifteen months ago, a group of Ephesoft employees joined Sweatcoin to help different organizations while getting exercise through their app. The app tracks every step you take with your mobile phone and gives you one “Sweatcoin” – a digital currency – for every 1,000 steps. Users can then choose to donate the money to various causes or charities. Since our last update in August 2021, the team has been trekking the roads and trails. 

Making a Difference

After a few months, we had accumulated 728,000 steps or 728 Sweatcoins and donated them to fight climate change and support lowering CO2 emissions. In January, after another 379,000 steps, we were able to donate our Sweatcoins to help fund education for children in Uganda. 

Helping Ukraine

Photo caption: Courtesy of the Los Angeles Times

As the war against Ukraine began at the end of February, many of us felt passionate about donating to help the people there. Our first donation in March was for 528,000 steps – 528 Sweatcoins – towards helping Ukrainian children flee and escape violence. But we knew that wasn’t enough. We enlisted the help of the entire company to help boost our donations by walking during our company meeting a few weeks later. We were able to donate another 1,052 Sweatcoins to help educate those affected by war. Our goal was to get 2 million steps by the end of the month.

Saving the Environment and People

Additionally, during March, the team donated 501 Sweatcoins to the TAPIA Project, which helps protect the Tapia forest, a Madagascar ecosystem, from further deforestation. Another team member was able to donate 459 Sweatcoins to support brain tumor research. 

We met our company goal for March and walked 2,012,000 steps! And, even better, since our last blog post, it’s been an amazing team effort: we walked a total of 3,268,000 steps! Using a steps-to-miles calculator, the team walked approximately 1,575 miles. The best part is that we had an opportunity to make an impact on others’ lives. Stay tuned for more updates as the team keeps trekking and giving! 

Who wants to join us and give back to the international community? 

“KMWorld 100 Companies that Matter Most in Knowledge Management for 2022” Selects Ephesoft as a Leading IDP Company

KMWorld’s annual list for companies that matter most in knowledge management recognizes Ephesoft as an influential intelligent document processing (IDP) company in the industry. Ephesoft’s IDP platform automates document-centric processes to maximize operational efficiency and productivity for enterprises and the public sector. Using AI, patented machine learning and proprietary classification models, Ephesoft’s customizable and scalable platform turns any document type into structured, actionable data to accelerate business processes and data-driven decisions.

“While digital transformation was well underway more than 2 years ago, the trend accelerated rapidly when the pandemic hit. It’s true that the tumultuous business climate continues unabated, but smart, knowledge-driven organizations have been successfully seizing products and services that help them identify new opportunities, improve customer service, modernize operations, thwart fraudulent activity, make the right information available to staff members who need it, and, when possible, enhance decision making with real-time information,” said Tom Hogan, Group Publisher, KMWorld. “Against that reality, KMWorld presents the KMWorld 100 for 2022, a list of inventive knowledge management companies whose offerings are targeted at helping organizations expand their use of information and knowledge and accelerate their growth.”

“We are pleased to be included in KMWorld’s important companies to watch in 2022. Companies looking to transform their documents into actionable data will want to keep an eye on our upcoming release of Transact in April, which includes a new AI feature enabling universal document automation,” said Ike Kavas, founder and CEO at Ephesoft. “Transact will soon run using our proprietary Semantik AI Engine that will eliminate the need for templates or rules. It leverages computer vision and adaptive AI models, marking the start of a new era of document automation.”

Most noteworthy last year, the company’s flagship product, Ephesoft Transact, included several new cutting-edge capabilities. Capturing handprint data and cursive handwriting has long been a source of hardship for many organizations, until recently. Industry-wide, the technology has been limited and the accuracy rates have been notoriously low. With the latest release, Transact now features Handwriting Recognition+, based on using cloud hybrid technology and AI, delivering 88% accuracy for capture handprint, machine print, complex handprint and cursive handwriting. The release also included an intuitive, AI table rule builder, which transforms complex tables into structured data in record time, at high accuracy.

In the public sector, Ephesoft also took great strides and became available on Project Hosts’ Federal Private Cloud FedRAMP-authorized Platform, proven to have a highly secure environment that withstood comprehensive audits and built on Microsoft Azure Government. The solution is compliant with all security controls and has a System Security Plan (SSP) in place to greatly accelerate the compliance verification and Authorization to Operate (ATO) process. With FedRAMP controls in place, Ephesoft Transact has been deemed a viable solution to provide significant time and cost savings, increased productivity and improved accuracy by automatically transforming any document type into structured, actionable data.

KMWorld has also named Ephesoft Transact a “Trend-Setting Product” five times in a row. For more information on Transact, visit the product page here. To read the entire list of “KMWord’s 100 Companies that Matter Most in Knowledge Management for 2022,” click here.

Digital Transformation in the Mortgage Industry

Zero-defect loans—the goal of every mortgage lending company. Unfortunately, these are hardly achievable without in-depth research and analysis on every mortgage loan applicant. But, new industry innovations like digital transformation have made zero-defect loans possible. 

Let’s get into what the digital transformation in the mortgage industry looks like and how technology can help improve how you interact with your customers.

How Is the Mortgage Industry Changing?

As the world becomes more automated, more and more home buyers want efficient and streamlined solutions for the mortgage application process. The mortgage industry has responded to this trend by implementing a variety of technologies, including the following:

API Adoption and Communication

Application programming interface (API) allows different applications to share information. Lenders can then expedite loan processing by extracting correct and relevant information from multiple sources, thus increasing processing speeds and improving data accuracy.

AI-Powered Document Scanning

Lenders and applicants alike have a mountainous pile of documents to fill out and sort through to complete the application and approval processes. Both processes can be significantly easier thanks to AI-powered intelligent document processing in the mortgage industry.

Scanners will look over both digital and physical documents to extract, identify and sort information. The indexable data helps reduce input errors and minimize busy work for loan officers who can focus on more important tasks, like making sure the applicant is qualified for the loan.

Self-Service Options

Today, many home buyers rely on—and even expect—an online solution for most of their needs. Ideally, they want loan applications to be as simple as ordering a burger on their phone. That means simple interfaces, quicker turnaround times and increased communication about the loan application status.

More lenders are developing their processes to meet those high expectations. This includes creating web applications that offer a completely digital experience, including digital document uploads, that help applicants get preapproved and lock in their interest rates.

What’s Causing the Change?

Many factors contribute to the accelerating digital transformation in the mortgage industry, including:

  • Applicant expectations for more convenience
  • Technological advancements (particularly in document processing)
  • Increased demand for an alternative digital solution

Another factor has also elicited a major change in the industry—and virtually every other industry in the world—COVID-19.

How COVID-19 Accelerated Digital Transformation in Mortgage

When COVID-19 first came onto the global scene in early 2020, many countries mandated stay-at-home orders. This meant digital solutions were no longer a luxury—they were the only option. Therefore, many mortgage lenders needed to accelerate their digital loan application processes to appease people who were still looking to purchase homes.

This resulted in many lenders suddenly having technology that was months ahead of what would’ve happened otherwise. And since the effects of the global pandemic have stretched for over a year, technological advancement was compounded and accelerated even further.

Where Is Digital Transformation Heading?

What we’ve witnessed thus far in digital mortgage processes is just the beginning. As technology improves and mortgage applicants look for more convenient application processes, the industry will become more streamlined and reliant on digital solutions. We can already observe one product of this advancement: hyperautomation.

Hyperautomation in Mortgage

Hyperautomation is the end-to-end automation of processes accomplished by harnessing multiple technologies. In the mortgage industry, hyperautomation can help lenders accelerate their response times or improve their predictive analysis, including their ability to monitor their mortgage applicants’ behaviors.

For example, lenders can use automation tools to predict when one of their homeowners may soon refinance their house. By combining intelligent document processing (IDP) technology to extract the data, it can feed that data into business intelligence platforms or other systems. Then, mortgage companies can take advantage of hyperautomation by monitoring specific data points, like rising home values, current interest rate levels and other potentially favorable market conditions.

How You Can Participate in the Transformation

If you’re a mortgage lender and haven’t gotten your start on digitally transforming your business processes, there’s no better time to start than now. Here are a few things you should consider doing to get started down the right path: 

  • Adopt an IDP solution. Integrating IDP technology into your mortgage application processes will help you improve employee efficiency, decrease data errors, and serve more customers at once.
  • Focus on data. Centralizing your lending strategy around rich data will help you make better business decisions and weed out people who aren’t qualified for your loans. Of course, using IDP will help you gather the information you need.

Get Started with Mortgage Digital Transformation

Are you ready to take your first steps towards digital transformation in mortgage lending? We’re ready to help guide the way. But first, check out how to Get One Step Closer to Zero-Defect Loans. This will help you figure out who to loan to without increasing your risk of losing time or profits.

Invoice Processing FAQs

Invoice processing is an essential task for accounts payable departments in almost every company. If this term is new to you, then you probably have a few questions on your mind. We hope the following FAQs can help you.

What Is Invoice Processing?

Generally speaking, invoice processing refers to managing and organizing invoices from vendors, suppliers or any other entity. Originally, invoice processing had to be completed by physically recording new invoices into a ledger. Now, most businesses use automated invoice processing.

Automated invoice processing is the use of software and technology to digitally extract data from all invoices that enter your system. This digitally formatted invoice is then classified by document type and the data is extracted for easy access and payment in the future.

Note: Invoice automation also makes it easier to pay the invoice, as invoice processing software can link to ERP and accounting solutions.

What Is the Average Invoice Processing Time?

The time it takes to process an invoice depends on whether you use a manual or automated process—and the difference is extreme.

  • Manual: On average, we estimate it takes about 10 days to manually process an invoice. During this time, an individual has to read the invoice, manually copy the information within the document (hopefully without human errors), send the invoice for approval and provide payment. 
  • Automated: With Ephesoft, invoice processing can take as little as 36 seconds. That includes the same steps taken in manual processing (without the possibility of human errors)—just astronomically faster.

What Is Accounts Payable Automation (AP Automation)?

AP automation is the processing of invoices without the need for any human intervention unless the solution flags a problem or exception, in which the system will alert the user. In relation to invoice processing, the accounts payable invoice will be scanned and digitally extracted through automation and delivered to whatever entity needs to pay the account.

Once invoice information is extracted, the data is exported to an enterprise resource planning (ERP) platform. This allows businesses to seamlessly complete the transaction. Ephesoft Transact’s intelligent document processing platform supports most integrations with third-party accounting and business systems.

What Is Intelligent Invoice Processing Software?

Invoice processing software is the technology that companies like Ephesoft have developed to automate invoice processing. 

There are multiple components to invoice processing software, including:

  • AI technology: Artificial intelligence helps invoice processing software correctly identify and categorize the information from documents. Additionally, AI technology can use the information it has previously collected to generate new invoices.
  • Connector and workflow technology: To easily send invoices anywhere within your company, your network needs to be fully connected. Invoice processing software is prebuilt with connectors that use data security protocols to maintain safe and reliable connections.

Ephesoft’s AI-powered invoice processing software offers optimal efficiency in six simple steps:

  1. Capturing: Captures any type of document from any source
  2. Image Processing: Uploading and refining the digital image
  3. Classifying: Identifies and sorts the document 
  4. Extracting: Takes data from documents to create key values
  5. Validating: Receives alerts on any errors or exceptions
  6. Delivering: Delivers the digital document to any application or repository

What Is EDI Invoice Processing?

Electronic data interchange (EDI) invoices are electronic versions of a paper invoice. Therefore, EDI invoice processing is similar to automated invoice processing in that it deals with digital copies of invoices. 

However, EDI invoice processing does not signify the same level of automation as automated invoice processing. EDI only deals with electronic invoices and does not necessarily encompass other features of automated processing, including invoice delivery.

Learn More About Automated Invoice Processing

If you’re interested in learning more about Ephesoft’s approach to invoice processing, visit our product page. There, you can learn what our customers have experienced with our products. 

You can also experience automated invoice processing by scheduling a live demo. Try it and see how much time you can save today.

Helping the World with Every Step: Ephesoft’s Marketing Team Steps Up with Sweatcoin

The Race Begins

The idea came from Ephesoft’s Global Vice President of Marketing Andrea Walter’s son at the beginning of January 2021. He was excited about an app called Sweatcoin that tracks every step you take with your mobile phone and gives you one “Sweatcoin” for every 1,000 steps. Your steps accumulate Sweatcoins – a digital currency – and users can choose to donate the money to various causes or charities. According to one article, one Sweatcoin is the equivalent of $0.05, but users can’t sell them for cash. Sweatcoin says the value is derived from their partnerships with brands “that want to connect with health conscious audiences, insurers wishing to encourage healthier lifestyle choices and governments looking to reduce healthcare costs.”

In the midst of the pandemic and lockdown from California to Germany, the marketing team decided that since we were all walking so much for exercise from home (and it could be done with social distancing), this would be motivating and feel good to donate to people in need around the world. At the time, there were 4 team members who participated and all of us connected via the app so we could see and compare our daily steps. The steps began to add up. 


Helping Children in Haiti

Finally, we felt we had enough coins to make a difference in March. We selected "Accessible Education for Refugee Children" for our first donation of 600 Sweatcoins, which is the equivalent to 600,000 steps. At the end of April, we had accumulated 463,000 steps, of which we donated 463 Sweatcoins to "Cleaning Services for Cancer Patients." Summer was a busy walking month and in July, we donated 784,000 steps or 784 Sweatcoins to "Care for Children with Brain Tumours." Most recently, in response to the current earthquake that hit Haiti, we donated 430,000 steps or 430 Sweatcoins to help Haitian children. 

After taking a step back to look at our progress, we were amazed: the team walked 2,277,000 steps! Using a steps-to-miles calculator, the team walked approximately 1,156 miles in total, which is about 144 miles per month. And, the best part is that we had an opportunity to make an impact in others’ lives. Stay tuned for more updates as the team keeps trekking! 

A Small World: Helping Our Mutual Customer, NHS

Another cool aspect about Sweatcoin and Ephesoft is that we have a common healthcare organization, NHS (National Health Service) in the UK, that we are both working towards helping in different ways through technology. Sweatcoin is piloting a new type of behavior change program to help NHS patients with Type 2 diabetes using their platform. Unrelated to the Sweatcoin project, both Leeds Teaching Hospitals (NHS) and Liverpool University Hospitals (NHS) have implemented Ephesoft’s intelligent document processing solution at their locations to improve patient care. At Leeds, the hospital uses Ephesoft to create an efficient, digital platform with an e-referral system so patients can get care faster through automation. At the Royal Liverpool and Broadgreen Hospital NHS Trust (RLBUHT), the hospital wanted to digitally transform their document processes to create paper-free health records to save costs, improve efficiency and gain more quality time with patients.

“It’s such a good feeling to know that different companies with different services can affect change for the greater good through technology,” said Andrea Walter, VP of Marketing at Ephesoft. “We’re glad to be a part of the solution and I’m proud of our team for taking part and living a healthy lifestyle while giving back. ”

Who wants to join us?


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