Technical FAQs

Barcode Xpress and ImageGear .NET.  Barcode Xpress is a leading barcode reading SDK. While it supports a variety of image formats, Barcode Xpress works with ImageGear to support even more obscure image formats. For example, Barcode Xpress does not support reading barcodes on PDFs. Combined with ImageGear, developers can support a myriad of image formats and PDFs. With Barcode Xpress & ImageGear working together, developers can integrate a barcode reader that can detect barcodes on almost any kind of document.

Barcode Xpress accepts images in multiple different object types, such as System.Drawing.Bitmap. Using the method ImGearFileFormats.ExportPageToBitmap we can easily take any image that ImageGear supports and export it to a System.Drawing.Bitmap object that we can then pass to Barcode Xpress. So, only a tiny amount of code is required to recognize barcodes with ImageGear .NET and Barcode Xpress. Below, we’ll show various ways to pass different types of images and documents to Barcode Xpress.

Image:

// Load the image into the page.
ImGearPage imGearPage = ImGearFileFormats.LoadPage(stream, 0);

// Export the image to a bitmap and pass that bitmap to Barcode Xpress
 Result[] results = barcodeXpress.reader.Analyze(ImGearFileFormats.ExportPageToBitmap(imGearPage));

PDF:

We need slightly more code for a PDF. First, we specify a page number when calling LoadPage. Second, we must dispose of the ImGearPage object after we’re done with it. 

// Load the specified page of the PDF as an ImGearPage object
ImGearPage imGearPDFPage = ImGearFileFormats.LoadPage(stream, pageNumber);

// Export the image to a bitmap and pass that bitmap to Barcode Xpress
Result[] results = barcodeXpress.reader.Analyze(ImGearFileFormats.ExportPageToBitmap(imGearPDFPage));

(imGearPDFPage as IDisposable).Dispose();

Now that we’ve explained the most important part, we’ll show you a simple console app that recognizes barcodes on a PDF using the method above. 

The code below assumes you’ve installed an evaluation or development license for both Barcode Xpress and ImageGear .NET.

using System;
using System.IO;
using Accusoft.BarcodeXpressSdk;
using ImageGear.Core;
using ImageGear.Evaluation;
using ImageGear.Formats;
using ImageGear.Formats.PDF;

namespace BXandIGDotNet
{
	class Program
	{
    	static int pageNumber = 0;
    	static string fileName = @"Path/To/Your/PDF..pdf";
    	static void Main(string[] args)
    	{
        	// Initialize evaluation license.
        	ImGearEvaluationManager.Initialize();

        	// Initialize common formats.
        	ImGearCommonFormats.Initialize();
        	// Add support for PDF and PS files.
        	ImGearFileFormats.Filters.Insert(0, ImGearPDF.CreatePDFFormat());
        	ImGearFileFormats.Filters.Insert(0, ImGearPDF.CreatePSFormat());
        	ImGearPDF.Initialize();

        	using (FileStream stream = new FileStream(fileName, FileMode.Open, FileAccess.Read, FileShare.Read))
        	using (BarcodeXpress barcodeXpress = new BarcodeXpress())
        	{
            	// Load the specified page of the PDF as an ImGearPage object
            	ImGearPage imGearPDFPage = ImGearFileFormats.LoadPage(stream, pageNumber);

            	// Export the image to a bitmap and pass that bitmap to Barcode Xpress
            	Result[] results = barcodeXpress.reader.Analyze(ImGearFileFormats.ExportPageToBitmap(imGearPDFPage));

            	(imGearPDFPage as IDisposable).Dispose();

            	// Print the values of every barcode detected.
            	for (int i = 0; i < results.Length; i++)
            	{
                	Console.WriteLine("#" + i.ToString() + " Value: " + results[i].BarcodeValue);
            	}
            	Console.ReadKey();
        	}
    	}
	}
}

Using Barcode Xpress and ImageGear in Other Languages & Linux

You can also use Barcode Xpress and ImageGear together outside of the .NET framework. Barcode Xpress supports several different programming languages and frameworks including .NET Core, Java, NodeJS, Python, C, and C++. All of which can be used on Linux. 

ImageGear for C/C++ also supports Linux. Barcode Xpress Linux, which is a C/C++ library, ships with a sample called “ReadBarcodesIG”, that shows how to integrate Barcode Xpress Linux and ImageGear for C/C++. You can find the sample code after downloading our SDK here! For more information on Barcode Xpress, visit our Developer Resources page on the website. In addition, you can also find more information about ImageGear .NET on its respective Developer Resources page as well.

Although it might feel as though time has been standing still for several months, 2020 is finally coming to an end. It’s been a year of unprecedented disruption for many industries, and insurance companies often found themselves struggling to adapt to change. Firms that had the foresight to invest in digital transformation backed by InsurTech solutions, however, proved more capable of meeting the moment and are now poised to thrive in 2021 and beyond.

As the new year approaches, it’s helpful to take a look back at some of the key trends that defined 2020 and created opportunities for innovative InsurTech applications. Understanding the pressures facing the insurance industry will also identify InsurTech projections to watch in the future.

5 Insurance Trends and InsurTech Projections

1. Remote Collaboration

No discussion of 2020 insurance industry trends would be complete without exploring how the COVID-19 pandemic has affected organizations. According to a survey conducted by Deloitte, 48 percent of insurance executives agreed that the pandemic revealed how unprepared their business was for such a disruptive crisis. From the sudden transition to a remote workforce to a shift in risk adjustment factors across the market, insurers have had to scramble to adapt their operations and continue delivering quality services to clients.

With so many employees going remote and customers unable to meet with representatives in-person, organizations that made early investments in digital collaboration tools and automation software were better equipped to meet the challenges of 2020. The industry is expected to make tremendous investments in digital transformation in the upcoming year, whether it’s in powerful document editing and management software, file conversion tools, or secure communication channels that better facilitate true collaboration.

2. Customer Demographic Shifts

Prior to 2020, insurance customers tended to be older, with millennials purchasing life insurance policies at lower rates and often delaying home ownership until later in life. This trend seems to have reversed itself in the wake of the COVID-19 pandemic, however, with life insurance application activity growing twice as fast for people under 45 than those aged 45-49. Since many of these younger buyers are first-time applicants, it’s important for insurance agents and firms to make the process as streamlined and easy to navigate as possible.

According to a nationwide industry survey, just over 75 percent of independent insurance agents are age 50 or older and nearly 68 percent have more than 20 years of experience. Having such a long-tenured workforce poses challenges when it comes to implementing new processes and reaching out to potential customers with different needs and preferences than those of earlier decades. In order to remain competitive, however, firms must invest in the right InsurTech solutions to gather data that will give them a better picture of what insurance products and services younger customers will find attractive.

3. Robotic Process Automation

The shift to a remote workplace greatly disrupted traditional workflows. Without centralized offices, key insurance tasks like claims processing and document verification are much more difficult to perform manually. Organizations that had already invested in robotic process automation (RPA) to handle repetitive tasks were in a much better position to thrive in a remote landscape. 

Insurance companies must be able to process a variety of forms during an application or a claim. Having automated InsurTech tools in place to quickly extract data from a variety of sources and carry information over from one form to another not only saves time, but also greatly reduces the risk of human error. For a remote workforce, automation software helps to consolidate complex workflows to eliminate version confusion and enhance collaboration.

4. Artificial Intelligence

Risk assessment and data analysis are crucial to the underwriting process. In a volatile economic environment, insurance firms are under more pressure than ever before to set the right premiums. Although the data is now readily available to make more accurate assessments, sorting through that information manually is difficult and time consuming. 

As the COVID-19 pandemic demonstrated, the scope of risk can change dramatically in a very short period of time. By deploying artificial intelligence (AI) to analyze risk factors and review potential fraud claims quickly and accurately, insurers can create customized policies and provide more responsive service to their customers.

Implementing AI-driven algorithms as part of the underwriting and fraud analysis process will only be one part of the challenge facing firms in 2021. These powerful tools must have sufficient data in order to make informed predictions. By improving the data collection process with form processing tools, file conversion, and programmatic searches, insurers can provide their analytics platforms the best possible information for analysis.

5. Customer Experience

One of the few positive impacts of the COVID-19 pandemic was that it forced organizations across every industry to find new ways of connecting with their customers. The insurance industry has traditionally lagged behind other sectors, tending to lean upon a combination of tradition and legacy infrastructure to engage with customers. But the events of 2020 have underscored the need for a true digital transformation that fundamentally reorients the way firms market, sell, and deliver insurance products. The need has become so evident, in fact, that a recent PWC survey found that 70 percent of insurance CEOs are prioritizing customer experience and user interfaces as their top investment opportunity.

In the coming year, firms will likely continue to invest in technology that makes it easier for customers to research and manage their policies. Whether it’s applications that allow them to submit claims information in a variety of file formats or forms and contracts that automatically fill in commonly used form fields, the core focus will be on making the customer experience as frictionless as possible with a variety of InsurTech benefits.

The Role of InsurTech

Many insurance companies will be looking to upgrade their technology stack and client-facing applications in response to these trends. That creates a tremendous opportunity for InsurTech developers who are creating the next generation of software tools to streamline core processes common to the insurance industry.

Delivering those digital products on a short timeline with limited resources, however, can be quite a challenge for even the most innovative InsurTech startup. That’s why many of them turn to third-party solutions to provide proven functionality that lies outside the scope of their development expertise. 

Features like forms processing, document conversion, and image viewing can be easily integrated into an application using an SDK or API, saving the team weeks or even months of work. This helps InsurTech companies get their products to market faster to meet the digital transformation needs of their customers and keep them a step ahead of their competitors.

InsurTech SDKs and APIs

Accusoft’s family of processing and automation SDKs and APIs provide InsurTech developers with the tools they need to easily plug essential functionality into their applications so they can get back to focusing on their most innovative features. With a variety of deployment options and a diverse set of code-based solutions, we have the flexibility to meet your software’s unique use case and substantially reduce your time to market.

Whether you’re looking to integrate document viewing, collaboration, or processing to your InsurTech platform, our SDK and API-based products can help you deliver the InsurTech benefits your customers are looking for. Learn more about our insurance solutions or contact us today to demo one of our products.

Seventy-six percent of companies surveyed plan to prioritize machine learning (ML) and artificial intelligence (AI) deployments in 2021. Despite increased uptake, however, there is still a great deal of confusion surrounding these advanced concepts. In order to understand how organizations hope to leverage ML and AI in their technology initiatives, it’s helpful to take a step back and examine how they work and how they differ from each other.

What Is Machine Learning?

Machine learning uses statistics-driven algorithms to find patterns in massive amounts of data. These algorithms are designed to improve over time as they process more data to enable more accurate outputs. Machine learning is widely used to produce predictive recommendations — companies such as Google, Netflix, and Facebook collect data about user behaviors and feed it into machine learning algorithms which then produce targeted search results, movie recommendations, or advertisements. 

The key to machine learning success is data. The more data available to ML algorithms — and the higher-quality this data — the better they’ll be able to identify patterns in current datasets and apply them to new data sources.

Most machine learning methodologies fall under one of two broad categories:

• Supervised Learning: Developers classify and label data to guide the algorithm’s inputs and outputs to ensure specific patterns are recognized. This method is time and resource intensive because it requires data scientists to capture, control, and curate data sources.
• Unsupervised Learning: This approach provides ML algorithms with unlabeled and unclassified data and allows them to identify patterns based on unique data characteristics. Developers don’t interfere with the learning and pattern recognition process, instead evaluating the outputs for accuracy and modifying code as needed.

Why Does Machine Learning Matter?

Machine learning helps organizations leverage the massive amounts of data they’ve accumulated. This information is drawn from a variety of sources, including disparate forms and documents, data produced through customer transactions and service calls, and the ongoing operational data produced by staff as they interact with IT resources.

Thanks to both the rapid uptake of cloud computing and availability of large-scale data collection and analysis tools, these data volumes are increasing exponentially. As a result, aggregate assessment is now critical — companies need a way to rapidly and reliably derive patterns from available data, and apply these patterns to predictive action.

This is the evolving role of machine learning. By creating, testing, and deploying ML algorithms capable of rapid pattern analysis and application it’s possible for companies to benefit from this continual data influx rather than being constrained by the bounds of traditional data evaluation. To facilitate this process, many next-generation software tools and services are either equipped with built-in ML frameworks or are capable of interfacing with them.

Key Machine Learning Applications

The applications of machine learning are vast, but they tend to produce the best results when paired with existing processes that supplement human efforts or automate low-value, but labor-intensive, functions in the workplace. In effect, it has the potential to do almost anything a human mind can do, given enough time. 

Improved Data Capture

Capturing data from internal documents and customer-submitted forms can be cumbersome and time-consuming. It can also lead to wasted time and effort if data is incorrectly entered, duplicated, or accidentally deleted. By pairing machine learning tools with forms processing solutions like Accusoft’s FormSuite for Structured Forms, developers can build applications that identify, collect, and capture key data more efficiently and accurately. For example, a robot process automation (RPA) bot can be set up to receive extracted form data from FormSuite and then populate that information into the appropriate fields within an application. This not only accelerates forms processing workflows, but also greatly reduces the risk of data entry error. Properly implemented, automated data capture can act as a springboard for improved data insight and decision-making thanks to improved accuracy and consistency. 

Streamlined Content Creation

By combining machine learning algorithms and data sources with document editing tools, it’s possible to streamline key processes such as the creation of complex, compliance-bound content. One in-practice example is the use of Accusoft’s PrizmDoc Editor within the LegalSifter contract review and creation platform. By pairing its AI technology with PrizmDoc Editor’s document assembly capabilities, LegalSifter was able to quickly locate repetitive clauses and suggest replacements to create an automated contract creation experience for end users. 

What Is AI, and How Does It Relate to Machine Learning?

The terms artificial intelligence and machine learning are closely related and often used interchangeably, but they’re not identical.

Artificial intelligence refers to technologies that are capable of performing tasks like photo recognition or data pattern analysis with similar (or better) outcomes than human beings. Machine learning refers to the creation, testing, and refinement of the algorithms needed to support AI tools. In many ways, then, ML functions as a distinct process that helps make AI possible.

As noted by Toward Data Science, it often helps to think of AI, machine learning, and deep learning like a set of concentric rings. The smallest, inner ring is deep learning, which helps inform the middle ring of machine learning by providing layered neural network structures that improve the process of pattern recognition. The final, outside ring is AI, which depends on both deep and machine learning to deliver real-world results. 

Artificial intelligence tools can be broken down into two basic types:

• Generalized AI: These tools are capable of solving problems bounded by a clear set of rules. Using the ML algorithms that underpin the larger AI structure, general AI applications can act on stimuli — such as a security alert from an IT network — and respond appropriately by creating and logging reports or looping in human agents. 
• Narrow AI: These solutions are designed to solve specific, small-scale tasks. Building on the security example from above, a narrow AI application might see tools responding to specific threat events such as DDoS or ransomware attacks by deploying targeted, defensive responses that close active sessions, capture attack data, and prevent future connections from the same IP address. 

In practice, narrow AI tools can outperform their human counterparts in completing specific tasks, but are unable to translate this expertise into applicable action at scale. General tools come closer to mimicking human intelligence but are still a long way from replicating the depth and breadth of human thinking.

Limitations of AI

Much has been made about the potential of AI technologies to take the place of human staff, leading to a generalized sense of worry about the future of these tools at scale. Recent research, however, found that substantial confusion remains around not only the deployment of AI but the definition itself. In fact, one study found that 40 percent of AI startups in Europe were not actually using AI. In some cases, increasing market interest in AI tools encouraged the use of this term to help startups capture attention, in much the same way that rapid cloud adoption spurred the creation of a host of “cloud” companies that offered nothing of the sort.

Uncertainty around AI itself, however, also plays a role in this disconnect. Given the massive potential of AI to help companies solve both specific and generalized problems, the term can be applied in almost any context and made to fit almost any description.

Unlocking the Future

After spending many years confined to research projects and future-focused technology articles, both machine learning and artificial intelligence are making their way into the applications and software companies are deploying every day. As developers look ahead to building the next generation of technology solutions, they must not only think about how they can better leverage ML and AI principles, but also how to implement features that take advantage of them.

Accusoft’s collection of versatile SDK and API integrations deliver powerful viewing and image processing capabilities that help applications streamline workflows and enhance productivity. To learn more about how Accusoft can help you enhance the workflow in your machine learning or artificial intelligence projects, contact us today.

Redacting documents is critically important for legal departments and government agencies. By removing sensitive information from a digital file before sharing it publicly, it’s possible to protect private data or classified materials from being exposed. 

In the days before digital documents, redaction involved a simple, if crude, process of covering text with a black marker. Since redactions were done by hand, it was easy for mistakes to be made, which could range from using insufficiently dark ink to leaving portions of text exposed. The development of high-powered photo enhancement has rendered this approach all but useless, as even inexpensive image processing technology can distinguish blacked-out text.

With the transition to digital documents, organizations finally have access to true redaction capabilities. Unfortunately, they still tend to make mistakes when it comes to flattened PDFs that could leave redacted context exposed and vulnerable.

What Is a Flattened PDF?

A modern PDF file consists of multiple layers, each of which can contain separate elements. One layer might feature text, another image, and yet another a fillable form. The flattening process removes all interactive elements from form fields and combines all of the document’s elements into a single layer. 

Organizations frequently used this process to “lock in” form content to prevent anyone from altering the information after a user completes the forms. It also removes elements like dropdown selections within form fields and can burn in other annotations or markups, making them a permanently visible element of the document.

Flattened PDF Redactions

Unfortunately, simply flattening a PDF is usually not sufficient to securely redact a document. That’s because obscured elements are still present in the document; they’re just not visible when the file is viewed and printed. 

Recovering improperly redacted content is actually quite trivial in many cases. Two of the most infamous recent examples include information released during the investigation of political campaign chairman Paul Manafort in 2019 and court documents related to Facebook’s use of personal data in 2017. In both cases, journalists were able to copy redacted text from PDF files and paste it into a text editor to reveal the obscured content.

There are typically two ways that improper redactions occur:

1. Covering Text with Boxes: This frequent mistake occurs when people try to treat a digital document like a physical piece of paper. They place annotations over the sensitive content, usually in the form of a black box, and then save a flattened version of the PDF thinking that no one will be able to separate the text from the annotation element. As the Manafort and Facebook cases demonstrate, however, getting around these “redactions” is usually quite easy.
2. Changing the Color of Text: Another common redaction error involves altering the color of the sensitive text to match the document background. Changing the text color to white, for instance, might make it invisible to the human eye, but it does nothing to alter the content itself. The text can be made visible again by using the copy/paste trick described above or by altering the background characteristics in another program. 

The only way to make these methods viable for true redactions would be to actually print the documents with the content hidden and then scan them back into digital form, where OCR could be used to reconstruct a new file. But even in this case, there’s a chance that a powerful OCR engine might be able to pick up the hidden elements.

Using Proper Redaction Prior to Flattening with PrizmDoc Viewer

In order to redact documents securely, applications need to have access to specialized redaction tools that are capable of actually removing content from the document itself before applying redaction indicators. PrizmDoc Viewer’s redaction API can find and extract key text while also providing single or multiple reasons for the removal. 

This not only allows organizations to redact documents quickly, but it also ensures that the redacted information won’t be exposed later because it no longer even exists within the document. More importantly, the outputted document is entirely new, so there is no deleted information to recover. 

While most people are familiar with the distinctive black bars that indicate redacted content, even this leaves behind significant context clues that could provide hints of what was removed. Consider, for instance, a document involving multiple parties where the names of conversation participants have been redacted.

The following information:

The length of the redaction, then, would at least indicate when the redaction did not involve one person or the other. There are also many instances involving government documents where the length of the redacted information in classified material might suggest its relevance or importance.

When it comes to GovTech applications that need to remove large portions of information for security reasons, it often helps to perform redaction BEFORE turning a document into a flattened PDF. The PrizmDoc Viewer redaction API can be used to quickly extract text from a document and then redact it as a plain text file. 

Unlike a static PDF document, plain text accounts for width variations, so all redactions can be replaced with a standardized <Text Redacted> marker that makes it impossible to know the length of the redacted content. The text could then be converted into a PDF after the redaction process is complete.

Take Control of PDFs with PrizmDoc Viewer

As a fully-featured HTML5 viewer, Accusoft’s PrizmDoc Viewer delivers powerful viewing, annotation, and conversion functionality to your web application. It provides a broad range of redaction capabilities that allow legal, financial, and government organizations to keep their sensitive data secure and protect their customers. 

By integrating these complex features into your applications, you can focus your development efforts on building the tools that set your solution apart from the competition while our proven technology powers your customers’ viewing and redaction needs. To learn more about PrizmDoc Viewer’s powerful capabilities, download a free trial and test how it can support and enhance your application.

Powerful patient portals are now essential for healthcare organizations to deliver high-quality care, even at a distance. Despite advancements around functionality, however, challenges remain. As noted by Healthcare Info Security, many healthcare providers still struggle with providing solutions to patients in an easily accessible portal that provides the security they require by law.

Here, HIPAA compliance is critical. Healthcare organizations need portal solutions that deliver valuable information without undermining regulatory requirements around data security and handling. Creating innovative, secure patient portals demands HIPAA-compliant tools that deliver advanced viewing and redaction tools while keeping privacy in practice.

The State of Healthcare Security

Security remains a problem for healthcare organizations as attackers ramp up efforts to access private patient and operational information. The healthcare industry saw more than 41 million records breached in 2019 and new attack vectors are now emerging as hackers look to leverage pandemic pressures and breach corporate security. It’s no surprise, then, that last year saw 28,261 HIPAA complaints, the highest number ever recorded, as organizations deployed more user-friendly technology and attackers looked to capitalize on potential weaknesses.

Ramping up security in patient portals and meeting emerging patient needs is a priority for organizations. Accusoft’s PrizmDoc Cloud, a HIPAA compliant solution, is capable of offering user-friendly portal capabilities inside your own secure application. The right combination of existing technology and cloud-based application programming interfaces (APIs) can take your patient portal to the next level. Let’s break down five key cloud-based APIs that can help patient portals deliver on practical potential.

Robust Document Viewing with PrizmDoc Cloud API

Effective medical care depends on documents. From patient consent forms to test results and referrals from other healthcare practices, documents form the core of custom-built treatment plans. While the transition to electronic health records (EHRs) has helped reduce the complexity and confusion that comes with paper-based processes, this digital transition has introduced the challenge of document diversity. 

From typical Word documents to Excel spreadsheets and scanned images of handwritten forms, patients need the ability to access documents on-demand, while healthcare organizations must ensure that patient access options are both secure and HIPAA-compliant.

The PrizmDoc HTML5 Document Viewing API offers document and image viewing while also streamlining the process with key features including:

• Responsive Web UI — Patients and staff can easily view documents and images that are scaled to fit their tablet, laptop, or mobile phone.
• Configurable Controls — Organizations can easily enable or disable tabs, localization, rendering options, and encryption within their patient portal.
• Microsoft Office (MSO) Conversion — Healthcare agencies can integrate true native viewing of Word, Excel, and PowerPoint documents.

Reliable PII Redaction

Data privacy is paramount for HIPAA compliance. As noted by Managed Healthcare Executive, this is especially critical in the world of COVID-19. With telehealth now the “new normal” — and likely to continue long after the pandemic subsides — organizations must ensure that protection of personally identifiable information (PII) remains intact.

While robust encryption and identity access management (IAM) tools form part of this function, redaction is another critical aspect. Consider the case of children. As noted by the Health Info Security piece, although parents typically have complete access to the medical records of children under 12, PII for those between the ages of 13 and 18 — such as mental health records — may be restricted. For healthcare agencies, this requires patient portal solutions that allow parents access to some data while also protecting specific PII. Here, robust redaction APIs that allow organizations to obfuscate key information are critical to meet regulatory requirements without compromising ease-of-access.

Regulated Image Compression

Images form a critical component of effective patient prognosis and treatment plans, and while DICOM files used in high-fidelity imaging are often a priority for medical agencies, there’s also a need for image compression solutions that enable the portability of more common image types such as JPEGs.

Consider the simple case of patient identification. By attaching high-quality photos to patient records, medical staff are better equipped to ensure the individual they’re assisting — virtually or in-person — is the patient linked to the account. High-quality JPEG photos are also useful to record and track the progress of specific physical ailments over time. Cloud-based image compression APIs streamline this process with the ability to compress individual or multiple files, set desired quality, remove metadata, and set JPEG mode output.

Rapid File Conversion

Complexity remains a challenge for healthcare records management. As patients visit general practitioners (GPs) and specialists, data volumes rapidly increase, in turn making it difficult for doctors to find specific information and create comprehensive treatment plans.

Multi-file combination and conversion to popular formats such as PDF helps solve this problem — not only can healthcare staff create files that are easily viewed by doctors and patients alike but administrators can also set key permissions around editing, annotating, and printing to ensure information remains secure. File format conversion with PrizmDoc Cloud APIs can help enhance patient portals with key features including:

• Easy combination of multiple files into single PDFs
• Data security with optional password protection
• Specific section or entire file conversion
• Searchable output formats

Relevant Watermarking

Last on our list of patient portal APIs is watermarking. By labeling key documents with unique healthcare watermarks, organizations can both improve front-line security and enhance HIPAA compliance. By training staff to only accept and process watermarked images and documents, companies can reduce the risk of potential compromise. If attackers attempt to spoof or modify key documents they can be easily detected because they won’t carry corporate watermarks. These marks also form a key component of auditing and data tracking if healthcare agencies are evaluated for HIPAA compliance by providing a visible chain of custody around document creation, storage, and access. 

User-friendly patient portals are critical for healthcare companies to survive in the “new normal” — and embrace what comes next. But speedy access requires a robust security balance; document viewing, redaction, compression, conversion, and watermarking APIs from Accusoft can deliver privacy in practice and capitalize on patient portal potential.  Try PrizmDoc Cloud API.

Of the many eDiscovery trends we’re seeing in the Legal Tech world, one stands out as particularly crucial. The eDiscovery services market is exploding. The market is estimated to grow 8.7% annually, reaching more than $17B by 2027. 

The rapid growth of eDiscovery presents exciting opportunities for the Legal Tech world. However, for independent software vendors (ISVs) to capitalize on those opportunities, they must also stay vigilant about associated concerns such as the use of AI, data privacy, and effective document management.

Amidst the remarkable expansion of eDiscovery services, a host of trends have emerged that hold significant relevance for ISVs. Below, we outline key eDiscovery trends and offer tangible ways to navigate the landscape successfully.

Three eDiscovery Trends You Need to Know

#1: A Cautious Embrace of AI is Critical

One of the most prevalent eDiscovery trends is the need for cautious use of AI. It’s no secret that AI, or Legal AI, generative AI tools trained on legal processes, is revolutionizing eDiscovery. Law firms are already reaping the benefits, as 70% of large firms agree that generative AI adds value.

Legal AI makes teams more productive by automating rote tasks such as document review, memo drafting, and initial contract creation. For example, a recent study found that AI-powered due diligence document review can cut review time by up to 70% compared to traditional methods. 

What does this data tell us? That lawyers will be turning to Legal Tech ISV professionals to help them better use, scale, and mitigate the risks of AI.

As the eDiscovery market grows, more sophisticated use cases for Legal AI will be developed. For instance, a Legal AI tool could generate textual content, such as policies or communications, based on input examples. Additionally, a tool could assign a tag to a given input and help professionals create a searchable database of documents to streamline due diligence.

In other words, the possibilities of Legal AI are endless. However, generative AI tools, especially when used in highly regulated fields, must be implemented with caution. That’s where ISVs can bring unique value.

Risks of Legal AI that ISVs can Help Mitigate

• Tools that are available publicly have been trained on vast amounts of historical data, which could result in outputs that are outdated, biased, or irrelevant to your clients’ needs.
• The misuse of AI is common within and outside of organizations, which could result in “deep fake” images and videos, along with generated data that are hard to verify.
• Inputs that include personally identifiable information (PII) can be accidentally exposed to other users of the tool. That’s where Accusoft’s PII detection and redaction feature in PrizmDoc can be helpful.

These are just a few risks that accompany all of the benefits Legal AI tools offer. It’s critical to spend plenty of time experimenting with various tools to see which ones pose the least amount of risk and work best for your application. Part of a cautious embrace of AI also includes forming a team to research, test, and launch tools safely. That’s why 38% of American Law 200 firms are expected to hire more technologists to support generative AI initiatives.

Action Items: How to embrace eDiscovery AI tools cautiously in your application

• Offer AI readiness assessments or audits to help law firm clients evaluate their current readiness, infrastructure, and data readiness for AI implementation.
• Facilitate knowledge-sharing among your clients by organizing learning sessions. Given that 90% of law firms reported that they expect their investment in generative AI to rise in the next five years, it’s clear that legal teams are using AI successfully. Consider arranging sessions where firms that have successfully implemented AI can share best practices with less experienced organizations. 
• Explore partnering with a trusted eDiscovery document processing vendor such as Accusoft to integrate carefully vetted AI tools into your application. 

#2 Data Privacy Restrictions Must be Top of Mind

Any list of 2024 eDiscovery trends must include a concern about data privacy. This year and beyond, restrictions on data privacy and protecting PII will become more rigid. Awareness of protecting client data has grown globally. Additionally, excitement about AI can inadvertently overshadow the data privacy concerns that come with using tools that are publicly available.

Increased data privacy restrictions within firms will look like stricter data retention policies and increased use of software designed to help teams identify and redact PII. Firms will need to conduct thorough research on the data privacy policies of their partners, as well as the data privacy laws of the geographic areas in which they conduct business.

Action items: How to keep data privacy top of mind in your application:

• Strengthen your software’s data security by implementing robust encryption protocols and security measures. Provide options for end-to-end encryption, secure file sharing, and secure document storage to safeguard PII and maintain client confidentiality.
• Provide tools for compliance auditing, monitoring, and reporting to assist legal teams in demonstrating regulatory compliance to clients and regulatory authorities. Features such as access logs, audit trails, and user activity monitoring ensure accountability and transparency in data handling practices.
• Ensure continuous improvement and responsiveness within your applications to evolving client needs and how PII could be exposed or inadvertently changed. Establish regular feedback loops with clients to gather insights, identify pain points, and prioritize feature enhancements. 
• Review your organization’s data privacy policy. How does your software protect client data, PII, and more? Keep your clients updated on your policy so that they know data privacy is a top priority for you. 

#3 Better Management of Collaborative Platforms is Needed

Another one of the most important eDiscovery trends of 2024 is the need for better management of collaborative platforms. The adoption of collaborative platforms, such as Slack, WhatsApp, MS Teams, and others, has surged due to the shift to remote work.

The use of collaborative applications offers advantages and poses challenges. For example, they enable legal teams to capture valuable information from communications across many platforms that strengthen court cases. However, they also create extremely large volumes of legal documents and the potential of large amounts of duplicate content that teams then have to review.

Why is the concern about collaborative platforms so great? Because the number and use of these platforms is only growing. From now until 2032, the collaboration software market is projected to grow 12% annually. 

This has had profound effects on legal firms performing eDiscovery, most of whom still depend on tools and review processes designed for standard digital documents (such as .doc, .xlxs, .ppt, etc), paper documents, and email. The process of collecting, viewing, searching, redacting, and collaborating across traditional documents and emails has pivoted, and firms are responsible for including the digitized content from these collaborative working social platforms in their eDiscovery.

Action items: How to help law firms better access to files created in document collaboration tools

• Embed advanced search and filtering capabilities into your Legal Tech software that are specifically tailored to collaborative platform communications. This includes the ability to search for keywords, filter by date range or user, and apply metadata tags to organize and categorize communications effectively. These features enable lawyers to quickly locate relevant information during eDiscovery proceedings.
• Create tools in your application that supports the collecting, viewing, searching, redacting, and collaborating across traditional documents and emails, and also the digitized content from these collaborative working social platforms.
• Consider integrating PrizmDoc into your solution to seamlessly search, identify, and redact information directly within your application, ensuring top-notch document security.

Solutions Built to Help You Capitalize on eDiscovery Trends

We’ve only begun to see how the explosion of the eDiscovery services market poses opportunities and potential downfalls to the Legal Tech world. With the right safeguards in place, ISVs can capitalize on these opportunities to enhance their services, maintain competitiveness, and above all, foster client trust.

Wondering how can Accusoft support your team in keeping up with the eDiscovery trends of 2024? Read our Legal Tech Fact Sheet.

Few document formats are more common than XLSX spreadsheet files. Although many alternatives are available, most enterprises continue to rely on the broad (and familiar) functionality of Microsoft Excel when it comes to their spreadsheet needs. However, few organizations take the appropriate steps to ensure Excel spreadsheet security, which could leave their private data and formula assets exposed to substantial risk.

As a third party dependency, Excel represents an obvious security gap that could easily be exploited. Any time a file travels outside a secure application environment, there is a potential risk of data theft and version confusion. In any situation where files are travelling between separate applications, there is also an opportunity for malicious files to slip into unsuspecting workflows. By focusing on ways to shore up their Excel spreadsheet security, organizations can minimize risk and protect their sensitive data.

Excel Spreadsheet Security Risk #1: Malicious File Extensions

Most organizations are aware that opening a file attached to an email is one of the most common ways to introduce malware into a system. What they may not realize, however, is just how pervasive the problem is or how well those files are masked. It’s easy to identify a malicious email attachment when its name is a jumble of letters and it has an unfamiliar file extension. The real threat comes when it actually resembles something familiar and potentially legitimate.

Unfortunately, XLSX spreadsheet files are frequently used to distribute malware. According to a comprehensive cybersecurity study conducted by Cisco in 2018, Microsoft Office file extensions (such as DOCX and XLSX) were used by 38 percent of malicious email attachments, higher than any other format. These extensions are attractive to cybercriminals precisely because they’re so widely used. Someone working in a financial services organization, for instance, is usually quite accustomed to sending and receiving spreadsheets via email, so they are more likely to open an XLSX file out of curiosity.

Of course, this raises a separate question about basic cybersecurity. No organization today should be relying on poorly secured channels like email to share sensitive documents in the first place. By integrating native XLSX viewing and editing capabilities directly into their web applications, developers can provide the tools necessary to share spreadsheets without the risk of exposing collaborators to malicious file extensions. Embedding spreadsheet files into the application allows for easy access, but also keeps the file safely within a secure environment. Once users become accustomed to accessing spreadsheets this way, they’ll be less likely to fall prey to a malicious XLSX extension in their email. 

Excel Spreadsheet Security Risk #2: Insufficient Access Control

Spreadsheets can contain a great deal of information. Not only do they make it easy to reference data and carry out complex calculations in seconds, there’s a lot happening behind the scenes that may not be immediately obvious to the average user. Spreadsheet cells typically incorporate highly detailed (and often proprietary) formulas that help organizations to estimate costs, assess risk, and adjust revenue forecasts. For many industries, there’s simply no software that can compete with the extensive capabilities of spreadsheets.

But that versatility comes with a cost. Any user with a rudimentary knowledge of spreadsheets can easily reveal hidden information and examine the formulas behind the document’s calculations. And once they’ve downloaded their own copy of the spreadsheet, there’s nothing to prevent them from using it elsewhere, which can be a serious problem for any organization that depends upon its proprietary formulas to drive business success.

The root problem in this case comes down to who has control over the spreadsheet. When an XLSX file is shared, it can then be copied or even altered without the knowledge or permission of its original owner. The best way to maintain control over spreadsheets is to integrate native XLSX viewing capabilities directly into a web application. This allows developers to control which elements of the spreadsheet are being shared and prevents anyone from downloading a copy without permission. Since users can only interact with the spreadsheet on the terms set by the file’s owner, they can’t peek “under the hood” to obtain proprietary assets like cell formulas.

Secure Your Spreadsheets with PrizmDoc Cells

Accusoft’s PrizmDoc Cells is a powerful API integration that allows developers to provide dynamic spreadsheet viewing and editing capabilities within their web application environment. Far more versatile than traditional viewer integrations that offer only a static “print preview” image of a spreadsheet, PrizmDoc Cells makes it possible to scroll both vertically and horizontally and even enter information into cells to perform calculations. It’s the most secure way to provide access to spreadsheet resources without sacrificing control over editing permissions. And since the XLSX file never has to travel beyond a secure application environment, there’s no need to worry about malicious file extensions when sharing spreadsheets.

Developers can use PrizmDoc Cells’s whitelabeling features to customize its look and functionality within their application. From editing cell content and format to embedding graphics, they retain complete control over the way viewers interact with spreadsheet files to maximize security and protect vital proprietary information. To learn more about how PrizmDoc Cells can enhance Excel spreadsheet security within your application, visit our product page to explore this powerful integration’s features.