Technical FAQs

Independent Software Vendors can help their customers reach their full potential and stop being held back by outdated document management practices. As data volumes continue to skyrocket, last century’s manual filing and sorting methods just don’t cut it anymore. Organizations are seeking new and efficient solutions to bring order to their document chaos.

PrizmDoc’s AI-powered Auto Tagging and Classification is helping solve these challenges. This breakthrough technology automatically organizes document collections, leading to faster information retrieval for ECM users. As an independent software vendor, integrating this tool into ECM platforms is an easy way to deliver next-level Auto Tagging and Classification capabilities. 

Streamline Document Management with AI-Powered Auto Tagging and Classification

In the realm of Enterprise Content Management (ECM), efficient management of digital documents is essential. PrizmDoc’s Auto Tagging and Classification, leveraging IBM’s watsonx.ai technology, revolutionizes this process by automatically organizing documents and making them easily searchable. 

This feature enhances document organization by using advanced AI-powered algorithms to analyze, categorize, and tag documents based on their content. This AI-driven tool improves document search and retrieval as a result of accurate tagging and classification. With contextually relevant results, your users will benefit significantly as search times are reduced, boosting productivity. This solution not only improves operational efficiency but also enhances user experience, making document management seamless and effective.

Benefits of AI-Powered Auto Tagging and Classification

Document management presents significant challenges for many organizations. According to one study, nearly half of employees find it hard to find documents quickly when they need them. For businesses seeking to solve this problem through new applications, another hurdle is that 80% struggle with seamless data and system integrations. PrizmDoc helps independent software vendors overcome these issues. When integrated into ECM systems, PrizmDoc allows ISVs to deliver solutions that streamline document organization, improve search functionality, and enhance efficiency – addressing the most common documentation pains experienced by businesses today.

Enhanced Document Organization

Independent Software Vendors integrating third-party document management solutions like PrizmDoc significantly reduce the time to market for new, innovative features like the AI-powered Auto Tagging and Classification tool. This tool offers ISVs an advanced way to organize documents for users, streamlining organization, ensuring information is consistently labeled, and easily retrievable by categorizing and tagging documents based on content.

AI-Powered Search and Retrieval

PrizmDoc enhances search functionality by generating relevant tags through IBM’s watsonx.ai technology. This leads to more precise, contextually relevant search results, reducing the time users spend searching for documents and boosting productivity within your application.

Time and Cost Savings Through Automation

Manual tagging is labor-intensive and prone to errors. Automating this process with PrizmDoc reduces the need for manual intervention, leading to significant time and cost savings. This allows resources to be allocated to more strategic tasks, enhancing overall operational efficiency.

Consistency and Accuracy

Uniformity in tagging and classification is crucial for maintaining data integrity. PrizmDoc ensures consistency across all documents by applying the same criteria uniformly, minimizing errors, and ensuring reliable document management practices.

Scalability

As an ISV’s customer’s business grows, so does the volume of documents they handle. PrizmDoc’s Auto Tagging and Classification scales effortlessly, handling increased document loads without additional resources. This scalability is vital for businesses looking to expand without compromising on efficiency.

Integrating PrizmDoc’s features within your tools can revolutionize document management, providing your clients with a competitive edge through enhanced efficiency and user experience.

Seamless Integration and Customization 

PrizmDoc provides seamless integration into ECM solutions for ISVs, allowing users to process documents without leaving the ECM environment. This ensures data security while enabling single-platform document management, viewing, annotation, and processing. PrizmDoc’s robust API empowers customization to fit individual systems. It seamlessly maintains security while boosting efficiency, empowering ISVs to deliver enhanced solutions, and clients to focus on strategic tasks driving business success.

Overcome AI Challenges for ISVs with PrizmDoc’s Built-In Auto Tagging and Classification

ISVs often face challenges in developing and maintaining their own AI solutions, including high costs, resource allocation, and the need for specialized expertise. PrizmDoc addresses these issues by providing built-in AI capabilities. By leveraging PrizmDoc’s advanced tools, such as Auto Tagging and Classification, ISVs can enhance their offerings without the burden of developing AI from scratch, enabling them to stay competitive and meet client demands efficiently.

Use Cases for Auto Tagging and Classification

Streamlining Legal Document Processing During eDiscovery

Law firms that need to manage large volumes of documents during litigation can quickly become overwhelmed. PrizmDoc’s Auto Tagging and Classification automatically organizes and tags legal documents based on document type and content, reducing manual effort and ensuring quick retrieval. This efficiency allows law firms to focus on case strategy rather than administrative tasks, ultimately improving case outcomes.

Unleashing ECM Platform Potential with Auto Tagging and Classification

PrizmDoc enhances ECM with advanced Auto Tagging and Classification. This allows in-browser document viewing, annotation, and processing within ECM. Streamlining tasks boosts productivity over external tools. For ISVs, PrizmDoc offers easily integrated AI solutions, removing in-house AI challenges and allowing ISVs to focus on solutions while growing business success rather than developing AI.

Schedule a demo now to see how Auto Tagging and Classification can supercharge your customers’ document management!

FinTech applications have become indispensable to the financial services sector, enabling users to easily engage with financial offerings in a manner that suits them, while also boosting operational efficiency. The industry’s ongoing digital transformation continues to redefine FinTech functions, with developers tirelessly crafting new apps capable of handling tasks formerly dispersed across numerous systems and software.

Among the most crucial features of FinTech applications is the ability to view and share documents. Developers have a range of document lifecycle solutions at their disposal to circumvent the challenging process of building these features from the ground up. However, the financial sector presents distinct security and compatibility prerequisites when it comes to choosing partners for integration. To truly grasp these technical hurdles, it’s important to understand the significance of Java in the development of FinTech applications.

A (Brief) History of Java in the Financial Sector

Financial institutions pioneered the adoption of automated workflows. The advent of the first electronic communication network that facilitated the trading of financial products off the trading floor was seen as early as the 1960s. During the 1970s, computerized order flows saw greater acceptance, with most financial companies crafting their own proprietary systems. The digital revolution truly ignited in the 1980s and early 1990s with the launch of the Bloomberg terminal and the Financial Information eXhange (FIX) protocol. By the late 1990s, the Nasdaq enabled the execution of securities trades autonomously, without the need for manual interference, through the incorporation of Island ECN.

Java shook up the programming language world when it debuted in 1995, and its timing couldn’t have been better. The financial industry witnessed an extensive wave of mergers and acquisitions in the late 1990s and early 2000s, which resulted in several companies grappling with the integration of a multitude of applications and data. Java’s ability to support diverse platforms was an appealing solution to this challenge, and numerous financial applications were translated into Java. Sun Microsystems, which first introduced Java to the market, even adopted the slogan “Write once, run anywhere” to promote its flexibility. Java’s simplicity of use and significantly enhanced speed compared to legacy code on outdated platforms quickly made it the language of choice for developers.

In a few short years, Java ascended to become the leading programming language within the financial services industry. Its popularity surged again following the launch of OpenJDK, a free and open-source version of the language, in 2007. An Oracle report in 2011 estimated that over 80% of electronic trading applications and virtually all FIX engines were written in Java. Even close to three decades after its debut, Java continues to be the primary programming language employed by financial services, surpassing other open-source alternatives by a considerable margin.

Java’s Enduring Appeal for the Financial Industry

The enduring preference for Java among financial sector developers isn’t simply due to tradition or resistance to change. Java’s unique attributes are an exceptional fit for financial applications, spanning both long-established enterprise-level banking systems and pioneering FinTech solutions.

Security

In the realm of financial services, security is the highest priority for developers. Applications related to banking and trading must have robust security provisions to guard financial data and personally identifiable information against unauthorized access. Java simplifies data access restriction and provides an array of memory safety features to diminish potential vulnerabilities, particularly those stemming from prevalent programming mistakes. Oracle consistently rolls out regular updates to fix recognized vulnerabilities and tackle the most recent cybersecurity threats.

Portability

Java, being a platform-independent language, allows applications to operate on virtually any device. This has always been a substantial benefit in the financial sector, but it has proven even more crucial in the era of cloud computing and mobile applications. Developers can employ the same code to roll out software in a virtual environment and render it accessible to end-users via their smartphones, computers, or other devices. The ability of Java virtual machines to support additional programming languages only adds to the language’s versatility.

Reliability

Given the nearly three-decade-long consistent use and the backing of a robust development community, Java has established itself as one of the most dependable programming languages globally. Potential instabilities have long been addressed, and there is a wealth of developer tools and documentation at hand to ensure software is built on a solid foundation. This reliability is critically significant for banking and financial applications, which demand high performance levels coupled with fault tolerance.

The Value of Java-Based Document Viewing and Sharing

As FinTech developers continue to build novel applications aimed at simplifying life for clients and employees in the financial industry, they’re facing a growing expectation from users for superior document viewing and sharing capabilities. Users want to bypass the time-consuming and resource-heavy task of manually processing paper documents, and most organizations strive to eliminate the security hazards associated with using external applications for managing digital documents.

However, developers face significant challenges when attempting to build these complex document viewing capabilities from scratch. Although there are numerous integrations that can introduce document lifecycle features, most aren’t based in Java and need extra development work to embed them into existing FinTech solutions. Without the option to natively view, share, and edit documents within the Java application, users frequently resort to external programs, a practice that presents potential security issues and version discrepancy risks.

Facilitating Java-based Document Functionalities through PrizmDoc^® for Java

Accusoft’s PrizmDoc^® for Java, formerly VirtualViewer^®, is a robust, Java-based HTML5 document viewing tool designed to assure optimal compatibility with FinTech applications without compromising functionality and security. By supporting an array of document types, such as PDF, TIFF, JPEG, AFP, PCL, and Microsoft Office, PrizmDoc® for Java creates a streamlined viewing experience that eliminates the need for external viewing solutions.

As an integration built on Java, PrizmDoc^® for Java can operate on nearly any operating system and is simple to deploy. There’s no need to install software on the user’s desktop, enabling FinTech developers to deploy a scalable solution that fulfills their crucial security and business continuity needs within a single, high-velocity application. PrizmDoc^® for Java’s server component swiftly renders and dispatches individual document pages for local viewing as required, allowing users to access, view, annotate, redact, and manipulate financial documents instantaneously. Since documents are rendered within the web-based viewer, users never have to download or transfer files, which could put sensitive data at risk.

Experience PrizmDoc^® for Java’s features for yourself by signing up for a free trial!

Ongoing Legal Digital Transformation

There are many challenges facing the legal industry that legal tech and new emerging legal technology can help solve, but getting firms to adopt new technology to address these challenges can be a hurdle.  But the most recent challenge within the eDiscovery process is compounding them all. 

The Arrival of New eDiscovery Challenges

The change to a remote/hybrid work environment starting in 2020 during the worldwide COVID pandemic transformed the working world. Even while some companies have returned to the physical workspace, hybrid and fully remote working conditions continue to exist. This means that the collaborative working social platforms and mobile apps we all used to communicate and work with (Teams, Slack, Zoom, Webex, WhatsApp, Google Meet, etc.) are here to stay. 

Regardless of whether employees are in-office, hybrid, or working remotely, using these collaborative working social platforms has become the new norm. 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.

Compounding the Problem

Processing this new collaborative working social content is a big enough challenge on its own. Unfortunately, many in the legal industry weren’t fully optimized with their digital transformation by adopting previously available legal tech. While some traditional eDiscovery tools have reached maturity and are being utilized by firms, many slower-to-adopt firms are still fighting internally to have legal tech implemented.

How can firms (both early adopters and those still in the digital transformation process) prepare for eDiscovery across these new platforms filled with chat streams, emojis, and video recordings?

Enter Third-Party Software Integrations

Legal tech independent software vendors (ISVs) can be assured that there is technology available that can support their eDiscovery across these collaborative working social platforms. But better still, they don’t need to build a solution from scratch. 

Readily available and easy to adopt, third-party software integrations allow ISVs to add the capabilities they need without disrupting development timelines or building features from scratch. The ability to view, search, annotate, and redact content within documents securely inside an existing application without sacrificing everyday functionality is powerful.

Take on Your eDiscovery Challenges with Accusoft

Accusoft software integrations help legal tech ISVs build a more productive process for case review and eDiscovery. With unique technology that enables easy digital document processing, manual processes like search and redaction are no longer labor-intensive. Accusoft’s digital document lifecycle technologies streamline collaboration and information-sharing while keeping files secure and original metadata intact.

Looking specifically to address the new challenges of processing new collaborative working platform content within your eDiscovery process? Accusoft’s solutions can not only view these new collaborative platform transcript file types (including JSON, VTT, DOCX) but also search, redact, and offer secure collaboration directly inside your application.

To learn more about how Accusoft integrations can support your legal digital transformation and eDiscovery challenges, talk to one of our technology experts today.

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For more information on Accusoft’s software integrations for eDiscovery, case, and practice management applications, visit our Legal industries page.

Barcodes continue to be an essential tool for today’s organizations, whether they’re using them for managing supply chains or sorting documents within a complex digital workflow. Since the early 1990s, however, the potential use cases of barcodes have expanded tremendously. That’s largely due to the invention of the quick response barcode, better known as the QR Code. Developed by the Japanese manufacturer Denso Wave in 1994, this two-dimensional barcode revolutionized the way data was encoded and scanned. Today, QR Codes can be found practically everywhere, along with their smaller cousins, the Micro QR Code.

What Is a Micro QR Code?

Although the standard QR Code could hold a tremendous amount of information, that ability occasionally created challenges for specialized use cases where space was at a premium. Small components like circuit boards or machinery parts, for example, often couldn’t accommodate a QR Code. Even when they could, much of the QR Code’s storage capacity wasn’t being used to its full potential. For use cases where space was at a premium and only a small amount of data needed to be encoded, a more compact version of the QR Code was needed.

The Micro QR Code was designed to solve this specific challenge. Roughly half the size of the conventional QR Code, this smaller version still provided many of the benefits of its bigger cousin, including finder patterns to orient the image properly, multiple levels of error correction, and support for Japanese Kanji, Kana, and Hiragana characters.

The Anatomy of a Micro QR Code

A Micro QR Code consists of four elements that allow it to encode data and provide a barcode reader with instructions for how to read the contents.

Data Modules

Like any other QR Code, Micro QR Codes store binary data in square modules. While the human eye only registers the black modules, a computer scanner also registers white modules when reading the code. A black square represents a binary 1 while white squares are read as a binary 0. The amount of information that can be encoded into these modules changes depending upon the size of the barcode. Micro QR Codes can be written in four different sizes (more on that in a moment), allowing them to store up to 35 numeric digits, 21 alphanumeric characters, or 128 data bits.

Finder Pattern

The finder pattern is the square “bull’s eye” that appears in the upper-left hand corner of a Micro QR Code. This pattern ensures that the barcode is oriented and scanned correctly when read by an application. Since Micro QR Codes contain less complex data, they only require a single pattern finder while a conventional QR Code uses three. While many QR Codes also require an alignment pattern to correct for crookedness or distortion, Micro QR Codes are not large enough for these problems to create much of an issue during scanning.

Timing Pattern

A series of alternating black and white modules running vertically along the left side and horizontally along top of the barcode, the timing pattern is used to configure the rest of the data grid for the scanner. By reading the timing pattern, the scanner software can quickly determine the size of the barcode’s data matrix, as well as the symbol and version density.

Quiet Zone

A clear margin space surrounding the rest of the barcode elements, the quiet zone makes the boundaries easy for scanning software to detect and identify. While a conventional QR Code requires four or more modules of empty space, a Micro QR Code only needs a two module-wide space. This helps to keep the barcode compact regardless of how much data is encoded within it.

Micro QR Code Sizes and Error Correction

Depending upon the amount of data encoded, Micro QR Codes can be written in one of four sizes. The smallest version, M1, consists of 11×11 modules, while the largest, M4, is 17×17 modules. Each size above M1 can support different levels of error correction, although the more thorough the error correction, the less data can be encoded.

Error correction is based on the Reed-Solomon algorithm and allows scanning software to recover lost, poorly printed, or damaged barcode data. Versions M2 and M3 offer two levels of error correction:

• Level L (Low): Capable of recovering up to seven percent of encoded data.
• Level M (Medium): Capable of recovering up to 15 percent of encoded data.

As mentioned above, higher levels of error correction impact the amount of data that can be encoded into Micro QR Code modules. That’s because the redundancies necessary to support error correction algorithms take up available space. Increasing an M3 barcode’s error correction from level L to Level M, for instance, would reduce the number of numeric characters that could be supported from 23 to 18.

An M4 Micro QR Code contains enough modules to support a third level of error correction:

• Level Q (Quartile): Capable of recovering up to 25 percent of encoded data.

Although level Q provides excellent durability, it leaves much less space for encoding data. An M4 barcode with this level of error correction actually holds less data than an M3 barcode with level L error correction. When writing a Micro QR Code, it’s important to determine what level of error correction is actually necessary for the use case at hand rather than simply defaulting to the most robust option.

Differences Between Micro QR Codes and Conventional QR Codes

While Micro QR Codes use many of the same 2d barcode principles as traditional QR Codes, it’s not quite accurate to think of them as a condensed version. They have some notable differences that make them more or less suited to specific use cases.

Micro QR Codes

• Provide up to three levels of error correction.
• Needs only a single finder pattern for orientation.
• Can encode up to 128 bits.

Conventional QR Codes

• Provide up to four levels of error correction.
• Requires three finder patterns for orientation.
• Can encode up to 23,658 bits.

Enhance Your Barcode Capabilities with Barcode Xpress

Adding barcode recognition capabilities to an application can help to streamline document management workflows and allow organizations to route files more efficiently. Developers can easily integrate the ability to read and write barcodes into their platforms using a barcode SDK like Accusoft’s Barcode Xpress. With support for more than 30 unique barcode types, including Micro QR Barcodes, this versatile SDK provides the tools to support a wide range of use cases that call for fast, accurate barcode recognition.

For a hands-on evaluation of how Barcode Xpress will perform in your development environment, download a free trial today or start a conversation with one of our SDK specialists.

Despite its reputation for being slow to adapt and held back by outdated, legacy technology, the insurance industry is undergoing a tremendous period of digital transformation. A new generation of InsurTech applications are helping insurers respond more quickly to a dynamic market and empowering customers to become more engaged with their policies. InsurTech digital collaboration is a key industry trend.

Digital collaboration tools are critical to this dramatic shift, which has created a unique opportunity for InsurTech developers. By deploying features that allow insurers to streamline workflows and improve communication both with internal stakeholders and customers, developers can capitalize on an emerging need and establish their applications as the “new standard” for digital collaboration in the insurance industry.

Creating Better Digital Collaboration Tools for InsurTech Software

Accessible Viewing

The ability to easily access and view insurance documents is increasingly important to insurance agents and customers alike. When assembling a policy bundle, insurance agents must reference multiple pieces of information about customers as well as detailed actuarial data from a variety of sources. By building HTML5 viewing capabilities into InsurTech applications, developers can help underwriters reference all relevant information within their existing workflow. Rather than ponderously requesting documents from other departments and receiving them via email, and opening them with an external program, they can simply request, search for, receive, or view files without ever exiting their secure application.  

Customers, meanwhile, expect to be able to access their insurance records quickly and easily. Whether it’s a detailed description of their policy or a copy of their proof of insurance, they want the ability to log into a web-based application that allows them to locate and view records related to their account. This can greatly improve communication with their insurer since they’re able to quickly reference different aspects of their policy and identify their needs more clearly. Developers can build viewing features into an InsurTech application so customers can access their essential documents without having to download anything or take any additional steps. Insurers can also use the same features to easily provide updates about policies or rates. 

Annotations

Building an insurance policy or evaluating claims can be a lengthy and confusing process without the right digital collaboration tools in place. Documents often need to be reviewed by people in different departments before bundled services and rates can be finalized. If an InsurTech application lacks collaboration features, insurers may need to resort to emailing documents back and forth along with their comments. There is ample space for miscommunication in this scenario, with vital comments potentially going unnoticed or the wrong document being sent as an attachment.

Built-in annotation tools allow insurers to leave comments, highlight areas of concern, and provide helpful notes directly on the files themselves. Developers can also make it possible to share and view those documents entirely within the application environment, which reduces the risk that someone will overlook important comments or compromise privacy by opening a file with poorly secured software. Annotation markups are stored separately from the original file until they need to be burned into a new copy. This protects the integrity of the source document throughout the collaboration process.

Version Control

One of the biggest challenges with digital collaboration is maintaining version control over documents. When multiple people are working on a file, it’s important to make sure that everyone is using the most up-to-date version of it. This is especially true of insurance documents because rates and risk adjustments can sometimes change quite rapidly. The last thing an organization (or their customers) want is to have inconsistencies spread across several documents due to poor version control.

Developers can combat version confusion by keeping every stage of document workflows within their InsurTech applications. Version problems are usually caused by people downloading documents, working on them in isolation with a separate program, and then uploading their changed versions back into the application. By making it possible to view and annotate content within the application, developers can help ensure that everyone is working from the most up-to-date version of every file. 

Conversion

InsurTech applications must be able to handle a wide range of file types if they’re going to effectively facilitate digital collaboration. Customers often need to upload images as part of their insurance claims and will often provide documents as scanned images that can’t be searched for key text. Without the ability to convert files into more manageable formats, collaboration can quickly become an exercise in frustration and confusion.

Conversion tools not only make files more accessible, but also make it easier to manage content. Several small documents, for instance, could be combined into a single file for faster access, review, and markup. Developers can also incorporate Optical Character Recognition (OCR) into their InsurTech application to extract the text from a document image and use it to create a searchable PDF for more convenient reference. These conversion tools provide a great deal of workflow customization that allows their customers to set up efficient processes that help them deliver better services.

Boost InsurTech Digital Collaboration with PrizmDoc Viewer

Accusoft’s PrizmDoc Viewer is an HTML5 that integrates smoothly into your InsurTech application to deliver a powerful array of digital collaboration tools. Using a sophisticated collection of REST APIs, PrizmDoc Viewer provides support for multiple file types and can easily convert between formats to simplify insurance workflows. It also features a full range of annotation and redaction tools as well as OCR text extraction and electronic signature features.

With three decades of experience developing imaging and document management technology, Accusoft offers a variety of software integrations that can support digital collaboration efforts. From document assembly to secure spreadsheet support, our collection of SDKs and APIs can provide the features your InsurTech application needs to meet the evolving demands of the insurance industry. Check out our InsurTech fact sheet to learn how you can turn our capabilities into your capabilities.

Despite the explosive growth of big data and sophisticated analytics platforms, a 2019 study by Deloitte found that 67 percent of business leaders are not quite comfortable using them to inform decision making. For many organizations, spreadsheets remain the preferred tool for managing data and evaluating trends. Developers looking to build the next generation of business applications can accommodate those tendencies by integrating native spreadsheet support for Microsoft Excel workbooks.

Excel Worksheets vs Excel Workbooks

Although sometimes referred to interchangeably or described broadly as spreadsheets, there is a key distinction between an Excel worksheet and an Excel workbook. A worksheet consists of only one spreadsheet while a workbook contains multiple different spreadsheets separated by tabs.

The difference may not be very important when viewing or sharing XLSX files natively in Microsoft Excel, but it can create serious challenges when rendering those files in another application. Without some way of accurately rendering dynamic spreadsheet data, viewers are often forced to resort to a static print preview image. This process makes the file viewable, but also leaves it “flattened” because all interactive elements are removed from the spreadsheet cells.

If the workbook contains worksheets with linked data (that is, cell data from one sheet is affected by cell data from another sheet), it’s critical that a viewing solution preserves the dynamic aspects of the file. The advantage of a spreadsheet is that it can serve as a working document. Without the ability to interact with it, users might as well simply copy and paste the data into a text document.

Managing Excel Workbooks with PrizmDoc Cells

PrizmDoc Cells provides several options for managing Excel workbooks, making it easy to transition back and forth between XLSX format and web browser viewing. Once a proxy route is set up within the application to send API calls to the PrizmDoc Cells server, three different commands can be used to manage Excel workbooks.

Upload Workbook

This API call adds a new XLSX file for viewing and editing. When a document is uploaded to the system, the server assigns a unique workbook ID to it so it can be found and rendered in the application’s viewer in the future. After uploading a workbook, a new session can be created using the workbook ID for viewing and editing purposes. 

Download Workbook

When PrizmDoc Cells displays a spreadsheet, it renders the XLSX file itself, but it doesn’t make any alterations to that file. As each session makes edits to the workbook, those changes are associated with the document ID rather than the original XLSX file, which preserves the integrity of the original spreadsheet. At some point, however, those edits may need to be saved into a new Excel workbook. 

The download API call converts the current session document so it can be downloaded as an XLSX file. File availability can be set during the download process to control who will have access to the new workbook.

Delete Workbook

Old versions of workbooks often need to be deleted for security reasons, usually because they contain confidential data. Since the original XLSX file remains safely within application storage, there often isn’t much sense in retaining workbooks IDs that aren’t being used. The delete API call removes a workbook ID from the server. Once removed in this way, the workbook cannot be viewed, edited, or downloaded by PrizmDoc Cells.

Preserving Workbook Functionality

Since PrizmDoc Cells natively renders information contained in an XLSX file, it retains the dynamic elements that make spreadsheet workbooks so useful to organizations. Not only does it preserve proprietary business logic and formulas, but it also maintains the integrity of this information across multiple worksheets. Cell content can still be searched to quickly locate important text or data throughout the workbook.

For situations where proprietary formulas need to be protected, PrizmDoc Cells allows users to upload XLSX workbooks as values-only files, with all spreadsheet formulas removed. Also, any cells locked in an uploaded XLSX file will remain locked in PrizmDoc Cells to preserve workbook security.

True Spreadsheet Workbook Support for Your Applications

Many organizations continue to depend upon spreadsheet workbooks to manage their business. By providing feature-rich workbook support within their applications, developers can help them retain control over their proprietary spreadsheet formulas without sacrificing the functionality they expect from Excel. 

PrizmDoc Cells makes it easier than ever to share spreadsheet workbooks without having to rely upon Microsoft Excel dependencies. Shared XLSX files can remain safely within a secure application environment to prevent unauthorized downloads or troublesome version confusion. Get a first-hand look at how PrizmDoc Cells can enhance your application in our extensive online demo.

Few industries have been impacted by the proliferation of digital technology than the financial services sector. In fact, it’s one of the few markets where the average consumer can easily observe how much has changed in a short amount of time. Many people haven’t even set foot inside a bank for years, and millions pay all of their bills exclusively online. According to the US Federal Reserve, personal checks declined from 58.8 percent of non-cash payments in 2000 to just 8.3 percent in 2018. Both of these trends are driven by the increased convenience of FinTech applications, and the same changes have impacted the lending industry, as well.

What Is FinTech Lending?

Since the 2008 financial crisis, a new breed of lenders has become a disruptive force in the banking sector. Unburdened by the cumbersome infrastructure that makes large financial institutions slow to adapt to change, FinTech lenders utilize the latest technology to deliver a more responsive, personalized, and transparent lending experience to consumers. These innovative startups have combined easy-to-access digital platforms with sophisticated data analytics to streamline the lending process and deliver funds to borrowers much faster than could be accomplished with traditional loans.

Borrowers, it seems, have been quick to embrace this alternative source of lending. From 2013 to 2018, FinTech companies increased their share of the personal loan market from a mere five percent to thirty-eight percent. That rapid growth is a result of increased penetration into the digital marketplace and more flexible credit scoring that allows FinTech lenders to assess risk and approve loans more effectively. 

In the early days of the industry, most FinTech lenders still relied upon traditional FICO credit scores when evaluating a borrower’s potential to repay loans. Over time, however, they have used a variety of alternative scoring mechanisms driven by data collection algorithms to create a more dynamic picture of a borrower’s credit status. Between 2007 and 2015, for instance, the correlation between FICO scores and the rating system used by one prominent peer-to-peer FinTech lender declined from 80 percent to just 35 percent.

The “Tech” Behind FinTech Lending

The loan adjustment algorithms working under the hood of FinTech lending applications are incredibly sophisticated, but they need good data for fast, accurate underwriting. While traditional lenders focus on predictable data points like income, debt payments, and assets, the digital nature of FinTech applications allows them to go much more granular. By gathering insights from other customer applications, internet searches, and even geolocation data, they can create a more complex profile of each customer, which then allows them to structure loans and other financial products that meet their specific needs while also protecting the lender to unnecessary risk.

This new approach to lending has helped FinTech applications to cut down the “time to yes” on credit decisions from the three to five weeks commonly seen from traditional banks to as little as five minutes. Even more critically, they can use digital funding to deliver cash to borrowers in less than 24 hours compared to the typical lender’s three month response time.

Improving “Time to Yes” on Credit Decisions

In addition to deploying more sophisticated risk adjustment algorithms to assess credit worthiness, there are some additional ways that FinTech lenders can continue to improve performance and efficiency.

Embrace Paperless Automation

The first and most obvious step they can take is by eliminating paper forms from the application process whenever possible. One of the reasons why banks and other financial services organizations move so slowly is due to the time it takes to fill out, fax, scan, and review physical documents. Not only are these forms inefficient, but they’re also prone to clerical errors when an applicant’s data needs to be transferred from the form into a database or application. By digitizing the application process wherever possible and automating data capture, FinTech lenders can significantly cut down on processing times and eliminate the human errors that so often create additional delays.

Increase Document Management Versatility

Shifting to an emphasis on digital documentation brings another complication along with it because there are a variety of file formats used throughout the financial industry. Some documents need to be in a specific format for compliance purposes, and if customers are submitting files through a FinTech lending platform, they could be using multiple different file types. 

In order to streamline processing, FinTech applications need to be able to easily convert a wide range of file types into a few key formats that work best with their processing workflows. That means FinTech developers will need to integrate powerful document conversion tools into their software to ensure that they can avoid any troublesome incompatibility issues during loan processing.

Enhance Data Capture Capabilities

Although FinTech lenders are developing incredible algorithms capable of analyzing massive amounts of data to shorten credit application times, they are still dependent upon the information made available to them. That means developers need to implement data capture tools that can pull key data from a variety of sources and compile it into an easily searchable format. 

Optical character recognition (OCR) engines can quickly extract information for any number of documents and images to create searchable files that FinTech software can quickly process as needed. For hand-printed documents scanned into digital format, intelligent character recognition (ICR) tools can be deployed just as effectively, allowing FinTech lenders to gather data from a wide variety of sources.

Expand FinTech Lending Capabilities with APIs and SDKs

One of the easiest ways for FinTech developers to quickly build lending-friendly features into their applications is to leverage API and SDK integrations. Rather than building new functionality from scratch, they can instead take advantage of existing, proven solutions to enhance their applications. This allows them to keep the focus on the core differentiators of their FinTech lending platform, allowing them to process and approve loans faster while minimizing potential risk.

Accusoft’s collection of API and SDK integrations provide powerful viewing and processing capabilities when it comes to FinTech workflows. Whether you need to convert multiple file types quickly, clean up document images, or perform OCR data capture, Accusoft has the solution to unlocking your FinTech lending application’s potential.

Document image cleanup is a vital step in building an efficient and accurate processing workflow. In a perfect world, every file an organization receives would be in pristine, high-resolution condition so it could be processed quickly and easily. Unfortunately, the reality is that documents come in all sizes, conditions, and formats. Companies can receive vital information in the form of email, traditional mail, fax, or even text. Documents scanned into a crooked, low-resolution file are just as likely to be received alongside digital versions submitted entirely through a web application.

This poses a significant challenge for software developers building the next generation of automation solutions. Without some way of cleaning up document images, companies that still rely upon manual processes will struggle to read and process files. More importantly, poor image quality interferes with optical character recognition (OCR) engine accuracy, making more human interaction necessary to verify recognition results. By integrating document image cleanup tools into their applications, developers can enhance the speed and accuracy of their automated processes and help their customers leverage the full potential of digital transformation.

7 Essential Document Image Cleanup Features Your Application Needs

There are a few essential document image cleanup tools that should be considered absolutely essential for any application that has to manage multiple file formats. To see these tools in action and understand why they’re so vital, let’s take a look at how these features work in ImageGear, Accusoft’s powerful document and image processing SDK integration.

1. Despeckling

Speckles can appear on document images for a variety of reasons. In some cases, they are unwanted image noise created during the original scanning process (the classic “salt and pepper” noise), but in other instances, they’re simply the result of dust particles on the surface of a scanned document or on the scanner itself. They are frequently encountered when converting old documents into digital form. Speckling not only interferes with OCR engine performance, but can also make it difficult to maintain image fidelity when compressing or converting files. 

ImageGear can reduce or eliminate speckling as part of the document image cleanup process. There are two ways to approach speckle removal:

• Despeckle Method: This function removes color noise from 1-bit images by taking the average color value in a square area around the speckle and replacing its pixels with that value.
• GeomDespeckle Method: This function uses the Crimmins algorithm to send the image through a geometric filter, reducing the undesired noise while preserving edges of the original image. This process is applied only to 8-bit grayscale images.

2. Image Inversion

With so many documents being scanned, converted, and transferred between applications, there’s a greater likelihood of something going wrong along the way. One of the most frequent problems is image inversion, which swaps pixel colors and turns a standard white background with black text into a black background with white text. This mix-up can render documents completely unreadable by OCR engines.

ImageGear can be configured to automatically recognize when image inversion is necessary. The invert method can also be used to immediately change the color of each pixel contained in the entire image, turning white to black and black to white.

3. Deskewing

Skewed document images are both cumbersome to manage and challenging for OCR engines to read accurately. Unfortunately, manually scanned documents are often uneven, and the problem is only becoming worse now that many people are using their phone cameras as makeshift document scanners. That’s why the first step in the document image cleanup process is often deskewing, which rotates and aligns the images to enhance recognition accuracy.

The deskewing process often involves more than just rotating a document, especially where images taken by a digital camera are concerned. ImageGear’s 3D deskew feature corrects for perception distortion, which can occur whenever a document is scanned by a handheld camera, using a sophisticated algorithm.

4. Blank Page Detection

Many documents converted into digital format contain information on both sides. If they are fed into a scanner along with single page documents, the resulting file will contain multiple blank pages. This might not seem like much of a problem, but if there is enough speckling or noise around the edge of the image, an application may try to apply an OCR engine to it and generate an error result. Blank page detection can quickly identify any image that is blank or mostly white and flag it for deletion.

5. Line Removal

Although they may not seem very troublesome at first glance, lines can create a number of problems for OCR engines. When lines and printed text overlap, it can be difficult for the engine to distinguish between the two. In some instances, the engine may even misread a line as a letter or number. Removing lines from a document prior to OCR reading ensures that the remaining text will be recognized more quickly and analyzed more accurately.

ImageGear supports both solid line removal and dotted line removal. The first method automatically detects and removes any horizontal and vertical lines contained in the document (like frames or tables), while the second method determines which dotted lines to remove by measuring the number and diameter of dots.

6. Border Removal

When scanned documents don’t align properly with the boundaries of the scanner or were copied onto paper that was larger than the original image at some point, the remaining space is often filled in with black. These borders are not only unsightly, but they also interfere with other document image cleanup processes. Although they can usually be cropped out easily, the cropping process alters the proportions of the image, which could create more problems later.

Removing these large black regions is easy with ImageGear’s CleanBorders option. It focuses on the areas near the edge of the page, which typically should not contain any important image data. 

7. Remove Hole Punches

Important documents were often stored in binders before they were prepared for digitization. When scanned, the blank space from the hole punch leaves a large, black dot along the edge of the document. Unfortunately, these holes sometimes overlap with text or could be picked up as filled-in bubbles by an optical mark recognition (OMR) engine.

ImageGear can identify and remove punch holes created by common hole punchers, including two, three, and five hole configurations. The RemovePunchHoles method can be adjusted to account for differing hold diameters in addition to different locations.

Unlock Your Application’s Document Image Cleanup Potential with ImageGear

Although ImageGear can perform a variety of document handling functions such as viewing, conversion, annotation, compression, and OCR processing, its document image cleanup capabilities help applications overcome key content management challenges and enhance performance in other areas. Improved document image quality allows data to be extracted more quickly, enhances the viewing experience, and reduces complications when it comes to file compression and conversion.

Learn more about the ImageGear collection of SDKs to discover how they can deliver versatile document and image processing to your applications.