Data is an integral part of the insurance industry, and every process in the workflow needs data sourced from multiple channels. Today, many data-related transactions are automated but at times need manual interventions.
Modern technology has solved this problem to a large extent, and data from forms that are structured can be extracted with no human touch. However, in other cases, data is received from a high variation of unstructured documents with no rhyme or reason to the way information is presented. There may even be different languages or nomenclatures within the documents your team is tasked with processing.
Other companies have spent millions establishing business process outsourcing (BPO) to handle these unstructured documents. This solution can be effective, but it takes your team out of the process and results in less than desired data quality.
Need for Data Extraction in the Insurance Industry
As a result of high variation and unstructured documentation, many companies still rely on manual labor to extract vital data for downstream operational processes. Some of these workflows include:
• Quoting & Submissions
• Claims Adjudication
• Financial Reconciliation
• Quick Claims Settlements
All of the above tasks require accurate data, but relying on human workers is not only time-consuming and expensive, but it is also prone to error. Another downfall of using manual labor in data extraction is the limited amount of information a team can process.
Operations teams in the Claims and Underwriting departments are hobbled by low-value, repetitive manual processes like data extraction. Many employees spend their days hunting and pecking through incoming documentation to find the critical data they need for the next step in the business process before rekeying that data into a database or underwriting/claims system.
Incoming documentation is the source of valuable data, but often that data is contained in unstructured text or forms with multiple variations. Collecting and managing all types of documentation on your own is unproductive, primarily when different information must be extracted from each document.
What Is Automated Data Extraction?
Automated data extraction downloads relevant data in Excel, XML, CSV, or JSON format, or you may use Salesforce and Google Sheets connections. Data extraction software extracts variations across rental apps and provides that information to the exact location where you need it.
Augmenting the human effort to extract this data through automation can help reduce turnaround times and errors while increasing the amount of data extracted. Tools like Robotic Process Automation (RPA), Optical Character Recognition (OCR), and Intelligent Document Processing (IDP) help automate manual processes, in particular, the extraction of relevant data for digital use.
Limitations of Current Data Extraction Technology
Unfortunately, many tools on the market face limitations, making them inefficient at completing the job they were designed to do. Conventional data extraction tools fail in that they:
- Do not work with unstructured documents
- Are expensive to implement and maintain if there are many document variations
- Take SMEs out of the process – experienced judgment and understanding are removed from the process, resulting in data errors and manual rework
- Require expensive IT support for new documents or changes to the data model
- Do not work well with handwriting or multiple languages
These limitations can create further challenges to address and result in staff reviewing data manually to identify the issue. Now, a new innovative tool is entirely transforming the previous data extraction methods.
Get 100% Accuracy With 90% Automation Using AI/ ML-Based Data Extraction Platform
Tools like SortSpoke combined with rapid development platforms like FulcrumOne differentiates itself from competitors as the next generation of data extraction technology. Our data extraction platform achieves nearly 100% accuracy using 90% automation capabilities and 10% human intervention. By leveraging Artificial Intelligence (AI) and Machine Learning (ML), extracting data is becoming more intuitive than ever before. The rapid development platform, essentially a low-code business platform like FulcrumOne, uses microservices-based architecture to bring in prebuild components like workflows, rules engines, etc., to make the automation end to end. Now, you can effortlessly extract any data from any document in any language.
What is SortSpoke? SortSpoke is a cloud-based data extraction tool that uses AI/ML to help you turn even the most complex PDF documents into data. In contrast to other tools that use semantic language models, SortSpoke reads the text context and spatial layout using symbolic encoding. With SortSpoke, there are no templates to maintain and no preprogramming to be done. SortSpoke learns continuously, from scratch to extract only the data that your team needs freeing their time to focus on data quality and other higher-value activities.
SortSpoke is specifically designed to handle complex unstructured documents that present notoriously challenging extraction tasks, and it can be set up and running in the afternoon on any use case.
What is FulcrumOne? FulcrumOne is a cloud-ready foundational low-code platform accelerator comprised of cross-industry technical components, industry-specific components, and APIs ready to be deployed instantaneously. With FulcrumOne, customers can easily build and integrate all their digital transformation needs into one centralized low-code business platform.
Final Thoughts
When you use such next-generation platforms to perform data extraction tasks, your team and insurance company benefit in multiple ways. For instance, you gain value from having access to the most up-to-date and flexible data extraction software, one that matches you and your team’s business and analytical goals.
• Learn to extract any data from any document, in any language, even if those documents are unstructured
• Run without the need for templates or pre-programming
• Be up and operating in an afternoon with fewer than 100 sample documents
• Make it easy for even the most junior member on your operational team to extract data
• Allow you to learn continuously in real-time from interactions with your team
• Be managed, maintained, and controlled by your operational team
• Help your operations teams be 30% to 90% more productive