Other parts of this series:
As I noted in my first post in this series, the right data capture approach can help insurers create value by reducing back-office costs. Many steps are needed before the rich rewards of big data can be reaped; of these, choosing the right data capture method for your organization is one of the most important.
Best-fit technology yields the best results. Here are a few of the established and emerging tools and methodologies insurers might consider as part of their data capture solution:
Word recognition technologies
Three primary technologies are commonly used to convert images or PDFs of static documents containing typed or handwritten text into machine-encoded text: optical character recognition (OCR), intelligent character recognition (ICR), and intelligent word recognition (IWR).
Some of these technologies have existed for many years, and have been consistently improved over that time. However, limitations exist – even when considering them as one suite of tools.
In order to achieve high accuracy rates, companies must spend a significant amount of effort and resources configuring and optimizing the technologies for each and every type of form to which the technology is applied. Even then, a significant amount of manual quality review and data entry capacity is required to support data capture through these technologies.
Application of text recognition technologies
One of the most common forms of applying recognition technology is through its incorporation into document management systems (DMS) and more broadly, enterprise content management (ECM) systems. ECMs have enabled certain global insurance firms to overhaul their entire legacy system and business information communications throughout every level of their enterprise.
While ECMs can improve a company’s IT infrastructure and increase efficiency, they are seldom the best single solution for data capture. Implementation can be expensive and time-consuming. However, today’s leading-edge technology providers can equip insurers with reliable, cost-effective data capture and transformation software that achieves extremely high accuracy levels and requires relatively little integration.
Mobile Data Capture
With mobile data capture (MDC), users take images of documents using a camera-equipped mobile device. The image data is sent to a data capture server that extracts the information stored in the image.
MDC is flexible, scalable, and increase speed while significantly decreasing the operating costs associated with data capture. It can be used effectively as the platform of a digital-first capture strategy; data is entered on the device and moves directly into a back-end system.
For this reason, it may be ideal for smaller, more contemporary entrants into the insurance industry; it is not appropriate as a one-size-fits-all approach for traditional insurers.
Crowdsourcing and machine learning
The merging of human and artificial intelligence is an approach to data capture that is at once flexible and scalable. Software alone, while far-reaching in its abilities to capture information from static sources, cannot accurately contextualize data. That ability remains a function of human intelligence. Crowdsourcing can thus be used to significantly enhance data capture software.
Data as a service
Data-as-a-service (DaaS) solutions such as those from Captricity make captured data available in a record that can be viewed and downloaded from a secure website or imported directly into existing CRM and ERP systems and statistical analysis tools. All interactions with the product occur via a web browser, agent, or application process interface (API).
My final post will look at how insurers can leverage the new data capture solutions and plot a new course for non-digital data capture in their businesses. To learn more in the meantime, download this report: Automation technology series: How automation can drive efficiency and enable growth in the insurance industry
How Automation Can Drive Efficiency and Enable Growth in the Insurance Industry
How Automation Can Drive Efficiency and Enable Growth in the Insurance Industry focuses on the challenges and opportunities that insurers and financial services organizations face as they look to automate their data capture process.