Reimagining data for insurance decision-making
Insurers should include data and content management in any process-improvement initiative.
Accurate data is critical to making good decisions, and for insurers, good decisions are critical for them to thrive.
The good news: There is more data, from more sources, available to insurers than ever before.
However, many organizations are struggling with how to get the right information to the right person at the right time so they can make the most informed decisions during the policy and claims lifecycles.
The way insurers handle data has the potential to be transformative, which is precisely why insurers should include data and content management in any process-improvement initiative.
Preparing for unexpected changes
The last two years have redefined what it means to “expect the unexpected.” Insurers are rethinking processes and how they use both historical and new data for underwriting policies.
The abundance of free-flowing information that exists in a process from multiple devices and multiple touchpoints and having access to it in real time so underwriters don’t have to search each page for useful information means that insurers need to consider how to better integrate data and process. This, along with the analysis and mining of that data, enables insurers to see behaviors and radically question the methods and processes used for underwriting in the past.
Luckily, there are plenty of data-powered tactics to streamline efforts.
Consider recent catastrophe losses. Over the past several years, storms have worsened due to climate change, and they have hit different parts of the country that insurers hadn’t considered previously. For example, in 2019, there was a quiet start to the hurricane season, but Hurricane Dorian rumbled through the Atlantic in the late fall, surprising forecasters across the world. Extreme weather research and the impact of intensifying storm activity represent a growing data source.
As extreme weather is happening in unexpected areas of the world, such as the recent outbreak of more than 30 tornados reported across the southern and midwestern U.S., insurers need to consider fresh sources of information. Insurers need to be able to access data from such weather events to analyze risks as part of the underwriting process while also considering if historical data is good for creating rates and for predicting losses.
Ultimately, underwriters must figure out a way to retrieve data from a variety of sources that are not tied to insurance but have information that’s relevant to underwriting. But how do insurers get the right information and organize it into an understandable and readable format?
Reshaping your approach to data
For so long, insurers have depended on data warehouses and virtual mailrooms to store their data but this system creates bottlenecks to accurate and speedy decision-making. They present the common challenge of getting data from a raw to refined state, so their teams can extract real value from the information they have in front of them instead of being overwhelmed by it.
Call center operations are an example of this. There is critical client information available that customer service representatives (CSRs) often have a hard time accessing throughout the lifecycle of the policy. In fact, in a recent digital transformation survey from ABBYY, 92% of respondents said they waste up to eight hours a week searching documents for information they need to serve customers and do their jobs.
To meet this demand for faster access to data, there has been a huge upsurge in intelligent document processing automation that enables the ability to help insurers solve their data challenges. According to the ABBYY survey, nearly 60% of insurance decision-makers said they will be investing in low-code/no-code (LCNC) tools, and nearly 50% said they will be investing in intelligent document processing (IDP) and optical character recognition (OCR) technologies.
AI technologies like no-code IDP are growing in popularity due to their ability to search for and capture information and, more importantly, deploy human-like skills to better analyze, read, understand (and actually make sense of) content, helping insurers make better decisions, faster. This allows users to derive business-critical insights from insurance-related documents on a large scale and handle complex tasks that humans would otherwise perform.
Additionally, a Forrester survey has shown that digital transformation initiatives are delayed by misunderstood processes. Manual routing and process gaps further complicate claims and underwriting processes with 37% of business and technology decision-makers reporting that their organizations experience these problems.
Understanding these process challenges, 83% of business decision-makers plan to increase the adoption of process optimization, and 57% of them are planning to increase it significantly.
It’s becoming more apparent that having real-time insight into processes is extremely important. Insurers need total process visibility and the power to pull together all the data and sources that represent the steps in their processes, then put it in a format that lets them visualize and properly analyze it. Only then can they discover where bottlenecks occur, where repetition happens, where data is missing and where automation is working (or not) while also identifying exactly where automation can make the biggest impact.
Data is an asset and should be viewed as such. But to successfully capitalize on this asset, insurers need to adapt their operating models, reimagine their data sources and processes, and invest boldly in developing digital capabilities.
Eileen Potter (eileen.potter@abbyy.com) is head of Insurance at ABBYY, a digital intelligence company. These opinions are her own.
Potter has more than 25 years of insurance and insurance technology experience with extensive knowledge of commercial, personal, and specialty lines, including insurance operations on both the agency and company levels. She has worked in independent agencies and MGA operations in a variety of roles, including commercial marketing and underwriting. Her software background includes systems marketing, sales support, and implementation roles with organizations such as Appian, One, Inc., Duck Creek Technologies, and Fiserv, among others.
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