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Automation in the insurance industry isn't limited to processing claims. Learn more about the common use cases of automation in the insurance industry.
The insurance industry has historically been slower than most to adopt automation technology, despite the advantages it offers. A 2020 report from PWC indicated just how detrimental the effect of this can be on their customer base. Out of 6000 people included in the PWC survey, 41% of insurance buyers said they were likely to switch providers due to a lack of digital capabilities and 15% of them identified this area as the topmost challenge while interacting with insurers.
The demand for ease of use and digitization from insurance clients is only growing. This is especially true as the digital generation starts to take over the consumer base. Automation allows insurers to offer faster and better customer service, primarily by improving workflow efficiency and lowering the risk of human error. To help you better understand these benefits and more, we’ve put together a comprehensive guide to automation in insurance.
Like many industries, insurance has always been plagued with high volumes of repetitive tasks. This alone should have made it fertile ground for automation to develop and yet, many insurance companies continue to rely on manual processing. Even as others in finance adopted AI and machine learning, insurance seemed to lag. The technology is readily available and brings with it numerous benefits, so why has insurance automation been slow to occur?
Robotic processes that use AI technology are far easier to adopt in processes that are already digitized. Ironically, what’s kept insurance manual is simply that it has always been so reliant on manual processes.
Automation is also best suited to repetitive, high-volume processes that are easily standardized. The input variability of insurance, in that a single claim can involve everything from medical reports to images of physical damage, also made it more difficult to shift to automation in insurance. Many claims also require delicate decision-making, which again was a tricky aspect to replicate with automation.
As discussed, insurers must contend with data collected from various sources when dealing with a claim. The range of formats the information comes in creates data complexities. Some documents are hand-written, some digital but ultimately both unstructured and structured data have to be dealt with in the claims process. Compounding this is the fact that information for these claims is often shared via multiple internal and external channels. This only makes data handling more complicated and without the capability to organize it all, it’s impossible to automate how the data is processed.
Not only are insurers expected to keep track of data that clients send in as supporting documents for their claims, but there is often important information in email messages as well as the customer’s insurance history to consider. Alongside this, clients might mail in physical documents such as slips, etc. that have to be validated and processed. One of the most significant hindrances to insurance automation has been how varied these data sources can be and the data complexity it causes as a result.
With how many data sources tend to be involved in a single insurance claim, there are also numerous stakeholders. Processing an insurance claim can include interactions between not just the client and the insurance broker, but claims admin, the adjuster, medical providers, and more. Involving more stakeholders adds to the complexity of the process and in turn, helps explain why it’s been so difficult for insurers to adopt automation.
All those different stakeholders represent different side streets that must be navigated in order to complete a claims process. Automation works best when the process is a single, main road with no obstacles. Saying that, technology has developed considerably. While certain processes will always require a degree of manual input, automation in insurance is expanding constantly.
Even though the insurance industry has not always been the fastest to automate, strides within the industry itself as well as the technology designed to serve it mean that it’s fast catching up. Insurance automation occurs in multiple lines, from data extraction to compliance and policy admin. Here are some key insurance automation use cases:
We’ve discussed just how scattered the information is that insurers have to grapple with when processing claims and how complex that can make automating data extraction, but now it’s time to talk solutions. Intelligent Document Processing (IDP) powered by machine learning and other technologies can help insurers extract data from various sources and return them in structured formats such as JSON or CSV.
Technology like this can process everything from handwritten documents to scanned invoices and PDFs. With IDP, all that information is digitized automatically in a fraction of the time manual data entry would usually require, and with far less risk of error. The result is accurate data that is easy to access and ready to be used by other solutions such as RPA for further processing, automation, or analysis.
Not only can automation technology speed up how information from supporting documents for claims is digitized, but by combining RPA and machine learning with great employees, the entire claims process is streamlined. For example, IDP can extract the relevant information from claims along with other supporting documents, such as blood test report, health examination report, etc., that come in as physical documents. The extracted data and the final information can then be sent into central claims systems and RPA can perform automatic tasks in the later stages.
By the time the information reaches an insurance employee, intelligent technology has already registered the claim and readied it for decision-making. Insurance automation like this significantly cuts down the need for insurers to waste time on menial tasks and not only that, it speeds up the entire claims process. By focusing their energy on the more complex aspects of the job and allowing the rest to be automated, insurers optimize their entire workflow. Clients get their claims outcomes faster and insurers are able to process more, in less time. It’s a win for all.
In the same way that automation technology can speed up data collection and analysis for claims processes, underwriting also benefits from these system improvements. The added task that underwriting requires is risk assessment based on the information received about a client and their desired policy. Aspects such as health risks, creditworthiness, and policy history all have to be taken into account.
Approximately 70% of this work can be automated with the use of IDP, bots, and other intelligent technology. This can extend from data extraction, classification, and analysis, to looking at a client’s history and the overall risk assessment according to an insurer’s internal standards. Automation in insurance is constantly improving to meet these needs, which is a reminder that what is available now is only going to be improved upon in the future.
The threat of compliance breaches and the resulting damage they can do to an insurance company is yet another area in which automation can have a positive impact. The regulations that insurers need to stay compliant with are often being updated, which only makes managing these processes trickier. That’s where AI-driven RPA comes in.
The technology can automate these complicated compliance checks, validate client data such as ID and proof of address, and generate regulatory reports. It can also automate checks on the alerts that come in from screening systems and limit the number of false positives insurers have to deal with from them. Overall, insurance automation in regulatory compliance allows for a faster, more accurate process which in turn helps to keep insurers better in line with compliance and less likely to face costly breaches.
Data and analytics are at the forefront of how businesses operate today. For insurers, staying on top of all the data is a significant challenge. The sheer volume of data and the fact that it’s in multiple formats makes centralizing that information with a manual system a slow and arduous task. Again, it’s an area where automation does some of its best work.
Tools like IDP, combined with targeted machine learning and AI, can not only digitize all that information with little to no human input required, but ready it for analysis far quicker and in the correct formats so that insurers are armed with better predictive information. Having data managed this way fundamentally empowers insurers with a better understanding of their business, their clients, and the way forward.
Every time a policyholder changes their address or wants another item added to their policy, that information needs to be added to the policy, and checks performed to ensure that everything is in line. This admin and servicing can be handled by automation, from the point at which the detail changes are received to the classification of the request.
Beyond the intricacies of underwriting and claims, insurance automation can also help with daily finance and accounting administrative tasks. Generating invoices and handling receipts can all be done through an automation system with OCR and machine learning. Not only that, but the financial data is digitized and more easily available for further analysis.
Shifting over to automation means that things like releasing payments to clients happen quicker and without the chance of human error. It’s yet another way in which automation in insurance impacts the overall efficiency of the business, and its ability to serve its clients.
We’ve touched on a few already but here are the main benefits of adopting automation in insurance businesses:
So many crucial processes within an insurance company are improved with the use of automation. Not only does this move from relying so much on employee involvement result in lower operational costs or fewer losses associated with human error, but a faster insurer is simply better able to meet client demands. People are impatient and they’ll take their business elsewhere if an insurer takes too long to process a claim. Automation in insurance allows businesses to keep those customers and that profit.
Bots don’t get tired and they don’t slow down. It’s why operational efficiency is boosted by at least 40% when tasks are automated. The impact of this improved workflow is far-reaching. It allows insurers to take on more work and ultimately, increase their revenue.
One of the most expensive parts of growing a business is having to increase a staff with it. Automation on the other hand allows insurers to scale while reducing costs and improving efficiency. The volume of work that an automated system can handle makes it far easier for businesses to expand quickly, and without necessarily having to hire more people. It makes growing an insurance business easier and cheaper.
Adopting automation in insurance begins with automating data extraction. FormX can help insurers extract data from documents with different layouts and formats so that they can start automating various tasks.
Contact us to tell us more about use cases and see how FormX can help you start automating various processes for your insurance business. Data complexity may have stopped insurers of the past from benefiting from all that automation has to offer, but with FormX, it doesn’t need to be an obstacle anymore. Digitization improves operational efficiency and the overall customer experience. Don’t get left behind.