Implement Intelligent Automation to Improve Insurance Services

In every sector of the economy, Intelligent Automation (IA), also known as hyperautomation or Robotic Cognitive Automation (RCA), is transmuting the way business is done.  

IA systems are capable of detecting and producing large volumes of data, as well as automating entire processes or workflows while learning and adapting as they go.  

It is already assisting businesses in overcoming traditional performance trade-offs to attain new levels of efficiency and quality. 

The rate of digital transformation in the insurance industry is stepping up. Insurers are eager for change and are assessing which technologies will have the most influence on their operations in the quickest period possible.  

For insurers, intelligent automation is a critical tool. It goes beyond simply removing repetitive procedures by combining process mining, artificial intelligence (AI), and other advanced digital technologies. This means faster reaction times, cheaper operational expenses, and increased productivity for insurers. 

According to a study, more than 65 percent of insurance carriers will embrace at least limited automation by 2024, as new technology and changing customer expectations drive rapid transformation in the industry.  

However, the insurance industry today is heavily reliant on numerous levels of manual processes that make customers wait as personnel attempt to decipher complex documentation. 

Insurance companies can use IA to reinvent how they function in order to satisfy rising client demands and market challenges. IA solves complex corporate issues by automating a business process from beginning to end using a combination of robotic process automation (RPA) and machine learning (ML). 

In the insurance industry, traditional RPA and optical character recognition (OCR) have had minimal success. IA, on the other hand, can show the industry the way forward.  

IA can help these companies change how they operate in order to meet rising customer demands and compete more successfully. While many of these tools are new to the insurance industry, they can assist in scaling operations and creating resiliency in the face of catastrophic occurrences. 

IA can handle complicated issues in the insurance industry by automating not just a single process but an entire business function using a combination of technologies such as digitalization, RPA, and AI/ML. 

While the emergent automation tools have proved productive, the insurance industry has been slow in adopting them for various reasons. 

Why has the insurance sector been so hesitant to embrace automation 

The insurance industry’s sluggish adoption of automation can be traced back to several factors and there are a few roadblocks to fully utilizing automation’s potential.  

RPA has been used to automate digitized, repetitive, standardized, rules-driven, high-volume activities. But what happens if these automation requirements aren’t met?

These confines can greatly limit the extent of what can be automated due to the nature of the insurance sector and its underlying operations.  

In the insurance industry, issues including data input inconsistency, customer engagement intricacy, and nuanced judgement have all made RPA adoption difficult in the past, with mixed results. 

One of the root causes of process automation is that the data required for most insurance procedures might be organized, unstructured, or semi-structured.  

Moreover, this information is frequently disseminated across the insurance ecosystem via a variety of methods, including emails, PDF attachments, online portals, contact center calls, internal phone conversations, and faxes.  

Before even considering automation, each of these mediums demands that data be properly received, contextualized, and digitized with a high degree of accuracy. 

The insurance industry has been lethargic to embrace big digital developments and is often considered as a digital laggard. 

The most difficult part of using digital technology for most insurers is prioritizing how they will utilize it and then aligning on how it will be integrated into their systems and processes.  

They must determine which business challenges they must solve first, which will necessitate additional data, and how to operationalize those models in order to optimize their core production system. 

While impediments to automation continue to deter insurers from adopting it, they are quickly realizing that if they do not aggressively participate in digital, they will lose ground to their competitors. 

How developments in automation can assist the insurance business 

Our new normal places a greater emphasis on the value of business resiliency. Manual processes operate against this since they frequently require employees to visit real business sites in order to complete paperwork.  

In today’s environment, this poses a risk. Intelligent automation liberates individuals and organizations from on-site, paper-based manual processes, allowing them to focus on activities that are better suited to today’s digital, dispersed, and remote work environment. IA might also scale up or down depending on the situation. 

According to Gartner, “The pandemic accelerated a default-is-digital requirement demanding digitized business and IT processes. IT leaders must recognize that hyperautomation is pervasive and a mandate for achieving business outcomes.” 

The moment has come for insurance businesses to consider how technology can help them improve their operating operations. IA has the ability to assist insurance professionals in conducting business more quickly, efficiently, and securely. 

IA is rapidly transforming from a choice to a necessity. RPA, low-code, AI, and a slew of other IA technologies have proven to be essential components in architecting and meeting crucial business needs. 

Intelligent automation has various advantages. The first and most important step is to build capacity. When a high-frequency, high-complexity process like claims intake is automated, it can free up to 90% of the resources generally used in the process.  

This means that the work may be done in a more sustainable manner, and that these resources can be redeployed to provide additional high-value services to clients.  

An enhancement in employee experience is a linked advantage. Employees might be relieved from tedious and attention-demanding tasks such as manual data entry by automation.  

Furthermore, automation eliminates the necessity for the insurance industry’s frequent error-prone validation jobs. 

These advantages only scrape the surface of IA’s potential. Processing speeds increase as insurance operations are automated, resulting in a better end-customer experience and allowing insurance companies to be more responsive to claimants’ needs.  

Data mining and generating relevant results from insurance procedures are made considerably easier by digitalization at the intake source and the inherent homogeneity that comes with automation.  

Today’s automation solutions work well with the most popular data analytics platforms. Finally, automation improves rigor and tracking, making it easier to audit and grow the process smoothly. 

For some years, the term “automation” has been bandied in and around the insurance industry as companies strove to establish internal centers of excellence.  

The advent of intelligent automation has come, thanks to new technologies that can blend artificial intelligence with automation. 

While the advantages of automation are becoming more widely recognized, the majority of the low-hanging fruit has already been picked. 

IA is exhibiting immense potential in all areas of the insurance industry, including life, property and casualty, auto, business, marine, home, agriculture, travel, reinsurance, and more. 

IA’s footprint in the major segments of the Insurance industry 

Insurance carriers have the potential value to better their companies with new and emerging intelligent automation technologies as they strive to become digital insurers.  

Finding that perfect peanut butter-and-jelly combo of operational efficiency and consumer engagement in all major segments of the insurance industry such as Life, Property & Casualty (P&C), Auto, Business, Marine, and more is undoubtedly a balancing act. 

Life: It’s in an insurance company’s best interest to strive to automate the life insurance claims procedure, given the variety of paperwork involved and the sometimes-lengthy timeframe. They can reduce spending while cutting cycle times and increase customer satisfaction by doing so.  

An effective intelligent automation technology will be able to handle a wide range of documents, extracting all relevant data and leaving humans to focus on the more important task of dealing with individual claims. The IA platform is based on a model with over 500 million data points, which allows it to comprehend human language, including the context of each document. 

The model can then be customized to automate the processing of life insurance claim papers for businesses. It only takes a few dozen real papers to teach the model what information to look for. It will then be able to locate and extract that data even if the document format changes, which is a significant advantage over RPA and templated techniques. 

When life insurance businesses use the IA platform, they often realize a more than 80 percent decrease in process cycle times, a 4x increase in process capacity, and a more than 70 percent reduction in human resources, all while enhancing process correctness. 

P&C: P&C insurers may use AI-powered RPA to automate the First Notice of Loss (FNOL) process and improve the claims experience for their clients. 

Intelligent software robots (also known as “bots”) can readily extract useful data from unstructured documents received via email, fax, USPS, or any other method and enter it into the proper systems. These bots can also use rules to triage claims, directing them to different workflows based on their features. 

To minimize overall claim processing time, all of these processes could make use of ML or smart analytics. Automation can handle high-volume, repetitive activities 24 hours a day, seven days a week, freeing up claims experts to focus on more complicated analysis and higher-value work. 

By automating the claims FNOL process, insurers may cut costs, eliminate errors, prevent fraud, and improve customer interactions. To strengthen the entire insurance value chain, these intelligent automation technologies can be applied to other sectors, including underwriting and policyholder services. 

Auto: While organizations are interested in automating all types of insurance processes, the auto insurance claims process may be the most advanced – thanks in part to the electronics integrated into today’s cars.  

Insurance firms can now sell policies that take into account a client’s driving habits using telematics data, such as how many miles they drive, how fast they drive, and even if they frequently brake hard. 

An intelligent document processing platform would be able to take unstructured content like adjuster reports and even images of the damage, extract the necessary data, and feed it to a claims processing system downstream.  

Intelligent processing, when combined with telematic data, allows some insurers to automate the claims process from start to finish, at least for uncomplicated claims. 

Business: IA is enabling customized customer relationships and unlocking revolutionary business models. It helps in enhancing workforce capabilities, enabling their customer reps to handle their client specific queries and needs with better quality, preparing the customer self-service approach (24/7, assisted by virtual agents for common requests). 

IA also optimizes their processes by reallocating employees to core added-value tasks. Businesses that are ahead of the curve are already redefining their new structure based on IA. 

Marine: Robotics is playing a bigger part in the insurance claim industry in general, and it has a lot of space to expand in the marine insurance business. 

When a ship is damaged due to a storm, collision, or other occurrence, the ship operator will most likely make an insurance claim. Insurers will almost certainly need to view the ship with a marine insurance inspector or surveyor to verify these claims.  

An underwater ROV could be used for this inspection. The surveyor, on the other hand, is not normally a robotic flying expert and may not have as easy access to the ship as someone who is currently on site. That’s why some in the marine industry are turning to RPA and IA. 

Documents for claims processing, underwriting, new client applications, and other purposes have long been awash in insurance companies. Insurers are seeking ways to streamline and automate insurance processes that include dozens or hundreds of papers now that digital transformation efforts are in full force. 

The issue is that many of the documents contain unstructured text, making automation systems that rely on keywords, rule-based methods, and templates difficult to work with.  

Intelligent automation, a type of artificial intelligence meant to “read” unstructured documents in the same way that humans do, is a potential technology solution that delivers instant benefit. 

Closing thoughts: 

RPA and other hyperautomation solutions are at the heart of business’s future. The majority of businesses appear to be aware of this.  

IA is becoming more important in day-to-day operations as company models transition toward digital-first processes and services. This has an impact on the organization’s attitude toward IA. It’s past time for businesses to expand intelligent automation and provide tangible results. 

Cigniti is powered by strong strategic partnerships with “Top 3” OEMs aiding in building be-spoke RPA solutions that help reduce initial investment on RPA tools. 

Cigniti offers 3 main streams of RPA services: 

RPA Assessment: A comprehensive technical and functional assessment aligned with the client’s business & technical objective to establish RPA. Engineering approach to identifying and prioritizing business processes through score cards. 

RPA – Implement and Maintain: An End -to-end RPA solution, beginning with evaluation & recommendation of automatable business processes, RPA tool finalization & pilot implementation, workflow documentation, BOTS designing, BOT execution – unit & integration and BOT maintenance.  

RPA Test & Validate: Cigniti also provisions an independent testing/validation service for organizations that build and develop BOTS. 

Need help? Talk to our Automation and Insurance domain experts to find out more about implementing intelligent automation to improve insurance services.