Robotic Process Automation: a Powerful Catalyst for Insurance Digitization
The previous blog looked at what enterprise digitization entails and concluded it’s a broad landscape that challenges the culture and resources of all but a few enterprises. The scope of digital transformation covers establishing – or expanding the following capabilities:
Connectivity: Enabling transparent and integrated communications across customers, employees and key third parties.
Automation: Completing the “last mile” of automation lacking in many companies to maximize the coverage of high performance operations and captured data.
System Integration: Finishing the “last mile” of integrated systems also lacking in most companies to optimize end-to-end processes, operational efficiencies and transparency.
Enterprise Data: Reducing and replacing silos of structured data and black holes of unstructured data with a rationalized data warehouse.
Business and Customer Knowledge: Creating the opportunity to mine a data warehouse and, by integrating external Big Data, drive highly effective strategic and operational decision-making.
As daunting as digital scope is, digital disruption is bringing huge changes to every industry and will be a big threat to any company that decides to “wait and see”. All companies will quickly see:
Squeezed margins – consumers can easily compare products, services and prices.
Lego operational models – competitors can offset a rival’s IT investment with variable Amazon cloud services.
New skillsets – automation may reduce staff, but digital execution will require other people knowledgeable in decision modeling, machine learning and Big Data analytics.
Constant disruption – the music industry is testimony to what the digital tsunami can wreak; vinyl to CD’s, CD’s to MP3s and MP3s to Spotify.
Insurance Companies Face Unique Digital Challenges
The majority of insurance companies face not only these digital challenges, but others unique to their industry.
Perhaps the most difficult challenge is a myriad of legacy software systems dating back as far as twenty to thirty years. These systems are rooted in distributed architecture, encompassing different system components for almost every insurance function – agency, underwriting, policy admin, claims, etc. The notion of leveraging “best of breed” component solutions made good sense at the time. Today the idea of creating silos of systems, data, technology and language wouldn’t get far. Compounding this challenge is a long history of industry consolidation, resulting in multiples of legacy systems thrown together my successive acquisitions.
Another challenge for insurance digitization is the complexity of industry business processes and decision-making, particularly in the areas of insurance underwriting and claims administration. Both roles require extensive product knowledge, industry experience and analytical skills. While the insurance industry has embraced automation, particularly in the claims area, both jobs retain prominent responsibilities for complicated and often subjective decisions.
A third challenge is the high degree of regulatory oversight, equaled only by the financial services industry. Regulatory compliance is a source of never-ending enhancements to existing policies and claim procedures – plus related applications and documents. The certainty of these annual changes places high risk on any plan for disruptive system or operational change.
A thread of permanence runs through all these challenges: business complexity and regulatory oversight will never go away, if anything both will increase. Legacy systems appear immune to significant change: a BT Global Services survey found legacy systems were indeed hurting the ability of insurance companies to create new product lines; regardless, only 42% preferred new systems and 37% planned to upgrade existing legacy.
Why RPA is a Powerful Catalyst for Digitization
Robotic process automation (RPA) is an innovative technology well suited to meet the unique digital challenges of the insurance industry. Beginning as a desktop “software robot” that automated a business user’s repetitive tasks, the technology has evolved into a platform-based application capable of automating complex business rules and orchestrating hundreds of “robots” to address large volumes of work.
Because its primary integration point is the presentation layer, this robotic software avoids complicated systems integration and database scope. Its non-disruptive deployment profile requires no modifications to existing systems and databases and needs no security access configurations. Its light implementation footprint is ideal for the insurance industry legacy environment and deployment is ROI-friendly – taking weeks rather than months. Once deployed, the technology is a powerful catalyst for digital transformation for insurance companies in these specific ways:
Front Office Operations: insurance products address widely different markets – such as auto, property & casualty, life, health – supported by distinct business process often supported by isolated legacy systems. This means it is difficult for the company to be aware of – much less take advantage of – cross-selling opportunities. For the customer, it can mean answering the same questions for each product silo. In the call center, or in an agent’s office, it means re-entering the same information in several different fields.
Robotic software automates all of these data migration bottlenecks so the company has a complete view of the consumer and all parties – agents, customers, customer service agents, etc. can spend their time in productive ways.
Underwriting: this robot technology may have started with simple, repetitive, rules but leading vendors now have products capable of incorporating complex decision modeling into the software design. This enables the automation logic to tie associated business rules to the support of more robust decision-making for underwriting and claims administration. The goal in both instances is to automate simple & medium quotes and claim adjudication. For quotes and claims which are complex, automated exception handling in both processes will route those exceptions to the specific employees best equipped to handle them – a strong efficiency benefit.
Claims processing: a claim lifecycle typically covers processes for: adjudication workflows; specialized actions by claims administrators or agents and handling additional claim details required for resolution.
Approximately 25% of provider claims are submitted in paper rather than electronic form. Leading RPA products have computer vision capabilities to transform that paper information into structured data, significantly reducing processing time and also making it available to other applications. Robotic software can also automate and accelerate existing manual claim revision activities, designed to fix simple claim errors and prevent first-pass edit failures.
The successful claim adjudication rate is generally around 95% for most claims systems. But when you consider major U.S. health insurers process over 150 million claims annually, a 5% rejection rate no longer looks small. Further, failed claims generally require the provider to submit supplemental information to appeal the decision and support a reversal – information which is almost always unstructured natural language in hard copy forms. Robotic process automation is able to quickly and accurately turn natural language into structured data, enabling a claims administrator to dramatically increase review process service levels.
Regulatory oversight: Leading edge robotic process automation products are platform-based and configured to capture all activities in log files which are archived in a central repository. UiPath combines this capability with Elastic Search so data retrieval for regulatory reports is quick and easy. The automation software for the robots can also be quickly and easily modified to mirror system changes required by regulatory requirements.
Within the insurance industry, some companies view digitization as a roadmap to providing consumers with a digital environment for shopping, getting quotes, purchasing and receiving policies via a secure shopping cart. Other companies have more modest goals. They have no plans to tackle the limitations of their legacy systems and view digitization as limited to showing products online and supplying quotes. By applying RPA technology to insurance industry digital challenges, its likely more companies will become aggressive in their transformational goals.