Consider a typical claims processing scenario of a general insurance company receiving thousands of new requests in a given day. It employs an army of executives to handle every claim form manually and cross-checks the information against the carrier’s claims processing database before sanctioning payment. Or the established practices in the underwriting department, where risk professionals have to connect with dozens of landscapes to validate the credentials and confirm the insurability of a single prospective client! Sounds regressive, redundant, and downright wasteful?
Nevertheless, such workflows that add up to labor-intensive and error-prone outcomes are merely the tip of the iceberg in the insurance industry, chequered with high toil patches that had conventionally been hard to disrupt. Experts feel that the association of insurance with the fundamental aspects of individual and institutional existence, essentially their financial security, has made it shy of abrupt shifts. But the cost of delaying the revolution has been profound, undercutting profitability. For instance, McKinsey estimates that at present, even for large commercial lines, at least 40% of an underwriter’s bandwidth is spent on repetitive administrative tasks.
Coupled with disproportionately manual process drivers, the fact that the industry owes its stability to the highly volatile global socioeconomic and regulatory winds can expose the business to a broad spectrum of overwhelming challenges. It includes an imperative to optimize the cost of underwriting sustainably to ease out bottom-line pressures, steward change management and intuitively counter cybersecurity risks, ensure compliance with evolving regulations, drive scalability to attain nonlinear growth, and much more.
However, Gartner observes that the post-pandemic economy has triggered a default-is-digital requirement, demanding a resolute digitalization of business processes. It implores decision-makers to realize that hyper automating business processes are vital to enabling business outcomes. Also, in the 4th edition of its State of the Connected Customer, Salesforce reports that 88% of the customers expect their brands to accelerate digital transformation due to COVID-19, indicating that insurers can no longer afford to return to their regular operational flavors.
Why is RPA Important?
The induction of Robotic Process Automation (RPA) promises to unlock a world of opportunities for insurers, accelerating tedious, time-consuming processes and streamline their operations. In fact, successful implementation of intelligent automation projects for insurance has been incredibly beneficial, improving delivery speed by 80%, with over 90% accuracy, and maintaining constant regulatory adherence. The claims have oblique corroboration by several IBM case studies that have demonstrated a solid 200% inflation in ROI within the first year of RPA deployment across the financial services spectrum. But how exactly is RPA implementation poised to contextualize and unlock value for a new-age insurer intending to navigate in a closely contested market? Let’s see how…
What are the benefits of RPA?
Streamlined data management: Insurers handle massive volumes of data daily to price and underwrite policies, including high-definition videos, audio files, and images. However, 90% of the unstructured data is still being processed manually, leaving significant room for exceptions to creep into the outcomes. Inadvertent processing errors can compromise the insurer’s ability to rationalize cost and deliver the expected level of customer service. Claims backed by inaccurate information can trigger a series of avoidable expenses, including overpayment, litigation fees, and excess operational overheads. They are further compounded by the immense reputational risks that an insurer exposes itself to by operating on suboptimal data. Interestingly a series of recent roundtables involving the industry’s data leaders revealed that only 24% are confident of the data in their possession to quantify and price risk.
In respite, RPA can bring exceptional precision, speed, and transparency in insurance data processing, attaining which can otherwise be an uphill battle for the insurers. For instance, while processing the First Notice of Loss request, an RPA bot can extract and feed the required information into the claims management system without manual supervision. If all the fields are complete, the claim can be cleared for payment. Else, it can be flagged for scrutiny by a human operator in the loop. A machine learning algorithm shadows the claims agent in the process, learning the exception management techniques for application in the future. The approach accelerates the process and cuts down workforce expenses to the bare minimum, adding to the bottom line.
Integration of various systems and software: Eliminating technical debt can be complex in insurance. Legacy IT landscapes are often costly and frustrating to maintain. But they host valuable business data, making insurers hesitant to embrace change. In the recent past, a survey by ITIC revealed that legacy system outages cost large companies to the tune of $100k per hour! Yet banks and insurers allocate up to 75% of their IT expenses to preserve their legacy resources.
RPA integrates legacy insurance systems with minimal coding, improving their operational efficiency and capability to deliver exceptional customer experience. RPA platforms can continuously mimic manual maintenance operations and connect various systems via Application Programming Interfaces (APIs) into coherent landscapes, providing end-to-end automation. Due to its ease of use and inherent benefits, Gartner predicts that 70% of the new application for driving RPA will be written using the low-code / no-code philosophy by as early as 2025.
Enhanced compliance: Globally, the cost of compliance for the insurers has been going up exponentially, bringing their business practices and data privacy postures under intense regulatory focus. Since 2008, compliance-related operating costs have increased 60% for financial institutions, with regulatory risk averaging $10k per employee. Further, the Global True Cost of Compliance 2020 report published by LexisNexis Risk Solutions in June 2021 estimated the aggregate cost of financial crime compliance for financial businesses worldwide to be $213.9 billion in 2020, rising from $180.9 billion in 2019.
The uncertainties emanate while the Risk and Compliance teams struggling to keep up with the blazing pace of regulatory shift are compelled to take decisions on fragment and incomplete view of their business environments, leading to compliance failures. Here, RPA deployments can intuitively keep track by logging and codifying all transactions at the velocity of business. With the audit trail available on-demand, it simplifies for the carriers to comply with various tax laws, data privacy rules, PCI standards, etc., and attain an unprecedented level of transparency.
RPA Adoption by Process
While the benefits for hyper automating insurance processes through RPA are apparent, its creative application can gainfully alleviate several industry pain points that had been undermining customer experience and business margins for a long time. A few such scenarios can be:
Claims Processing: Claims Processing is a labor-intensive and highly iterative yet vital linkage in the value chain for both the general and life insurance businesses. It involves meticulously collecting and assimilating vast amounts of information from diverse sources to ascertain the integrity of a claim, creating inconvenience for both the operations and customer-facing staff. However, for carriers thinking automation first, it is easy to simplify claims workloads. Cases can be processed at least 75% faster using RPA, with bots operating alongside human elements to intuitively pull data from various landscapes and collating them into detailed claims insights for decisioning. RPA deployments can readily convert paper-based, legacy workflows of insurance companies into agile and hyper automated conduits, primed to boost CSAT and Net Promoter Scores.
New Business & Underwriting: Underwriting involves collecting information from various sources and collating them to assess the liability associated with a given cover. It is a painstaking process that can take four to six weeks to complete on an average in the life insurance vertical. Consequently, Accenture comments that over 50% of an insurance underwriter’s day is spent on repetitive tasks instead of strategic initiatives. RPA can automate and orchestrate these workloads by fetching information from internal and external sources and weaving them into decision-ready insights. Also, with the advent of self-service automation and citizen-led development culture, underwriters can now automate the back-office processes themselves without raising an IT ticket, accelerating time-to-insights for deliverables to drive business decisions.
Policy Cancellation: This is another area where quick turnaround time and conclusive outcomes define customer satisfaction and delight. While conventionally, it has been a time-consuming process, with RPA in the loop, insurance policies can be canceled with just one-third of the time, saving valuable customer service bandwidth. A carrier receives the cancellation request from the policyholder either as an email attachment or as the email body content. The RPA bot extracts information like policy number, customer name, etc., using OCR and verifies the sender’s identity using an AI engine. Once confirming that the sender is authorized to cancel the policy, the RPA-engine triggers an automated workflow for raising a cancellation ticket, terminates the policy and closes the case with a standard response to the policyholder. However, if the validation cycle fails, it will put up the case to a human operator to process it manually.
Business & Process Analytics: To sustain growth in highly competitive markets, insurers must assess business performance in real-time and convert data into actionable insights that can pinpoint areas for improvement. With RPA taking care of various insurance workflows, it is easy to quantify and appraise the throughput. Information on variables like transactions processed and exceptions encountered can be transferred into a business intelligence environment at runtime, delivering end-to-end visibility for the decision-makers.
How can Percipere bring in the value?
Today, an insurer intending to deploy RPA as part of its enterprise transformation roadmap is spoiled for choice. However, unlocking its true business worth hinges on having best-of-the-breed implementation expertise at the helm. That’s why we at Percipere have partnered with UiPath, a global leader in RPA platforms, to resolve complexities around two grey areas across the insurance value chain: Customer Onboarding and Claims processing.
We are a full-cycle RPA innovator, trusted industry-wide for infusing efficiency, speed, and precision into legacy insurance system landscapes with minimum intrusion. As an end-to-end RPA innovator, Percipere’s interventions range from Advisory, Consulting, Implementation to Incident Response, backed by well-laid plans and an efficient change management culture to help you make the most of your RPA investments.
Author: Akshay Farde, Lead Manager (RPA)
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