For insurers, claim assessments is an operational area of the utmost importance, impacting both Loss Adjustment Expenses (LAE) on one hand, and customer satisfaction and retention on the other. In fact, according to the EY Global Consumer Insurance Survey, 87% of policy holders say that their claim processing experience impacted their decision to renew an existing policy, with settlement speed and process transparency being the next most important factors. Despite efforts of introducing automation to streamline processes, most insurance carriers still rely mainly on manual processes for claim assessment. As a result, insurers are struggling with multiple challenges.
Current challenges in claims assessment
Operational efficiency. Historically, claims assessment has been a lengthy, manual process, requiring weeks and even months to complete, frustrating both insurers and customers. As part of this labor-intense process, insurance agents have to manually gather data, investigate it, and crosscheck it against varying sources and parties. In addition, the manual nature of the assessment process is highly prone to human error. Mismatched financial data or customer details, decisions made on partial or irrelevant data, and built-in cognitive biases often lead to sub-optimal results that adversely impact the business.
Customer expectations. The insurance claims journey has historically been opaque and confusing to customers. In recent years, however, and especially on the heels of the expedited migration to digital services during COVID-19, customer expectations have changed. Consumers increasingly expect the speed, convenience and transparency that they have learned to expect from other digital experiences. In fact, more than 50% of consumers think traditional insurance companies are lagging other industries in both responsiveness, technology, tools and personalized products. This is especially true in light of InsurTechs, which are dramatically disrupting the industry, introducing mobile-first, pure digital experiences and super-speedy offers.
Partial data. Across industries, the consolidation of data from multiple sources and the increasing reliance on data-driven processes and decisions have led to improved financial outcomes. Within insurance companies, manual processes and point solutions often rely on inadequate, siloed information and data. Insurers still struggle with leveraging the data at their disposal, as well as with introducing new data sources that have become operable with the rise of IoT. Data is fragmented and cannot be harnessed to either simplify and streamline the assessment process, or provide an enhanced understanding of specific cases. These sub-optimal settlements based on partial data have a direct impact on insurers’ bottom lines.
AI capabilities for claims processing and settlement
To overcome these challenges, many insurance companies are investing in game-changing Artificial Intelligence technologies. Insurance executives already recognize investment in digitization, automation and the use of data and technology as their top growth priority, according to a recent survey. In order to reap the full range of benefits, insurance companies need to devise an enterprise-level strategy to implement AI throughout the entire claims assessment workflow, and provide a digital solution that can provided end-to-end support to their employees. Transforming the insurance assessment process requires multiple AI capabilities working in tandem. These are the main AI modules required for AI claims assessment:
Data capture. Data processing lies at the very heart of AI claims assessment. AI-based data capture (also referred to as IDP — Intelligent Document Processing) is a next-generation solution for extracting data from complex, unstructured documents. Compared to previous OCR offerings, IDP can handle document complexity and variation with greater speed and improved accuracy and efficiency. AI-based data capture is designed to overcome data silos and fragmented data, creating data synergies across multiple sources to enhance the analysis and investigation of claims.
Visual assessment. AI-based image recognition is used to improve visual appraisal processes, enabling immediate and accurate inspections. AI models instantly analyze images of properties, vehicles or other insured assets to evaluate damages costs or devaluation based on analyzing visual cues. Additionally, by identifying data patterns in claim reports, AI-powered visual assessment can aid insurers in automatically identifying fraudulent claims, as well as in minimizing human errors and resulting inaccuracies.
Risk management. AI-based risk assessment verifies the data that both customers and agents enter into company databases, and is essential for weighing the veracity and authenticity of insurance claims. An effective risk management assessment process helps to accurately identify and root out dubious claims.
Payments. Finally, by bringing all these AI capabilities together, end-to-end claims assessment solutions provide the optimal payment scheme for each claim, according to its unique context and attributes. By bringing together and autonomously processing all relevant visual and textual data, utilizing risk management that is powered by machine learning, AI enables insurers to accurately investigate and settle claims, prevent erroneous settlements, and improve overall profitability.
End-to-end AI Claims
Insurance companies have a lot to gain from investing in AI solutions that can elevate service quality with faster, more accurate claim handling decisions.
Forward thinking insurers who have already implemented AI claims assessment solutions as part of an end-to-end automated process enjoy these benefits:
- Increased adjuster efficiency with faster automated claims and payment processes, with full explainability and recommendations
- Reduced back office and LAE costs
- Deeper visibility into each claim, with better use of data from multiple sources
- Quicker and more streamlined customer experience, resulting in improved customer retention
When applied to claims processing, AI technology can drastically shorten settlement cycles, saving the insurer significant resources and offering a faster payout.
The BeyondMinds solution
The BeyondMinds end-to-end enterprise platform enables insurance companies to transform core business processes to human-machine automation, adapting to specific business needs. As a fully customizable end-to-end platform, it covers all underwriting processes with relevant AI capabilities, from data capture through visual assessment and risk management, to pricing optimization. All of BeyondMinds’ AI solutions, across use-cases and verticals, are built on top of a modular universal platform, enabling each customer to deploy its personally tailored AI solution in just weeks, no matter which business they’re in.
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