Revolutionizing Claims Journey through Generative AI
3AI July 5, 2024
Featured Article
Author: Vidhya Veeraraghavan, Standard Chartered
In the Claims-2030 series of articles, Mckinsey emphasizes that by 2030, every touchpoint in the claims journey, starting even before an incident occurs, will be supported by a mix of technology and human touch that seamlessly interacts to expedite the process and deliver a better experience across the board. It is not hard to believe this. We are witnessing a lot of changes that technology has brought into our everyday lives.
In an era defined by rapid technological advancement, the insurance industry stands at the height of transformation. The traditional claims journey, often loaded with inefficiencies, complexities, and manual efforts, is a ripe ground for revolution. As we navigate through the digital landscape, the integration of Generative AI promises to reshape every facet of the claims process, from submission to settlement. Through this article I try to illuminate the path toward a future where policyholders, insurers, and stakeholders alike benefit from the unparalleled potential of GenAI. Welcome to the dawn of a new epoch in Claims Journey.
Typically, the Claims Process goes through a series of stages. Let’s now take a look as to how GenAI can help in each of these stages.
Stage 1 – Submission
Empowering Policyholders with Seamless Claims Submission through GenAI-Powered Assistance
– GenAI-powered chatbots or virtual assistants can be the first point of contact in any claims process and can assist policyholders in submitting claims through various channels, providing guidance on required documentation with completeness as criteria. For example, a virtual assistant can guide a policyholder through the process of submitting a car insurance claim after an accident, ensuring all necessary details are included.
– As a good addition to the GenAI suite, Natural Language Processing (NLP) algorithms can analyze submitted claim forms and documents to extract relevant information, reducing manual data entry and minimizing errors. For instance, NLP can extract key information like policy numbers and incident descriptions from an uploaded claim document using Named entity recognition (NER) technique.
Stage 2 – Initial Review
Streamlining Claims Validation and Fraud Detection with GenAI Algorithms
– GenAI algorithms can perform automated validation checks on submitted claims to flag any missing or inconsistent information for further review. To give an instance, object detection algorithms, such as YOLO or Faster R-CNN, can be used to identify objects within an image and draw bounding boxes around them. These can help detect missing signatures or incomplete sections in a health insurance claim forms and even enrich your dataset with missing information using generative AI algorithms.
– Complementing the GenAI results, Machine learning models can analyze historical data to identify patterns associated with fraudulent claims, helping prioritize investigations and mitigate financial losses. For example, a model built using anomaly detection algorithms combined with apriori algorithm can detect patterns of suspicious activity in health insurance claims, such as frequent claims for the same medical procedure by rules of association.
Stage 3 – Document & Imageclassification
Efficient Document Management and Enhanced Fraud Detection through GenAI Solutions
– GenAI solutions can automatically tag documents and images, summarize key information, and assess customer sentiments. To illustrate, an AI system built to categorize and summarize homeowner insurance claims documents can make them easily searchable for claims adjusters.
– This automated classification and summarization process not only streamlines operations but also enhances fraud detection capabilities by enriching the data available for analysis. By identifying relevant attributes and contextual information, GenAI solutions empower insurers to make informed decisions and detect fraudulent activities more effectively and accurately.
Stage 4 – Investigation Strategy
Augmenting Claims Investigation with GenAI Decision Support Systems
– GenAI-powered decision support systems can augment the investigative process by providing adjusters with timely access to relevant information and insights. For instance, a GenAI solution can analyze historical claims data, customer profiles and external factors to provide recommendations on the legitimacy of a homeowner or disability insurance claims and to provide assistance to adjusters in making informed decisions about causal claims & validity.
Stage 5 – Evaluation Blueprint
Enhancing Claims Assessment Accuracy and Efficiency with GenAI Predictive Analytics
– GenAI-powered decision support systems can assist insurance adjusters in evaluating complex claims by providing data-driven insights and recommendations. To give an example, predictive analytics models can estimate the expected cost of a car insurance claim based on historical data and industry benchmarks, aiding in accurate valuation and reserve setting. This in turn generate the evaluation report automatically based on the data collected.
– By leveraging machine learning algorithms, insurers can predict claim outcomes with greater accuracy, enabling proactive risk management and financial planning.
Stage 6 – Negotiation
Empowering Fair and Informed Settlements through GenAI Insights
– Decision support systems powered by GenAI can assist claims handlers in negotiation by providing real-time insights into policy terms, industry standards, and historical settlement trends. For example, an AI system can analyze similar cases from the past connecting with the market data to provide recommendations on a fair settlement amount for a property or car insurance claim.
– By analyzing comparable cases and external data, AI systems enable claims handlers to make informed decisions and negotiate fair settlements that align with the insurer’s guidelines and objectives.
Stage 7 – Payment Program
Efficient and Secure Claims Disbursement Enabled by GenAI Technology
– GenAI solutions streamline the payment process by automating the generation and distribution of payment instructions, reducing manual errors and processing delays. For example, a GenAI system can be exposed as a microservice via APIs, to initiate electronic transfers for a life insurance claim payout, ensuring timely and accurate payments to beneficiaries.
– Additionally, AI-powered fraud detection algorithms continuously monitor payment transactions for any suspicious activity, helping safeguard against fraudulent claims and unauthorized payments. By leveraging advanced technology, insurers can enhance the efficiency and security of the payment process while maintaining compliance with regulatory requirements.
Conclusion and Call to Action for CXOs:
As we conclude our exploration of the transformative potential of Generative AI (GenAI) in revolutionizing the claims journey, it becomes abundantly clear that the future of insurance lies within our grasp. CXOs hold the pivotal role in steering their organizations toward this future, where innovation meets efficiency to redefine industry standards. By embracing Generative AI, CXOs have the opportunity to unlock unprecedented value across the claims journey / lifecycle, from enhanced customer experiences to optimized operational processes.
By embracing Generative AI as the catalyst for change, championing innovation, fostering collaboration, and investing in cutting-edge technologies, CXOs can propel their organizations into the forefront of the insurance industry where claims management is seamless, efficient, and customer-centric.
Title picture: freepik.com
