The insurance industry is using cognitive computing, a form of AI, to transform claims processing. This blog explores how AI is going beyond automation to improve efficiency, prevent fraud, and enhance customer experience. You'll learn about the current challenges in claims processing and how AI tackles them with intelligent automation and data analysis.
The worldwide industry is embracing cognitive computing to embed native intelligence into digital solutions and the insurance sector is right at the forefront of this refreshing trend. With the help of machine learning, deep learning, image recognition, reasoning, and many other cognitive automation technologies, cognitive computing is making a huge difference to claims management for insurance carriers. It is enabling smarter and faster decisions and is helping to predict and prevent problems in the business process and the delicate customer touchpoints along the way. Faster execution of complex and ambiguous tasks with high accuracy is the watchword here. With that, faster time-to-market, higher agent effectiveness, lower customer acquisition costs, improved sales, and enhanced delivery on the interaction and customer experience are the exciting new realities for the insurance industry.
In order for this to happen, the industry needs to go beyond just automation of manual processes to address creeping loss ratios crippling the carriers and making big dents in their profit margins. But, how can the carriers go beyond the mind-set of thinking of automation as the panacea for all the ills of the business? What can be done beyond offering incremental advantages of cutting costs, reducing fraud, and improving customer experience? If automation alone lacks the capability to spur further growth of the sector, what options do we have to propel it to newer dimensions of growth? The answer lies in employing intelligent inputs with cognitive computing in addition to reducing manual intervention.
The State of the Current Claims Process
Any lasting solution needs to start with clear understanding of the pitfalls of the current process. It needs to go deeper into the pain points and their genesis. This will ensure that the pain areas are addressed for good while uncovering exciting new opportunities.
Adverse Financial Performance: Higher than required claim settlement means lower revenue and profits for the carrier.
Undesirable Customer Churn:As claims processes sometimes end up protracted, delayed, or result in less than the claimed amount, they can be a source of dissatisfaction for the customers. This can churn the customer base.
Inability to Handle Fraudulent Claims:Identifying a fraudulent claim and proving it are two different things. Due to lack of a clear and structured process, carriers are sometimes forced to settle fraudulent claims for lack of defensible proof. They directly impact financial performance.
Increased Loss Ratio:When loss ratios increase, premiums increase for customers. So, it is in the interest of carriers to be competitive and keep the ratios low.
Impact to Multiple Parties:There are many parties involved in a typical claims process. A poorly handled process can hence impact not only the customer but also agents, underwriters, actuaries, adjusters, and Third Party Administrators (TPA).
High Manual Intervention:Claims settlement process tends to have high regulatory oversight. In addition, the financial nature of the process entails a lot of manual coordination, paperwork, and communication. This results in high administrative costs which translate to a higher premium for the customer.
Intelligent Claims and Effective Settlements – The Cognitive Way
The cognitive computing approach leads the insurance business out of high overheads and low profit margins by judiciously combining human logic with machine learning to great effect. Intelligent data analysis of past history and efficient outcome prediction are at the core of this approach. Cognitive computing-based systems have the knowledge to decipher hidden patterns in the data and produce the desired output through its advanced machine learning algorithms.
If you imagine the following scenario and the way it unfolds during the registration, processing, and completion stages of an insurance claim, the advantages of financial efficiency and administrative precision become amply clear.
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Register FNOL (First Notification of Loss) by uploading an image/video |
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CSR supplements it with additional information with the help of an AI-based virtual assistant with integrated NLP |
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Cognitive system extracts patterns from the data using image recognition and machine learning: validates/authenticates the claim and claim value estimation done. |
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System suggests repair shops using geo-based algorithms. |
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After a Claims Adjustor is appointed, workflow is initiated and the customer is kept abreast with timely alerts. |
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Critical assessment of damage is done using image recognition, cognitive automation, machine learning, and deep learning. It is determined whether claim should be approved or rejected. |
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By using a rich set of business rules and workflow, the claim is settled as appropriate via STP or cheque. |
Cognitive computing in insurance provides an effective solution that is win-win for both insurance carrier and customer. It guides the complete process with high operational efficiency, AI-based outcome prediction, and even remediation while the customer receives a definitive closure in far shorter time than the time taken by the current ‘automated’ processes. There is huge positive impact on business financial performance as well as on customer experience.
Coforge uses a systematic approach by mapping out the current business processes, identifying the critical pain points, bringing in the required deep expertise for the design and implementation phases and finally delivering the final solution through customer collaboration. Seamless support is ensured through go-live and post-implementation support stages of the project. Based on our proven record of working with insurance clients for many years, Coforge can offer help in designing and implementing critical technologies such as AI-based digital business assistants, deep learning, machine learning, multi-currency/multi-lingual/multi-channel experience, image recognition, RPA, OCR, NLP, and workflow automation. We can deploy APIs for integration with multiple stakeholders in producing a seamless experience.
If you like to break out of the pack by deploying cognitive computing technologies in the traditional insurance underwriting business, you will find just what you are looking for, right here.
Conclusion
Cognitive computing is revolutionizing claims processing by offering intelligent solutions beyond just automation. It helps insurance companies reduce costs, improve accuracy, and enhance customer satisfaction. This win-win situation paves the way for a more efficient and customer-centric insurance industry.
Call to Action:
Ready to break free from outdated claims processes? Contact Coforge today to learn how our AI solutions can transform your insurance business.
