How Cognitive Document Processing Redefines Data Pipelines in Insurance

In the fast-changing insurance sector, data-related challenges are a major issue. A 2020 report from The CRO Forum points out that insurers face data quality challenges every day. 

Problems like incorrect addresses result in lost mail, and missing customer identification numbers make it difficult to interact with service centers. 

These issues highlight the need for innovative solutions, such as Cognitive Document Processing, to improve data accuracy and operational effectiveness.

This article will look at how it improves data handling and helps insurance companies run better.

What is Cognitive Document Processing

Cognitive Document Processing, in short CDP, revolutionizes how insurance companies work with data. It uses AI/ML to automate the extraction, classification, and analysis of data from various document types. 

Unlike regular Optical Character Recognition-OCR, which merely converts text images into machine readable text, CDP does so much more. 

While OCR is limited to recognizing characters and producing plain text, CDP analyzes context, applies complex rules, and extracts actionable insights from both structured and unstructured data.

For example, CDP can process structured data, like claim forms and invoices as well as unstructured data, like customer emails and chat messages, CDP does it all.

This innovative approach minimizes costs, maximizes accuracy, and speeds up decision-making. This could allow insurers to be even more competitive and fully meet customer needs that are changing.

How CDP is Redefining Data Pipelines in Insurance

1. Automation of Data Extraction and Validation

Generally, traditional data pipelines in the insurance industry are characterized by lots of manual entry and validation. These methods are extremely time-consuming and quite error-prone. CDP now changes this by automating these essential tasks, making data extraction faster and more accurate.

For example, automation in document processing—such as in Zurich Insurance's AI-driven initiative—reduced application processing times from 22 days to less than a day.

In addition, automation in document processing has been shown to cut processing times for repetitive tasks by 30-50%, allowing insurers to scale operations and respond more efficiently to high volumes of customer inquiries.

While automation addresses the time-consuming tasks, insurers also need scalable and secure systems to handle increasing data volumes and regulatory demands.

2. Enable Scalable and Secure Data Pipelines

CDP goes well with cloud tools since it can easily scale up the insurance companies' data pipelines as their data demands grow. 

Besides, the strong security measures built into these systems help companies meet strict industry regulations, keeping customer information safe and ensuring that data is managed correctly.

3. Quality and Consistency Data Improvement

A major challenge in the insurance industry is to ensure data quality and consistency across different documents. CDP uses machine learning to improve accuracy and consistency in data. 

This is quite important for precise underwriting and accurate recording of claims is vital in maintaining accuracy. In CDP, insurers can be assured of the data they possess for better decision-making and also an assurance of a holistic customer experience.

Case Study: How a CDP helped a insurance provider become successful.

WNS worked with a large U.S. insurance company to improve their claims processing using intelligent automation. The insurer had trouble extracting, categorizing, and indexing data from many different sources and formats. This caused delays, mistakes, and made the claims process slower.

To solve these problems, WNS added SKENSE, a smart data capture and processing tool that uses artificial intelligence (AI) and machine learning (ML). SKENSE helped automate the gathering of unstructured data, used natural language processing to mix information from different sources, and identified, extracted, and sorted the data needed for automatic claims processing.

The use of SKENSE brought several improvements:

Automation: 88% of the claims indexing volume was automated, reducing manual intervention.

Efficiency: The average time to handle claims went down by 68%, speeding up the claims process.

Accuracy: Better data extraction reduced mistakes, leading to more reliable claims settlements.

Customer Satisfaction: Quicker and more accurate claims processing improved the overall experience for customers.

Insurance CDP Use Cases

1. Claim Processing/Claim Settlement

CDP, driven by AI, extracts the relevant information from the claims, checks policy rules, and automatically flags errors. This increases both the speed at which the claims are processed and reduces any chances of an error occurring.

2. Fraud Detection

Examining patterns in historical claims data, machine learning can identify unusual activity that might indicate fraud. This proactive approach helps insurance companies lower risks and safeguard their profits. 

3. Onboarding of Customer

CDP simplifies document verification, reducing the time required to onboard new customers. Automating these checks allows insurance companies to improve the customer experience, which can lead to higher retention and satisfaction rates. 

4. Underwriting Automation 

CDP makes the underwriting process easier. It extracts and analyze data from sources like medical records and financial statements. This automation helps speed up policy issuance and improves risk assessment.

5. Policy Administration

CDP automates tasks such as updating, renewing, and cancelling policies. It efficiently handles related documents, which makes operations smoother and improves the customer experience.

6. Regulatory Compliance

CDP helps insurers follow industry regulations by automating the analysis of compliance documents. This reduces the chance of facing penalties for non-compliance.

7. Customer Service Enhancement

CDP manages customer inquiries and feedback from various channels. This allows insurers to respond quickly and accurately, boosting customer satisfaction.

Conclusion: Are You Ready for Change? 

With Cognitive Document Processing, insurance companies can lead the way in efficiency, cost savings, and customer satisfaction. The time is now to upgrade your systems with CDP and stay at the helm of your competitors. It's much more than an upgrade in technology, and rather, it is an imperative ingredient to success in the insurance business.

Author Bio:

Raj Kumar is a dynamic digital marketing lead passionate about helping financial companies embrace innovation and stay ahead in today’s fast-paced digital world.

As part of the pre-sales team at Kumaran Systems, a company specializing in app modernization and cognitive document processing services, they help insurance companies automate the processing of complex structured and unstructured data using cutting-edge cloud-native tools and industry-leading capabilities. With his deep insights and strategic acumen, Raj is committed to driving digital success and fostering a competitive advantage for clients in the financial sector.