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Overcoming Data Challenges in the Insurance Industry

March 27th, 2023

Data is at the heart of the insurance industry. Vast amount of information is collected and analyzed daily for different purposes including risk assessment, product development, and making informed business decisions. But managing this data can be a significant challenge, with issues ranging from data volume to quality concerns, siloed systems, and integration difficulties.

In this blog, we’ll explore these common data management challenges faced by insurance companies. We’ll go on to introduce you to Astera ReportMiner, the solution that can help overcome these obstacles.

Common Data Management Challenges in the Insurance Industry

Data trapped in Unstructured sources

Managing the sheer volume of data scattered across various unstructured sources is one of the top data management challenges in the insurance industry. An insurance company may receive claim documents in PDF format, making it difficult to extract relevant information.

Consider an insurance company that needs to extract data from a large number of PDF documents. These documents may include insurance policies, claim forms, medical records, and more. These PDFs may vary in format and layout.

Manual data entry can be time-consuming, resulting in delays in processing claims and increased costs. Moreover, there’s always a risk of human error, which can lead to incorrect insurance processing.

Siloed Data

Data silos refer to the separation of data into isolated and disconnected systems or repositories. In the insurance industry, data silos can occur when different departments or business units within an insurance company store and manage data independently without sharing it with other parts of the organization. This can be a serious challenge for the company.

For example, the underwriting department may have a database of policyholder information, including details such as name, address, and policy coverage. The claims department may have a separate database of claim information, including details such as the type of claim, the date it was filed, and the status of the claim. The marketing department may have a third database of customer data, including details such as demographics and purchasing history.

In this scenario, the data is siloed, as it is stored in separate systems and is not easily accessible or usable by other departments. This can lead to inefficiencies, as employees must spend time and effort manually gathering and organizing data from multiple sources.

Moreover, it may not be possible to analyze data from different sources in a comprehensive manner. This can hinder the ability to gain meaningful insights from data

Inaccurate data

Quality and accuracy of data are crucial in the insurance industry, given their significant impact on decision-making and risk assessment. Errors, duplications, and inconsistencies can compromise data quality and lead to incorrect or incomplete insights.

For example, consider an insurance company that receives claims data from multiple sources, including policyholders, claims adjusters, and third-party databases.

Improper validation and cleansing of data may result in errors or inconsistencies impacting the accuracy of the company’s risk assessment. This, in turn, could lead to incorrect decisions such as underpricing or denying coverage for certain risks.

How ReportMiner can help Insurance companies deal with these data challenges

Our no-code data extraction automation solution, Astera ReportMiner, can help insurance companies overcome these data management challenges.

Using the intuitive, drag-and-drop environment and AI-powered template-based capabilities, insurance companies extract, cleanse, and integrate data from various sources to create a unified data system.

Data Extraction

Astera ReportMiner can extract data from various sources, including insurance documents, claims reports, and third-party databases.

Insurance companies can use the code-free interface to extract the data required to make informed decisions without manual data entry or transcribing information.

Insurance companies can leverage ReportMiner’s optical character recognition (OCR) and natural language processing (NLP) capabilities to extract and classify data from these documents.

For instance, OCR can be used to convert scanned images of documents into machine-readable text, while NLP can be used to identify relevant information such as policy numbers, customer names, and claim amounts.

By streamlining the data extraction process with ReportMiner’s AI capture, the insurance company can save time, reduce errors, and improve data accuracy.

Data Consolidation

Astera ReportMiner helps insurance companies eliminate data silos and integrate data extracted from various sources into a consolidated repository.

Companies can ingest data from structured and unstructured sources, such as documents, spreadsheets, databases, and web pages, and create automated ETL pipelines to consolidate it into a single data warehouse.

For example, in the scenario mentioned earlier, ReportMiner can extract data from the underwriting department’s database, the claims department’s database, and the marketing department’s database and consolidate it into a single repository.

As a result, business users get a complete view of their data, enabling them to make more informed business decisions. It also saves employees time and effort by automating the data consolidation process and providing access to more comprehensive insights.

Data Quality

Astera ReportMiner has advanced data validation capabilities to identify and fix errors and inconsistencies in data to ensure data quality.

Working with large volumes of data can be time-consuming and error-prone when using manual data cleansing. Data validation rules can be particularly useful in such cases.

For example, an insurance claim file can have errors, including spelling mistakes, incorrect formatting, and duplicate or missing values. You can customize data validation checks in ReportMiner to identify these errors and missing values.

Accurate data allows insurance companies to make informed decisions about insuring clients, determining premiums, and providing coverage. This, in turn, can improve risk assessment and underwriting processes.

Astera ReportMiner is an ideal data extraction and integration solution for insurance companies as well as vendors looking to work more effectively with insurance companies. We have designed our code-free solution to streamline and simplify large-scale data management processes.

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