Why Is Data Accuracy Important In The Insurance Industry?

by | Published on Sep 8, 2021 | Data Entry Services

Data is an important aspect, particularly in a client-centric sector like the insurance industry. The amount of data consumed by the insurance sector in the United States alone is phenomenal. Reports show that about 5,965 separate insurance bodies are active countrywide and premiums totaled more than $1.3 trillion in 2019. Therefore, insurance data accuracy and integrity is growing more and more essential. In fact, insurance companies are looking out for smarter ways to analyze tons of data efficiently. The need for speedy data transmission has led companies to rely on data processing services to handle critical data entry and analytics needs.

Even though the majority of insurance claims are now processed electronically, there is still a significant amount of paperwork involved in claims processing. It is estimated that as many as 25 percent of claims arrive as physical documents. Many insurers have implemented document scanning processes, but unfortunately they do not take complete advantage of digital transformation processes. The insurance document scanning departments rely heavily on manual labor, thereby slowing down claims processing. Fortunately, there are intelligent document scanning and processing solutions that not only reduce labor and minimize error but also enable more efficient and economical claims processing.

Insurance claims data entry is challenging. Often, insurance claim documents need to be copied or shared and reviewed by multiple departments, depending on the type of claim. Handling physical documents makes it difficult for numerous employees to work simultaneously on the same claim simultaneously. As data from various documents within a claim is manually entered into the claim management software, these steps can lead to errors or omissions that may create chaos in the process, delay payments, or result in mishandling of the claim.

Significance Of Data Integrity In The Insurance Industry

Here discussed are a few reasons why data integrity is important in the insurance industry –

    • Privacy and Data Accountability – Protecting sensitive information of clients is crucial for insurance companies, particularly in this age of data protection. For instance, across Europe, this right is protected by the General Data Protection Regulation (GDPR). Failure to protect insurance data adequately may also lead to private suits and claims. In short, it is extremely important for insurance companies to make sure that their data is accurate, protected and organized. In fact, the threat of data theft and other malicious attacks revolves around lack of accuracy and clarity.


    • Fraud Detection – Fraud costs the insurance industry billions of dollars each year. Fraudulent practices in insurance arise in many different forms. Insurance carriers can help combat fraud by ensuring that their records are up to date or accurate – both in its organization and its references. Reports from the Insurance Information Institute suggest that the US auto industry saved $128 million through detailed data checks like photo inspection process. Data such as photo ID and basic cleansing can help reduce costs for insurance carriers across the country.


    • Better Customer Care – Accuracy in data is vital to ensure better customer service. The more accurate insurance data is, the more specific policies and pricing will be. For instance, insurance premiums can be complicated, particularly for the end-user or policyholder. Therefore, insurance companies need to ensure that their numbers are accurate. On the other hand, duplication in data is another factor that causes problems for insurance experts and policy holders. Failure to compile data in a specific place and into one singular, accurate record could lead to mispricing. Outdated records can also lead to inaccurate policies, quotes, and extra expenditure for customers.


  • Efficiency and Processing – Inaccurate records and poor data collation can lead to more time and effort used for putting together policies. While filing for claims, policyholders require quick action. If insurance carrier data is poorly organized or unclear, this could impact a company’s reputation as well as the customer experience. In addition, it could impact the quality of the end product for the policyholder. As, the insurance industry revolves around data, inaccuracy in data may result in a policy that fails to protect a user in the way they expect. Therefore, it is important to make sure the data they work with is clean and easy to source.

Insurance companies use a variety of methods to collect data. These include manual underwriting and data collections from multiple sources. Manual underwriting involves considerable time to combine together background data from a variety of sources. Predictive analysis is not easy to set up. However, emerging technologies are helping the industry find new ways to build profiles.

For instance, insurance carriers may start collecting data through customer targeting. They can set up their targeting profiles to find policyholders that fit their needs and this option is entirely possible through tailored web advertising, social media, and more. Insurance carriers may have access to a variety of public records. Policyholders and potential customers need to understand that this data is necessary to build appropriate risk analysis that helps companies set rates and to offer adequate coverage. Due to increasing fraud, insurance bodies can no longer rely on customer input alone. Therefore, it is important to work with multiple sources and data collections. With a transparent system to collect data in place, the future looks bright for the industry.

Right from claims processing, fraud detection to underwriting, data accuracy is transforming every single facet of the booming insurance industry. Without accurate and clean data, insurance companies could lose billions of dollars, and policyholders could receive inadequate coverage for their needs. Data insurance trends shows that clean data collation (from multiple sources) could speed up claims processing. This will also help improve the overall customer experience, and provide valuable savings by reducing risks. Error-free data entry services can help consolidate data, reduce expenses, improve customer experience, and reduce fraud in the long run.

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