Data entry has always been an essential and integral part of businesses that leverage some form of computing and, these days, some extent of automation. While data entry is indispensable, and enterprises are currently incorporating the evolution of complex and robust programming best suited for businesses, the human element is still critical to a successful implementation.
Any project requiring data entry must be backed by quality assurance and free from issues like fraud, copyright, patent, plagiarism, and misrepresentation of facts, as the case may be. Those entrusted with such tasks must exhibit diligence and a high degree of professionalism.
While some speculate that Artificial Intelligence (AI) and, in the case of Data Entry, automation will effectively replace humans, rendering them jobless and redundant, other industry pundits beg to differ. Nonetheless, automation is being implemented on a massive scale and will only see further adoption. Worldwide, the dependence on AI has pegged its CAGR at 36% by 2023 and a value of USD 407 billion.
Robotic Process Automation (RPA) deploys programmed bots to act as digital workers and tackle repetitive tasks. By adopting these cost-effective technologies, insurance companies can automate the data entry processes in insurance, making them faster and more efficient.
Top Benefits of Robotic Process Automation in the Insurance Industry
Transforming Business Processes: By applying AI to traditional historical, new, and real-time data, insurers can get actionable insights into insurance customer experience, better assessment of risks, increase fraud detection rates and make faster and more accurate business decisions.
Deliver Top-Notch Customer Service: Digitalization can help insurers better understand their customers through data analytics, which can help them develop more personalized products, address customer queries and pain points and improve customer retention.
Easy Audit Trail: Insurance companies must understand the entire process to evaluate a claim properly. This procedure can be easily understood if there is an audit trail. It helps the insurance officer to get a complete overview of the policyholder, detect upcoming issues, and provide data on what task was performed by who, at what time, and at which location.
Data Accuracy and Quality Data: Automation helps in data accuracy, bringing in quality data that can support the exponential growth of the insurance business. Based on data, organizations make decisions; therefore, when data accuracy is high, one can get quality data, boosting efficiency and ROI.
Eliminates Excess Manual Work: Statistics show that automation reduces the amount of manual work by 80%. It no longer requires a person doing data entry to be in the same proximity as the information provider. Automation also reduces the dependency on the specific skills of the individual data entry operator. It enables teams to do more with the same resources.
Zero Scope for Human Error: Automated data entry software leverage AI & ML capabilities to extract data accurately and minimize post-processing. Such algorithms can handle your typical data constraints and eliminate errors. Votaries of automation emphasize the overall reduction in human error, including mistyping, duplication, and omitting data components.
Optimized Workflow: Along with minimizing the role of manual data entry, automation can optimize workflows by streamlining processes and reducing the work of human resources staff. The data automation software can extract data from PDFs, documents, images, emails, or websites and present the relevant information in a structured format.
Insurance Agency Automation that doesn’t work
Quality concerns: Surprisingly, although automation helps in reducing numerous human errors, it, unfortunately, compromises the overall output quality. Quality checks still need to be performed by humans, especially when specific auto-generated datasets require validation, as in the case of the insurance industry.
Affordability concerns: Certain tools used in automation can be too costly to consider feasible in the short term. Their high installation and maintenance costs at the initial stages make it challenging to assess the ROI, and their benefits may be realized only after several years.
Our Recommendations: Insurance Data Entry Automation with Human Intervention
As it is amply evident, the advantages of insurance data entry clearly outweigh its traditional form of data entry. This is why the insurance industry has increasingly gone ahead with Data Entry Automation recently. AI-enabled applications and tools have greatly helped increase the volume of work undertaken. However, replacing human capabilities must not be the ultimate goal. Insurance automation with human intervention, in good measure, is the way forward.
Data validation is still necessary for those companies who have already automated their insurance processors to ensure the automation is working the way it should be. Human-centric data validation will help ensure the data collected is error-free, legitimate, and relevant.
For example, when manually written data in printed forms are converted to digital text using OCR software, there are many instances when the letter or numbers can be wrongly recognized, which could result in wrong data collection. Hence, human intervention is required to ensure the final data is precise and error-free.
Insurance companies that have yet to automate or partially automate their services can still ensure high-quality data management by outsourcing their data entry services to third-party vendors. Quality, affordable, and verified data entry services are critical factors of consideration that will ensure a successful outcome in one’s business endeavors.
Our competent team of professionals is proficient in Data Management and specializes in data collection, data entry, and data validation. They work diligently and round the clock according to your time zone to offer scalable datasets and can fulfill your data needs through an outsourcing model. Contact us for a quick chat, as we have a solution for your data management problems.
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