The common bottlenecks which might slow down your business growth
The overall process of an insurance claims involves back and forth between the customer and insurance companies and is quite cumbersome.
Paper-based processes and a general lack of technology innovation have hampered the process of insurance claims.
There are volumes of data available in the insurance claims industry, but the lack of structure makes this data unusable.
Outdated and time consuming processes are pervasive in the industry, thereby causing considerable delays in the outcome.
The traditional process is highly dependent on specific employee execution and results in low levels of satisfaction.
The current system of acquiring information from customers for insurance claims requires a substantial amount of time.
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Reduced processing time and increased quality of service through big data analytics in insurance claims
In the current process, claims go through multiple employees that severely affect the quality of the process. Through claims analytics in insurance, the process of ‘touchless’ claims does not require any human intervention. This is done through the automated reporting, capturing, auditing and communication.
This is a technology that leverages popular messaging apps on customers’ phones to execute interaction. The technology of natural language processing and sentiment analysis allows for automated and effective communication. Claim analytics in health insurance allows for customized interactions, wherein questions can be answered, claims can be resolved, products can be sold, leads can be addressed, and coverage issues can be identified.
The competitive streak of the insurance market can be tackled through claim analytics in health insurance that offer personalized sales tactics. AI has the potential to rope in customer data and create a profile that targets the customer’s preferences with relevant insurance products.
Insurance claims data analytics cuts down on the traditional underwriting process, which is tedious and fairly ineffective. Not only can it offer customers the benefit of a personalized insurance plan, but the automation feature can alert insurance companies on risky customers without the need for invasive questioning.
Wireless communication is a feature of insurance claim data analytics that offers data from the customers to the insurance companies in an automated fashion through identification of GPS patters in the data. This technology is capable of tracking traffic conditions, risk factors, etc. that eventually lead to fewer claims processing and higher customer satisfaction.
The ability to meaningfully generate and apply data through machine learning holds tremendous scope to improve insurance and claims companies bottom line and overall profit through claim data analytics solutions. It offers features such as electronically generated customized insurance advice and improved insights into the needs of the customer.
The current system has insurers adopting speedy processes to settle claims quickly. However, this causes many instances of overpayment, due to the eagerness to settle claims. Our deep data analysis assists in the optimization of payouts to curtail the time involved in claim cycles and reduce insurer costs through limited instant payouts. Additionally, the insurer is able to save more revenue loss.How we do it
At OSP Labs, our insurance claims analytics work to automate the entire lifecycle of insurance claims, from prioritization, forecasting, to improvisation of speed and accuracy of claims. Our process-driven solutions leverage big data analytics to improve risk management toward underwriting, resource utilization to settle claims, prediction of disputed claims, and data mining toward automation of claims processes.
We engage with your organization to create systems that are geared to perform intelligent predictive analysis of data that is able to highlight the likelihood of claims that are bound to be frauds, cause wastage or even abused. This is executed through data model and patterns that are developed through broad exposure and investigative data mining abilities that hunt customer data to minimize the chances of frauds, waste and abuse.
Compensation insurance is one that requires keen monitoring through automated features due to the high volume of claims in this arena. Our solutions are empowered with predictive analytics to gauge the risk factors with compensation insurance, specific to customers, through the analysis of their data. This preemptive approach avoids expenses through identification and risk analysis of inaccurate payments, and suggestions for early intervention.
We follow every government's regulatory mandate and create solutions that adhere to strict protocols.
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