Insurance Industry collects and processes a huge amount of data of their customers. This data is usually collected by insurance professionals using manual methods like filling up of printed forms which is later on sent for processing. Underwriters in insurance companies evaluate the risks of an insured person using personal details and claims data to calculate the gross and net premium for policy issuance. Such kind of data is usually stored as standalone information and is difficult for insurance agents to access or share to relevant stakeholders. Such kind of data is also difficult to analyze and use for decision making resulting in higher cost and loss in sales.
Insurance Data Analytics helps insurers by providing accurate data and intelligent insights on every aspect of life insurance. Data Analytics helps in acquiring the necessary data in a very short amount of time and provides solutions which customers actually want. It also helps companies to improve the customer experience while cutting claims handling costs and eliminating fraud.
Data Analytics in Insurance Industry is also helping companies to mitigate risk by providing analyzed information in a timely fashion. It provides information alerts explaining the risk attributes and proposes a solution to resolve the issue. Insurers are also using predictive data analytics to fast track claims and process them with little or no human intervention. The traditional way of analyzing data has limits for newer categories like food safety, cyber or supply chain disruption, by using the Data Analytics tool insurer is able to overcome such limitations.
In the modern world, data analytics is transforming the insurance industry in the following ways.1. Handling fraud cases – Insurance Data Analytics has been extremely helpful in identifying and resolving fraud cases. By using Social Network Analysis and telemetric a large amount of data can be checked in a very short span of time thereby reducing the number of fraudulent claims. This has led to a substantial cost savings of Insurance companies and has also helped to prosecute offenders.2. Customer-centric- Latest Insurance Data Analytics tools have also helped the insurance industry to be more client-centric. Insurance Management Solutions by use of Technology also provides actionable insights into customer data thereby allowing agents to make informed decisions. An agent can have a complete overview off his client’s portfolio and help in bridging any possible gaps in client’s policy. He can then actually let the client know about what is missing in the policy, which not only enhance customer satisfaction but also increases sales.
3. Subrogation cases – Huge amount of data is received and required for subrogation cases which may come through medical records, police records or any other source. Insurance Data Analytics provides phrases that can show that the cases being investigated are subrogation cases.4. Premium pricing- Insurance companies have traditionally relied on statistical predictions like “the law of large numbers” to fix policy prices which are generally not accurate. Advanced Insurance Data Analytics logarithms allow insurers to fix policy premium pricing, provide customized product offering and do profitability analysis of policies offered.
5. Handling Complex cases – Data Analytics in Insurance sector has also enabled insurers to handle complex cases efficiently. By using data mining techniques where claims are categorized and scored as per their importance, claims are prioritized and settled accordingly.
6. Case settlement – By the use of Data analytics, it is possible to check and analyze the claims of each customer quickly and easily. This helps reduce employee’s work costs as they don’t have to check and analyze data regarding the claim manually. It helps in the processing of customer payouts faster, thereby increasing customer satisfaction and reduction in lawsuits.