Whether operating in home insurance, health insurance, auto insurance, or any other insurance sector, maintaining high underwriting efficacy should be your company’s top priority. After all, accurate risk assessment in the underwriting process helps you make effective insurance decisions, which is critical for your business to stay financially healthy.
As your company grows and its clientele expands, determining coverage eligibility, assessing potential risk and reward, and calculating premiums accurately for each individual customer becomes more challenging. With its workflow automation and data analytics capabilities insurance underwriting software can help you navigate underwriting complexities and streamline this business process.
The article highlights three common insurance underwriting challenges and specifies how a tailored technology solution can address them.
Challenge 1: Locating and sourcing data required for underwriting
To accurately assess potential risks and determine coverage terms for policyholders, underwriters analyze a wide range of data from multiple sources, both internal and external. This can range from the applicant’s personal data and claims history to third-party data, such as records from property and vehicle databases or information from credit bureaus.
Without specialized software in place, underwriters have to collect all this data manually from paper documents, corporate systems, and other sources. And this manual approach is highly inefficient – it requires too much effort and time, which can cause frustration for both underwriters and customers. In addition, collecting and processing data manually poses risks for an underwriter to miss some valuable information, which can negatively affect the accuracy of the applicant’s credibility and risk assessment.
An insurance underwriting system integrated with different corporate and third-party data sources can provide professionals with all the information required to do their job efficiently. It consolidates data from corporate systems such as claims management software and document management software, and external resources, for example, property information databases, and brings this data to a unified view, making it ready for analysis and further usage.
Thus, insurance underwriting software eliminates the need for underwriters to source necessary data manually, increasing the speed at which they operate. The software also provides underwriters with a 360-degree applicant view, thereby helping them perform comprehensive and accurate risk assessments, which improves the overall quality of underwriting decisions.
Challenge 2: Making underwriting decisions quickly and accurately
Besides having relevant and accurate data at their fingertips, underwriters also need to carefully review and analyze it to create a comprehensive client risk portfolio, decide whether to approve or reject an application, and decide how much money a customer should pay for an insurance policy. The need to review and analyze vast amounts of information can cause delays in underwriting decision-making, which can increase the risk of applicant drop-off. However, ensuring high underwriting speed without sacrificing accuracy is a challenging task for any insurance company.
Insurance underwriting software offers multiple solutions to help insurers make accurate underwriting decisions faster. For instance, a company can use an insurance underwriting system complemented with AI technology to automate the process of insurance risk assessment. Once an underwriter submits an applicant’s information to the system, it can automatically analyze the submitted data (including credit bureau data, past claims data, and other personal and financial information) and factor in additional risk parameters (from weather conditions to local crime rates) to create an accurate risk profile of the customer.
Based on this profile and all underlying risk factors, the system can determine the likelihood and severity of potential losses associated with an insured item or person. It then recommends the most risk-free underwriting decision, namely, to approve or deny the customer’s application.
Suppose the customer’s application is considered eligible, and the human underwriter approves it. In that case, the insurance underwriting system can also help the specialist determine the amount of money a customer should pay monthly or annually to keep its insurance policy active. In particular, the solution can analyze relevant data, such as a customer’s past paid premiums and claims, while taking into account factors such as policy terms, risk levels, and industry pricing benchmarks, to estimate an optimal insurance premium.
Challenge 3: Spotlighting and preventing underwriting fraud
Underwriting fraud can take many forms, from fabricating personal or financial data and manipulating medical histories when applying for insurance policies to using fake identities or naming counterfeit beneficiaries. Identifying and preventing fraud before it makes any significant impact can be difficult for human underwriters, especially if your company serves a high volume of customers.
A robust insurance underwriting system can help your company detect underwriting-related fraud automatically, much faster, and more accurately than human specialists. For example, a solution augmented with AI capabilities can review all insurance applications a company receives in real time to identify suspicious applicant behavior. Such continuous fraud analysis minimizes the likelihood of processing fraudulent applications, which can save a significant portion of your company’s finances.
Final thoughts
Underwriting is one of the most critical aspects for any insurance firm, as it helps foresee insurance risks and reduce the likelihood that claims are made against its insurance policies. Ensuring high underwriting accuracy and speed can be challenging, especially if an insurance business grows rapidly and its customer base expands. To streamline underwriting processes and hurdle complexities their employees face, companies can implement robust insurance underwriting software.
If you are thinking about adopting an underwriting software solution, consider consulting with third-party experts before launching an implementation project. They will thoroughly analyze your business needs, help decide whether you should purchase a ready-made software solution or build one from scratch, and provide assistance with any implementation aspect, from tech stack selection to software development and deployment.
(DISCLAIMER: The information in this article does not necessarily reflect the views of The Global Hues. We make no representation or warranty of any kind, express or implied, regarding the accuracy, adequacy, validity, reliability, availability or completeness of any information in this article.)
