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Underwriting is the process by which insurers assess the risk and profitability of offering a policy to an individual or entity. Underwriting is a complex process involving data, statistics, and actuarial guidelines. Underwriters use this information to assess the level of risk and establish premiums based upon that risk.
Takeaway: An efficient underwriting process is crucial to an insurer’s profitability and viability.
Underwriting workflows are characterized by multiple reviews and hand-offs, many of which are manual processes, resulting in delays and inefficiencies. This, coupled with pressure to reduce cost while maintaining or improving quality, makes underwriting especially challenging.
Many underwriting platforms lack the ability to pre-screen and pre-approve policies, preventing the underwriter from focusing on those challenging applications that represent the greatest risk to the carrier.
There is a massive amount of new information available to underwriters both internally and from third-party data providers. This can be a blessing for underwriting helping to make better informed decisions regarding risk. Unfortunately, most underwriting systems are unable to integrate new data sources.
Carriers are often not satisfied with their current underwriting systems and workflows. Many systems are not flexible enough to support new products, rates, price packages, or complex workflows.
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Traditionally, claims processing requires multiple handoffs between systems and claims handlers. This complexity and inefficiency best case results in information silos; and worst-case results in an inability to collect the information required to adjudicate claims. Rework, process bottlenecks and delayed payments can result in customer dissatisfaction, decreased productivity, increased operating cost and loss adjustment expense.
Takeaway: A streamlined claims process is key to delivering a better customer experience.
Most insurance companies use traditional data collection methods, including email questionnaires, webforms, PDF forms, and even worse, phone conversations. Inefficient data collection results in inaccuracies, process delays, rework, and customer frustration.
Claimants can be frustrated by the process; not knowing when they will recoup their losses and having to constantly chase their insurer for updates. These concerns are amplified if claimants must manage multiple points of contact, repeatedly answer the same questions, and arrange multiple appointments for damage assessments before they can be made whole.
Reserve accuracy is one of a claims department’s most important responsibilities. Inadequate reserving can raise the attention of auditors and regulatory agencies, jeopardize reinsurance recovery, and impact financial statements.
Insurance is a heavily regulated industry making it nearly impossible to ensure all rules are being followed and proper protocol maintained.
Claims processing requires the collection, review, and management of disparate documents and sources of information and making them available throughout the claims process.
Insurance providers have been slow to embrace modern technology due to the difficulty of integrating with legacy systems or transitioning to contemporary, fully-digital platforms.
Policy management systems are designed to manage policies through the lifecycle from quote to termination. Policy administration systems facilitate customer facing operations like quoting, handling transactions, and corresponding with policy holders. On the back end, policy administration systems integrate with underwriting, rating, billing, and accounting systems; and include batch processes like policy renewals and terminations.
Takeaway: A well-designed policy administration system is key to efficient insurance operations.
Today’s insurance consumer demands self-service capabilities. They want to obtain quotes and perform simple transactions without contacting an insurance agent. Legacy policy administration systems do not provide this capability and are too inflexible to integrate with emerging technologies.Two problems often associated with the quote/bind process are data collection and prolonged cycle times. Traditional data collection methods include email questionnaires, webforms, and phone interactions. Inefficient data collection results in inaccuracies, process delays, rework, and customer frustration. Imagine requesting a quote only to discover days later that you were denied for not meeting underwriting guidelines.
Today’s insurance consumer demands self-service capabilities. They want to obtain quotes and perform simple transactions without contacting an insurance agent. Legacy policy administration systems do not provide this capability and are too inflexible to integrate with emerging technologies.
Insurance is a heavily regulated industry and regulations vary by location and line of business. This complexity makes it nearly impossible to ensure all rules are being followed and proper protocol maintained.
Policy Administration requires the generation, collection, review, and management of disparate documents and sources of information and making them available throughout the policy lifecycle.
Many policy administration systems are old, difficult to maintain and expensive to run. Legacy policy administration systems are inflexible and difficult to integrate with contemporary systems. Legacy systems may be the greatest obstacle in servicing policy holders.
Implementing ACORD across organizations as a common data standard.
Integrating applications with internal and external rating systems including quoting and binding.
Automating document generation to enhance data quality.
Integrate with internal and external systems including claims and underwriting.
Bring the transformational technologies used by InsurTechs to modernizelegacy applications and platforms.
Delivering web and mobile applications that enhance and deepen engagement with your customers.
Replace manual processes to accelerate operations throughevents, rules, and notifications.
Enable and implement contemporary technologies by breaking up monolithic applications using Containerization, Serverless Technology, empowering your development team with CI/CD pipelines, and the many benefits ofDevOps.
Migrating applications from on-premises environments to the cloud, delivering operational efficiency, eliminating costly, inflexible, and monolithic infrastructure, and opening the door for transformational technologies such as data analytics, machine learning, and artificial intelligence.
Integrating your applications with third-party data providers such as LexisNexis, ISO, Verisk.
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