Let's be clear: The job of an underwriter is not easy. It is complex and multi-stage, requiring precise data management, communication with various stakeholders and the application of sophisticated risk analyses.
A typical day for an underwriter starts with reviewing dozens of emails, most of which pertain to inquiries, documentation or updates on claim statuses. Next, the underwriter moves on to manually entering data into various systems, verifying documents and analyzing the risks associated with individual policies. Any error or missing information can lead to delays, damaging customer satisfaction and overall work efficiency.
In discussions with representatives from the insurance sector, I have noticed numerous challenges facing underwriters. In this article, I would like to present a remedy for the various inconveniences of underwriters' work.
Challenges Facing Underwriters
Underwriters struggle with daily chaos and information overload due to the processing of enormous amounts of information. Documentation, emails, insurance applications and client data all must be thoroughly assessed. The lack of consistent and integrated systems does not help, leading to errors and delays.
Decision-making processes, still based on manual data processing and risk assessment, also contribute to delays. It is common for underwriters to wait for additional information or approvals.
Significantly, manual data entry is still prevalent. This activity prolongs working hours, is monotonous and time-consuming and increases the risk of errors.
Additionally, changing legal and regulatory requirements necessitate continuous knowledge updates and process adjustments.
All these challenges ultimately affect the customer, whose expectations for fast and personalized service are rising. Underwriters need to respond quickly to inquiries, tailor offers and provide support at every stage of the insurance process. Otherwise, the company risks losing the hard-earned customer.
See also: AI's Role in Commercial Underwriting
The New Era of Underwriting
The future of underwriting is looking bright thanks to artificial intelligence (AI) and business rules engines (BRE). Let’s explore how these solutions can enhance the efficiency of underwriters' work.
Artificial Intelligence
Underwriters perform many repetitive tasks, such as data entry, sending emails, generating routine reports and monitoring application statuses, which consume a significant portion of their workday.
How AI can help them in their daily work?
Aan underwriter at a property insurance company may be required to enter property details and client information into multiple systems. AI can automate these tasks by automatically filling forms based on previous entries or sending automated policy renewal reminders.
Another example from the underwriter's life involves reviewing numerous insurance applications, each containing extensive documentation such as medical records, financial statements and credit histories. An underwriter handling life insurance policies might need to review detailed medical histories to assess the risk associated with pre-existing conditions. With AI-driven data processing automation, these documents are quickly scanned, and relevant data points extracted and analyzed. This automation not only reduces the time spent on manual data entry but also ensures that all critical information is accurately captured and easily accessible for risk assessment.
Another example could be an underwriter working for an auto insurance company. They must assess the risk associated with insuring a driver by analyzing factors such as driving history, age, location and vehicle type. Traditionally, this process involves manual analysis of historical claims data and personal information. AI can streamline this process by using machine learning algorithms to analyze vast amounts of historical data, identify patterns and predict the likelihood of future claims. This enables the insurer to make faster and more accurate decisions regarding premium rates and policy terms.
Business Rules Engine
In the underwriting process, a BRE allows for the automatic management of repetitive and rule-based tasks. However, nothing happens by itself. BRE is a tool through which underwriters themselves decide what will be implemented. How certain tasks are carried out will depend on the rules they create.
Consider a flood. Last year, the residents of this area experienced a flood, and this year their insurance policy is up for renewal. All of them have a so-called flood damage claim. The insurer, however, does not want to take on the flood risk, so the policy renewal must go through an underwriter. Traditionally, the underwriter would have to review each application individually. Using a BRE, a single rule is enough to handle everything automatically.
Another example of using a BRE is in auto insurance, where it can assess the driver's risk level by automatically checking their driving history. If the applicant has had no traffic accidents in the past five years, the BRE assigns a lower risk score and approves the policy with a lower premium. If the applicant has multiple violations or accidents, the BRE flags the application for review. This automation not only streamlines the policy issuance process but also ensures consistency and accuracy in risk assessments.
BRE also helps maintain information consistency. In a health insurance company, underwriters can use a BRE to verify customer information. The BRE checks the consistency of personal details, such as age or date of birth. If the client's age does not match the date of birth, the BRE automatically flags it for correction. This validation step helps maintain high data quality.
BRE lets underwriters focus on more strategic and valuable activities.
See also: Insurance Underwriting Will Never Be the Same
Will Automation Replace Underwriters?
Will automation completely replace underwriters? The answer is not straightforward and requires understanding how automation affects various aspects of underwriters' work.
Automation can significantly ease underwriters' daily tasks by taking over routine and repetitive tasks, such as data collection and verification, preliminary risk assessments and the generation of standard reports and documents. Underwriters will still play a crucial role in managing and overseeing automation technologies. Their expertise is essential for calibrating AI systems and updating business rules to comply with current industry standards and regulations.
Automation cannot replace the human experience and intuition in solving complex risk cases. Underwriters will still be necessary for analyzing situations that require a personalized approach and deep industry knowledge.
Automation also cannot replace human interaction. High-quality customer service often requires personal contact and interpersonal skills, which are challenging to automate.
Conclusion: Automation as an Opportunity
Modern technology will support underwriters, not replace them. This opportunity leads to synergy, which can benefit both insurance companies and their clients. With automation, underwriters can focus on more strategic and complex tasks, increasing their job satisfaction and efficiency. Meanwhile, faster customer service, error reduction, and process optimization lead to increased profits and better customer service.
According to a McKinsey report, automation can increase operational efficiency in insurance by 30% to 40% and reduce claim processing time by 50%. This proves that investing in modern technologies and automating underwriting processes is not just a trend but a necessity to stay competitive in the market.
