The insurance industry has been known for tedious, manual underwriting processes. However, with the rise of digital technology, the underwriting landscape is rapidly changing, and automated underwriting in insurance is emerging as a critical innovation.
As a vendor involved in developing and implementing rule engines, InRule has seen firsthand how automated underwriting can transform operations, improve accuracy, and enhance customer satisfaction.
In this article, we’ll explore how using automated decisioning and machine learning to automate underwriting is no longer just a trend but has become a requirement to compete in today’s competitive insurance industry.
The Evolution of Underwriting
A 25-second story of underwriting
Traditionally, underwriting in insurance has been a labor-intensive process. Underwriters would manually assess risk by evaluating various factors, such as the applicant’s financial history, medical records, or property details.
While thorough, this process was slow and prone to human error and inconsistency. As the volume of applications (or spreadsheets) increased, so did the time it took to process them, leading to delays and customer dissatisfaction.
Over time, insurance companies began to adopt digital tools to streamline underwriting, The tools helped reduce paperwork but required fundamental changes in how underwriting decisions were made. However, with the advent of advanced technologies like artificial intelligence (AI) and machine learning, the insurance industry is now on the brink of a revolution.
The transition from spreadsheets
The push towards decision automation in underwriting started with the need to process applications faster while maintaining accuracy. This was initially done in spreadsheets, but organizations quickly learned that spreadsheets would not scale to fit modern needs. A better way was needed.
To improve Automated underwriting insurance companies have started to rule engines, and sometimes machine learning, to assess risk, evaluate applications, and make real-time decisions.
InRule has worked with a large number of insurance companies that struggled with backlogs of applications who adopted a rules engine as part of their automated underwriting solution. Within months, these companies saw a dramatic improvement in processing times, reducing the average turnaround from weeks to days.
Not only did it positively impact customer satisfaction, but it also allowed the company to take on more business without increasing operational costs.
So, what are the true benefits of an automated underwriting process?
Speed, speed and… speed (and efficiency)
Did we mention speed? One of the most significant advantages of automated underwriting is its speed. By leveraging decisioning and machine learning, automated underwriting systems can analyze vast amounts of data in seconds, allowing insurance companies to process applications much faster than traditional methods.
Use Case Example: Consider an insurance company specializing in life insurance policies. Before automation, it took underwriters an average of three weeks to process an application due to the need to review extensive medical records manually.
After implementing an automated underwriting solution, the process now takes less than 48 hours, leading to a significant boost in customer satisfaction and a 20% increase in policy issuance rates as well as 90% reduction in process application time.
Do Away with Human Errors
As with any repetitive and manual task, human error is an inevitable part of manual underwriting. Automated underwriting solutions eliminate this risk by consistently applying the same rules across all applications. This not only improves accuracy but also ensures fairness and consistency in the decision-making process.
Improve Scalability
As companies grow, so does the volume of applications they need to process. Scaling manual underwriting processes to meet this demand is costly and inefficient.
On the other hand, automated underwriting solutions such as business rules engines can easily handle increased workloads without requiring significant additional resources.
How Does Decisioning and Machine Learning Affect Underwriting?
Data-Driven Decisions
The combination of decisioning and machine learning can have a profound affection on insurance underwriting by enabling Data-Driven Decisions.
Automated decisioning, powered by a rule engine, and machine learning are the driving technologies behind automated underwriting. These technologies allow systems to analyze vast datasets, identify patterns, and make informed decisions based on real-time data, all while keeping humans in the loop.
The level and scale of analysis are far beyond what human underwriters can achieve using traditional methods, leading to more accurate risk assessments, better decision-making, and improved efficiency.
Continuous Learning and Improvement
Machine learning and one of its key benefits, is its ability to learn and improve over time. As the system processes more data, it becomes better at predicting outcomes and refining its decision-making algorithms. This continuous improvement ensures that the underwriting process remains cutting-edge and highly efficient.
How Can Customer Experience Improve With Automation?
Personalization at Scale
In today’s competitive market, providing a personalized customer experience is crucial and on every leading company’s agenda. Automated underwriting allows companies to offer customized policies tailored to individual risk profiles, leading to higher customer satisfaction,retention, and improved profit margins.
Faster Turnaround Times
Speed is a critical factor in customer satisfaction. Automated underwriting drastically reduces the time it takes to process applications, which means customers receive decisions—and their policies—much faster.
Compliance with Evolving Regulations
Insurance is a heavily regulated industry, and staying compliant is a constant challenge. Automated underwriting insurance systems ensure that every application is processed according to the latest regulations. These systems can be updated quickly as new laws are enacted, reducing non-compliance risk.
Real-Time Risk Management
Automated underwriting insurance systems provide real-time monitoring and risk assessment, allowing companies to adjust their strategies on the fly. This proactive approach to risk management helps reduce the likelihood of financial losses and enhances overall operational efficiency.
Automated Underwriting Systems Empower The Next Leap for Insurance
Industry Trends On the Horizon Generative AI
As technology continues to evolve, so will automated underwriting. Future trends include the increased use of generative AI, which will further empower underwriting processes’ accuracy and efficiency.
Gaining a Competitive Advantage
Early adopters of automated underwriting insurance will have a significant edge in the competitive insurance market. These companies will be better positioned to offer faster, more accurate, personalized services, to better attract and retain customers.
Overcoming Challenges
While the benefits of automated underwriting are clear, challenges exist, such as integrating new systems with existing infrastructure and ensuring data privacy and security. However, these challenges can be overcome with careful planning and the right technology partners.
Read more about how InRule addresses privacy and security here.
Should You Invest in Automated Underwriting?
Automated underwriting insurance is not just the future of the industry—it’s already shaping the landscape today. By embracing this technology, insurance companies can improve efficiency, accuracy, and customer satisfaction while staying ahead of regulatory changes and market trends. The message for business leaders is clear: investing in automated underwriting systems and solutions is a strategic move that will pay dividends in the long run.
If your company hasn’t yet explored automated underwriting, now is the time to do so. Get in touch with us to learn how to leverage automated underwriting to improve your business.
Or… you can just sit back and wait six months to watch how your competitors leverage it to offer your clients a better experience.
