The insurance industry, like others, is en route to digital transformation, underwriters are still lagging due to several challenges arising out of the legacy policy administration systems.
The insurance sector has been overlooking underwriting, focusing less on its efficient management. Insurance carriers spend 60-70% of the premium collected on settling claims and the remaining 30%-40% on marketing, sales, and broker commissions.
They usually distribute the premium balance to deliver profit to stakeholders and manage operating costs, including underwriting expenses. Although underwriting costs are a small portion of the total overhead, insurers can increase profitability if they make better decisions on handling underwriting because this can help lower the cost of claims.
However, for many companies, underwriting efficiency improvement is not on the agenda of transformation.
The Utter Need to Consider Underwriting a Central Area for Profitability
Any insurance company’s top management has its entire focus on maintaining overall productivity and growth. In most cases, the management expects employees and teams to work together for a common goal. Let’s take an example for this.
When employees walk the extra mile to go beyond their individual targets, collaborate and contribute to better overall performance, especially in areas crucial for the success or failure of the company, top leaders would appreciate that and be impressed.
There’s no doubt that companies acknowledge and reward revenue generators. Considering all this, it is high time for underwriters to showcase their importance and position themselves to be recognized as a crucial part of the revenue-driving team.
However, the road to recognition is not as easy as it might seem.
The most critical system of any insurance carrier is the policy administration system (PAS). Despite playing a central role in supporting other insurance business functions, several challenges arising due to legacy PAS make it difficult to obtain underwriting excellence; let’s discuss a few.
Challenge 1: Unstructured and Inflexible Data Sets
The legacy systems still used for policy administration run on rigid data models. This makes it extremely difficult to extend the system to capture additional data, catch up with other lines, and expand business in new geographies.
Hard-coded underwriting rules are impossible to improve until the system itself is not modified. Not only this, flat, well, to be precise, inflexible and unstructured data sets hinder reporting, making it considerably challenging to observe basic patterns like policy ownership or company performance.
Challenge 2: Lack of Features in PAS
The legacy policy administration systems were developed to rate and book policies, far away from generating new business opportunities. Most of such systems;
- Don’t offer an easy way for agents to manage and submit their work
- Cannot be linked with agency management applications where agents store most of the data
- Don’t offer any support for underwriters to monitor and optimize the portfolio of agent relationships.
When things are not interconnected due to any reason, the reason becomes an obstacle to underwriting excellence.
Challenge 3: Unfamiliar Interface
Since the legacy PAS was built to reduce data storage, little attention was given to its interface. As a result, these systems usually have a not-so-easy-to-understand interface. Many new employees generally take a lot of time (sometimes months) to understand it and learn about its functionalities.
Consequently, data processors and underwriters often spend a lot of their valuable time carrying out basic processing tasks. Moreover, many times, they need to leave transactions to be processed overnight, extending the time taken to change, renew policies or update policy-related reports.
Maybe this is the reason many insurers opt for underwriting support services from providers expert at handling modern policy administration and management systems.
Challenge 4. Manual Underwriting Methods
The legacy PAS cannot be used for underwriting purposes; however, it can support an underwriter to manage core jobs falling under a risk evaluation and building relationships with agents and insurants.
For many processes, mainly in commercial lines, underwriters depend upon paper to obtain account data, risk information, policy documents, etc. This massive amount of data usually reaches underwriters in an unstructured form, making it challenging to make rule-based decisions.
A lot of underwriters would agree that their legacy policy administration methods are challenging, especially those at the supervisory level, who need to follow manual procedures for monitoring and managing the work distribution and the performance of individual underwriters.
Solutions to Overcome Underwriting Barriers
Solution 1: Utilization of Software, Specialized for Underwriters
Amid the major digital transformation in the industry, what software-oriented underwriting is and what its effects would be are uncertain. However, viewed from an analytical perspective, the role of underwriters can be simplified, enabling them to make better decisions on the basis of the abundance of data.
Many insurers are slowly shifting underwriting from human beings to digital algorithms. However, the idea of automating underwriting on a larger scale might not impress many in the industry as the nature of work is different in each line of insurance business. In commercial lines, humans and technology can work together efficiently and bring the most favorable outcomes.
Solution 2: More Use of Analytics Tools
Instead of seeing underwriters as a role that will soon be completely automated, insurance experts are redefining underwriters as data scientists. This definition they are getting as they heavily depend upon analytics tools to measure and manage risks.
Therefore, an underwriter’s value depends upon their level of capability for data aggregation and the skills they have for analyzing data in order to apply brilliant perspective and judgment. The more they use analytics tools, the closer they can reach risk minimization.
Solution 3: Technology to Support Underwriters of the Future
In a few years from now, algorithms will not replace underwriters. In contrast, they will enable underwriters to evolve into the role of data scientists obtaining insights using analytics. Insurers looking to become a data-driven organization must know that they need to take various steps in order to achieve their goals.
For example, insurance companies need to allow their underwriters to access comprehensive data, integration tools to combine data obtained from external and internal sources, and intelligent analytical tools. There needs to be a complete solution to build a data-centric environment that will be enough to support the rapid emergence of digital underwriters.
Benefits of this Transformation for Insurers
Making improvements in underwriting and related processes can result in:
- Customer satisfaction: Simple, transparent, and streamlined processes boost customer satisfaction.
- Cost savings: Implementing modern technology for underwriting purposes can help reduce underwriting costs. Several tedious, repetitive, and laborious jobs don’t need a team of 5 employees but just one skilled person with knowledge or expertise in handling data and analytics tools.
- Efficiency enhancement: What a professional team does in an entire day, underwriting tools can do within a few minutes. Hence, increasing efficiency – more work in less time.
As an insurance business owner, you might also be slightly pressured to choose between legacy underwriting applications and modern tools.
