PAS Implementation for Insurance Firms: Exploring Advanced Product Configuration Challenges

Building on our previous discussion on Policy Administration Systems (PAS) for insurance companies, we now shift focus to the practical aspects of Product Configuration within the PAS framework. A well-implemented PAS is foundational for operational efficiency, customer satisfaction, and staying competitive in the market.

[See the previous article: Expert Insights on PAS Implementation for Insurance Firms]

In this article, we explore the advanced aspects and complexities that emerge as companies move beyond the initial launch and navigate the further stages of the Product Configuration lifecycle. While our earlier discussion covered the basics of PAS, it is time to delve deeper into the essential details that ensure the effective management and ongoing evolution of an insurer's operational platform. We will analyze:

• Effective-Dated Product Changes,
• Product Logic Corrections for In-Force Policies,
• Multi-Product Portfolio Configuration,
• Product Configuration Development Lifecycle.

Addressing these challenges requires collaboration between specialized implementation partners, PAS platform providers, and business stakeholders to ensure successful PAS implementation.

Effective-Dated Product Logic Changes

After launching a new insurance product and building the initial book of business, adjustments in rates, forms, or rules become inevitable. These changes are typically scheduled to take effect on a specific date, impacting only new policies issued after that. Existing policies must adhere to the original terms under which they were bound.

Looking ahead, companies might use several strategies for handling these changes to the existing book of business:

• Retaining their original rates and conditions for existing policies,
• Switching existing policies to updated conditions upon renewal,
• Customizing approaches to fit specific business needs.

Implementing effective-dated changes in product configuration can vary significantly depending on the chosen PAS. Some platforms may offer robust mechanisms to seamlessly support effect-dating across different aspects of product configuration. Others may require effect-dating to be implemented entirely as part of custom business logic. If the platform supports effect-dating but only for limited elements of product configuration, a hybrid solution combining platform functionality and custom logic may be required.

The complexity of managing effective-dated product logic lies in the need to support multiple versions of product configuration simultaneously. The system must handle in-force policies that rely on different configuration versions at any given time. This requires careful planning and engineering as part of a comprehensive PAS Solution Architecture, blending platform capabilities with additional custom solutions.

Product Logic Corrections for In-Force Policies

A different challenge arises when inaccuracies or errors in pricing, policy documents, or other business logic are discovered within live products. Unlike scheduled future-dated changes, these corrections need immediate action, affecting both active configurations and existing policies. They may also involve "patching" active policies to incorporate the necessary adjustments.

This brings us to a critical consideration: Policy Administration System's capability to correct or "patch" in-force policies. When outputs like pricing or document generation are automatically produced during specific policy lifecycle events fully managed by the platform, how can these be corrected after the fact?

Potential approaches include:

• Correction Endorsement: This involves configuring a special type of endorsement to override standard processing and apply the necessary corrections directly to the policy. This might also require additional modifications to the product data model to enable different transaction processing modes.
• Transaction Reversal: If supported by the platform, this approach involves reversing the previous transaction and reapplying it after updating the erroneous logic in the configuration.
• Cancel-Rewrite Process: This is a commonly available method that doesn't require additional PAS functionality. The company cancels the original policy and issues a new one using the corrected configuration. While feasible in most system environments that support basic policy cancellation and issuance functions, the added manual processes can increase the workload on internal policy servicing teams.

The best approach depends on the platform's capabilities and the company's business requirements and should be integrated into the PAS Solution Architecture.

Multi-Product Portfolio Configuration

The complexity of product configuration increases further when a company offers a range of products, especially when products share a common foundation but vary in certain aspects. For example:

• The same product might be offered across different states, with variations due to state-specific regulations or requirements from various carriers.
• The company might offer different forms of the same insurance type (e.g., different homeowners forms: HO-3, HO-5, etc.) differentiated by factors such as named vs. open peril coverage, included coverages, and eligible property types. Despite these differences, the products might be structurally similar and utilize the same core underwriting data.

This scenario requires technology capable of configuring and maintaining a portfolio of multiple product definitions that incorporate both shared and unique elements.

Given the diverse capabilities of different PAS platforms, there might be other approaches to organizing multi-product configuration artifacts:

• Separate Product Definition Instances: Each variation is defined independently, duplicating similar components across different product definitions. While this approach is straightforward, it can lead to redundancy and increased maintenance overhead.
• Universal Configuration (Umbrella Model): A single configuration manages multiple products through conditional logic. This model can streamline management on a smaller scale but may become overly complex as the portfolio grows.
• Sophisticated Product Models: Some PAS platforms might support advanced product models, allowing reusable components and mechanisms such as product generalization and inheritance. These can be used to build flexible, modular configurations. This approach can enhance implementation efficiency but may also complicate the resulting complex product model's navigation, understanding, and management.

Regardless of how the final configuration is structured in the system, maintaining a cohesive understanding of the entire model is critical. When logic is fragmented and divided into common, reusable components, it is essential to have a clear view of how each actual product instance is assembled. This includes tracing component usage, identifying redundant elements, and assessing the impact of changes in any individual place. The ability to compare, analyze, and understand business logic variations is crucial for a comprehensive understanding of the entire product portfolio.

Designing and maintaining a multi-product configuration requires solid requirements engineering and knowledge management to ensure consistency, reduce inefficiencies, and maintain manageability. Structuring multi-product configurations is another vital aspect that must be addressed within the overall PAS Solution Architecture to ensure alignment with both platform capabilities and business needs.

Product Configuration Development Lifecycle

Product configuration follows its own development lifecycle, separate from the core development cycle of the underlying PAS platform. It is a complex entity in its own right, with many Software Development Lifecycle (SDLC) principles applicable to it. Changes must be designed, implemented, and thoroughly tested—resolving all identified issues—before being applied to the live system.

The technical details of the process vary depending on the format and technology used by the PAS to organize the configuration and the tools available for managing it.

To illustrate this, we can compare two different models: No Code/Low Code and Configuration-as-Code.

• No Code/Low Code: In this approach, the product configuration is created using a visual editor - typically a proprietary tool provided by the PAS vendor. This model is often considered to be more user-friendly, allowing business users to modify it without engaging specialized technical teams for every change. In such environments, the configuration is usually inseparable from the PAS platform and can only be maintained through the platform's built-in tools. However, this approach can have limitations in the organization of the development process, such as versioning, release management, and more.

• Configuration-as-Code: This approach creates the configuration in code, including declarative definitions and scripts. This code can usually be developed using external tools, such as industry-standard IDEs and editors, and is then built into a final configuration package for deployment to the PAS. While this method requires more technical expertise and is less suited to business users' self-service, it enables the use of mature software engineering practices. These include version control and branching, automated configuration management, and continuous integration/continuous deployment (CI/CD) pipelines.

Conclusion

Mastering the complexities of Product Configuration within a Policy Administration System requires a strategic approach that balances innovation with practicality. At DataArt, we provide the expertise to guide insurance companies through these challenges, delivering high-quality, scalable solutions tailored to specific business needs.

Partnering with experts and effectively leveraging PAS capabilities ensures that insurance companies can meet current challenges and thrive in a dynamic, evolving industry.

Originally published here.