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In the financial services industry, the life and annuity sector is riddled with a multitude of unique operational challenges. While the pandemic has introduced a new set of constraints for companies to deal with, some of these challenges have existed since their inception. One such challenge is containing and maintaining the complexity of insurance product portfolios. While today’s customers are demanding more personalization in insurance services and products, companies are finding it difficult to administer policies through legacy systems.
Moving away from legacy policy administration system in insurance to a modern, cloud-based PAS seems to be the obvious solution. But this does not make legacy problems associated with insurance legacy systems disappear with them. Underlying this shift should be a strategic move to reduce product portfolio complexity, and consequently the costs involved in dealing with this complexity in the organization. Rationalization is the true answer to reducing operational complexity, and yet not an easy one for many. Rationalization requires companies to critically evaluate their insurance product portfolios, conduct a demanding process of mining, mapping and reconfiguring old products as new, simpler ones, and stripping the complexity off an insurer’s offerings.
The problem: legacy-on-legacy
Life and annuity providers roll out new products on a constant basis due to a number of factors. But are these products really new? Sometimes, as a result of the company’s changing risk appetite, an existing offering is modified and opened to a new age bracket. At other times, a change in interest rates gives birth to another variation of an existing policy. The source of these variations can be many: differing rate structures, change in annuitization age, different riders, product names, premiums, and so on.
There seems to be only one constant in the equation, and that is variation. Insurance and annuity providers introduce a multitude of variations on a core product during its lifetime, and this is a key characteristic that defines operations in the sector.
However, when these variations are created on legacy policy administration systems in insurance, companies face a range of operational challenges that impact workforce productivity and customer experience, and ultimately lose cash for the enterprise. Here are a few examples of how these legacy systems shoulder legacy products, only to backfire onto life and annuity providers:
Too many similar products complicate business process flows.
Customers of similar products receive a different experience.
Any changes to regulatory compliance processes need to be duplicated.
Technical maintenance is not cost-effective as any technical changes will involve duplication in development and testing.
Companies need to maintain expertise for offerings that are no longer in use. In addition, legacy tech talent only adds to an organization’s liabilities in the long run.
Similar products with different plan codes make it difficult to identify those that are truly fuelling growth and others that are proving a liability. In other words, learning from your enterprise data becomes difficult.
In addition, this legacy data from insurance legacy systems can constrain modernization efforts because a mere shift to a different policy administration platform does not alleviate the challenges arising from this model. This is because migrating to a new PAS comes with a number of challenges that not only reduce the ROI on technology, but also migrate old problems onto newer platforms.
Therefore, an IT-only approach is doomed to fail from the get-go.
For life and annuity providers, the product rationalization process is like opening a can of worms. When companies take on the rationalization process, they are bound to face a number of complexities that have accumulated over the years of operations:
There are differences among products filed with regulators and those configured in the system.
There is a mismatch in the documented definition of a filed product and how operational processes define it. For example, minimum withdrawal amount as per the contract is $100 but in practice, $50 may be allowed.
Legacy policy administration systems in insurance with legacy data methods make it difficult to distinguish the profitable products from the ones that are bleeding cash. As a result, the company continues to carry the costs associated with them, in terms of technology, human resources, customer service and time.
Often, there are products with policies that have met the run-off criteria but are still impacting operational processes and customer services because standard operating procedures have not been updated. These are another source of redundant costs.
Discrepancy in business rules or process for the same product. For example, the loan default period is 30 days for one product and three months for similar products administered in another system. While products among different systems are usually not rationalized, introducing uniformity adds to operational simplicity.
Calculations are handled differently for different products. For example, in the case of daily interest calculation the total number of days taken is 366 for one product and 365 for another product. Such miniscule details must be identified, and standard rules must be introduced.
These challenges point to two major problems: First, companies operate on loose definitions of a product -- this results from a lack of common understanding of what parameters actually define a product. And second, insurance legacy systems are not able to handle these product complexities inherently and will make entire IT ecosystems complex as a whole, whereas modern insurance IT ecosystems tend to the keep the core systems as simple and easy to maintain, leading to scalability, standardization, and solving some of the challenges unique to this domain.
The solution - decode, rationalize, modernize
To modernize their existing products and introduce personalization in insurance, insurers must invest in understanding their products first. This translates to a critical review of processes and resources that define a plan in the legacy worldview. In other words, every policy must be identified as a constituent of its defining parameters. Since plan codes help insurers tackle simple variations of parameters such as charges and calculations, or issue parameters such as age and distributors, mapping these plans to these parameters is critical to moving towards a simplified and agile portfolio. This process also helps unearth mounds of grey data arising from inactive policies, closed plans, and so on. It is at this stage that companies begin to see the various redundancies and similarities among product components.
Once the mapping has been completed, the plans and policies must be rationalized to achieve a lean and configurable portfolio of products, which can be administered over a single modern policy administration system. The rationalizing process involves clustering similar products with small variations and configuring them as a base product in the target system. The rationalization process has two stages: product alignment and system migration.
During product alignment, companies must build their target offerings with flexible, lean and customizable base products, over which variations can be introduced. Partnering with a capable technology leader, insurers can explore a number of modernization options that align their product offerings with business KPIs. In rationalizing, a number of parameters are considered -- product names, versions, riders, fee variations, state tax rules, M&E changes, etc. -- that are mapped by variations on the base product. The rationalization process is usually applied within one legacy system.
During migration, the rationalized product features and attributes are then mapped to the legacy product. Then rates and calculations are configured to ensure that the legacy product data is used for business processing.
Modernizing insurance products is critical for insurers in today’s digital economy, which is riddled with operational constraints such as mobility restrictions and workforce unavailability. While an IT-only approach can help solve these challenges, the impact of rationalizing, and consequently modernizing your portfolio can be tracked across the value chain, from cost of administration, to stakeholder experience of the value chain, from agility to simplicity -- not to mention increased speed of delivery and better customer experience. More specifically, product rationalization can bring about a major impact. Here is how:
Rationalization of the portfolio can provide insights into the existing products and opportunities to introduce new products that align better with the demand of today’s customer.
It creates an opportunity to glean new insights into customer preferences while exposing errors in the existing stream of operations.
Lesser number of products means maintenance is simple and cost-effective. Additionally, rationalization brings the possibility of standardization, and helps introduce new products to the market 30% faster. Beyond new products, this can also help in keeping up with the changing ecosystem variables, such as rate changes.
It helps with the implementation of archival strategy, which can reduce maintenance costs associated with managing myriads of product and policy data.
Improved compliance with regulations, which in turn reduces the cost of negative visibility and implicitly increases brand quality.
Lastly, rationalization also reduces IT and personnel costs. This is because legacy PAS run on outdated technology stacks, where expertise is becoming rarer and costlier.