In another flurry of bad press for the insurance industry, multiple state probes have found life insurance companies with significant unpaid benefits. In New York alone, life insurance companies owed more than 32,000 beneficiaries over $262 million. Leading life insurance companies have been fined tens of millions of dollars.
More worrisome than the fines are the potential impacts on the industry, itself. The number of US households without life insurance coverage is at a 50-year high (LIMRA). Ownership is declining among consumers under the age of 45, and one of the top reasons cited is a lack of trust in financial institutions. This group is reluctant to purchase life insurance because they do not trust that the company will pay the benefit.
A matter of good business, but how?
New regulations in four states require insurance companies to review Social Security Death Master Files (DMF) more regularly. In light of current publicity and perceptions, insurers should consider supporting these regulations across their book of business.
Supporting these regulations requires a simple way to:
- Apply Social Security information across multiple policy administration systems
- Identify unpaid beneficiaries and addresses/contact information
- Communicate with beneficiaries and track distribution of proactive communications
- Weave integrity into marketing materials and agent communications
There are three fundamental strategies for addressing this reconciliation; the right one depends on the scope of the problem in your organization and your capabilities. Let’s look at each in more detail.
Manual Process. In this scenario, reconciliation requires direct user interaction. A person manually retrieves Social Security updates and cross-references them to names or Social Security numbers in the policy administration system using a spreadsheet. From here, the process uses existing system capabilities to initiate benefit payout for each policy.
This approach does not scale well, but if it’s only performed a few times a year or labor costs are low, this may be an acceptable approach—especially where there is a single policy administration system. As the number of policy administration systems and/or policies grows, the time required for this strategy increases drastically and, at some point, one of the other two strategies may be more appropriate.
Semi-automated Reconciliation. This solution relies on basic automated processing to retrieve Social Security notification lists and cross reference policy information in the pertinent administration systems automatically. The result is a filtered list of policies that are strong or exact matches and that require further processing to be performed through existing policy administration capabilities. This type of solution does not need to be technically sophisticated to be extremely useful. It removes the manual reconciliation process, allowing human workflow to focus on validating and processing death benefits. This solution can be enhanced over time through additional automated steps, and it can be particularly useful when working with legacy administration systems that do not have readily available APIs or fully embrace the concept of user work queues.
Fully Automated. This solution combines the previously described automation capability with complete integration with policy administrations system(s), likely with a robust business rules-based validation component that replaces the manual validation steps in order to ensure compliance with policy terms and conditions. Furthermore, it can initiate communication with beneficiaries through a variety of channels and provide tracking, visibility, and reporting to management that reflects the status of each policy in the process. This solution has the highest upfront cost but the lowest ongoing cost.
Regardless of your scope, size, or budget, the first step in defining the right solution is to analyze the processes and systems that will facilitate the reconciliation procedure. This analysis allows a full understanding of the scope of your organization’s issue and helps you determine the appropriate resolution strategy. Often the best approach is an iterative one that eliminates manual steps along the way. This allows the overall solution to emerge from what is actually working and produce benefits today rather than relying on lengthy upfront analysis.
Again, the right strategy is unique to your operations and normally is dependent upon the following variables:
- Number of policies (and their growth rates)
- Number of administration systems housing these policies
- Number of staff available to develop and maintain the solution, both for policy administration and technology development