A relationship manager at a bank called to tell me his client asked him if he should be paying the loan interest on his life insurance policy. Good question, but where does one start? I too often witness agents, advisors and policy owners go with a gut feeling rather than perform even a simple empirical analysis of the situation. Here is how I approached this.
Admittedly, this is a very simplistic situation but this is exactly why I am choosing it. The process for approaching everyday simple queries and complex questions relative to life insurance can follow a very similar roadmap. Clearly some scenarios will require additional resources and higher level analytics, but most any question can and should be boiled down to a set of empirical facts which can be objectively analyzed resulting in informed decisions rather than knee-jerk decisions guided by emotion or conventional wisdom.
After procuring authorizations from the policy owner, my team ordered multiple in-force ledgers from the insurance carrier so we had data to crunch. Many times, loans are so big they need to be paid back in order for the policy to survive. Other times, the loan interest needs to be paid lest the loan grow out of control and kill the policy. In this situation the loan was so modest and the policy so well funded that even if the loan interest was never paid and accumulated for the balance of the insured’s life, the policy would be fine.
The quick answer is, no, he doesn’t have to pay back the loan or pay loan interest. The next question is, should he? To answer that question, we simply focused on two ledgers, the one assuming loan interest being paid and the one assuming loan interest accruing. Clearly the one paying loan interest would result in a higher death benefit, but what about the internal rate of return (IRR) on the transaction, which I argue defines “better” in this case? We simply isolated the spread between death benefit on each ledger at multiple year durations and used this at “Future Value”. We input the annual loan interest as “Payment” and calculated for IRR over various intervals. What we found is that at any point during the transaction, the IRR on loan interest payments to increased death benefit was 6.51% net.
Once again, I chose a ridiculously simple example which involves very simple analytics but the sad point is, this is rocket science compared to the “analysis” I usually see in the market. Systematic number crunching of complex insurance portfolios incorporated into sophisticated business and estate planning can end up with the same result, namely, giving the client and advisor team black and white data on which to make informed decisions. I can hardly count the number of times that the results of an empirical analysis of the facts, if completed earlier in the life of the transaction, would have lead the decision makers to go in a substantively different direction.
In this case, the client thought this was a good use of money given his cash flow, his goals and alternate uses of money so he began paying it.