Survival Analysis: What It is, How It Works, Pros and Cons

Survival analysis, often known as time-to-event analysis, is a field of statistics that investigates how long it takes for an event of interest to occur.

Insurance firms use survival analysis to forecast the insured's mortality and estimate other key aspects such as policy cancellations, non-renewals, and the time it takes to file a claim. The results of such assessments can assist providers in calculating insurance rates as well as client lifetime value.

Understanding Survival Analysis

Survival analysis is mostly used in medical and scientific sciences to analyze rates of death, organ failure, and the start of various diseases. Perhaps this is why many people link survival analysis with bad things. It can, however, apply to positive events as well, such as how long it might take someone to win the lotto if they play it every week. 

Survival analysis has been applied to the biotechnology sector throughout time and is now utilized in economics, marketing, machine maintenance, engineering, and other sectors in addition to insurance. The hazard rate is used in the study to calculate the odds or chances of an item or system failing based on the period of time the item or system has been in use.

Insurance

Survival analysis is used by analysts at life insurance companies to estimate the likelihood of mortality at certain ages given particular health conditions. Calculating the likelihood that policyholders will outlive their life insurance coverage is quite simple using these functions. Providers can then compute an appropriate insurance premium, or the amount charged to each client for protection, by factoring in the value of prospective customer payouts under the policy.

Survival analysis is also used extensively in the insurance business. For example, it may aid in estimating how long it will take drivers from a specific zip code to be involved in a vehicle accident, depending not just on their location, but also on their age, the type of insurance they have, and how long it has been since they last submitted a claim.

Advantages and Disadvantages of Survival Analysis

Other, more frequent statistical methods may give some light on how long something may take to occur. Regression analysis, for example, which is often used to assess how certain factors such as commodity prices or interest rates influence the price movement of an asset, may assist forecast survival durations and is a simple computation.

The issue is that linear regression frequently employs both positive and negative numbers, whereas survival analysis is concerned with time, which is always positive. More crucially, linear regression cannot account for censoring, which means survival data that is incomplete for a variety of reasons. This is especially true of right-censoring, or subjects who have not yet experienced the expected event during the time period under study.

The fundamental advantage of survival analysis is that it can better address the issue of censoring because its key variable, other than time, addresses whether or not the intended event occurred. As a result, it is possibly the technique best suited to solving time-to-event queries in a variety of businesses and professions.