For rental property management companies, the cost of a rental turnover can be significant1. According to Lori Hammond at Property Management Minutes, “The cost of a single turn including rent loss generally starts in the range of $1,000 and can easily grow to a range of $2,500 to $5,000 depending on the capital replacements”. Comprehensive resident screening during the application process, which includes identifying tenants who are more likely to remain at a property, can generate substantial cost savings. Below, we highlight several elements of resident screening data from CoreLogic® that correlate with a tenant’s length of stay.
In a recent study, CoreLogic examined the correlation of a tenant’s length of stay with the following three data fields from their rental application screening: the applicant’s SafeRent Score™, monthly income, and age. The CoreLogic SafeRent Score is a proprietary tenant screening system that predicts the likelihood of lease default using the applicant’s credit history and rental application. Scores with a higher value (ranging from 200 - 800) indicate lower risk. This study relied on CoreLogic proprietary rental data (2010 - 2017). A tenant’s length of stay is defined as the number of months a tenant has completed as resided at a property before vacating. Because the long-stay records with move-in or move-out dates outside of the data time window could not be included, the average length of stay for the long-stay group in this study may be underestimated. Otherwise, the correlation trend shown in this study would be even more prominent.
Figure 1 shows the average length of stay for tenants with different CoreLogic SafeRent Scores. The correlation is clear; renters with higher scores stay in their lease longer. However, the length of stay dips slightly in the highest score range, as top scoring renters are likely to buy a house.
The SafeRent Score predicts the probability of rental default. A higher SafeRent Score also indicates a longer stay on average. The SafeRent Score helps property managers not only reduce the risk of lease default by improving their ability to measure the credit quality of residents, but also saves on turnover costs.
Similarly, an overall positive correlation is evident in Figure 2, which shows that as the tenant age increases, so does the average length of stay.
Figure 3 shows the correlation between the length of stay and monthly income. The increasing trend of length of stay vs. income only holds true for the income range below $6,000. The contribution to this “hump” could indicate that high-income tenants have a greater likelihood of purchasing homes and moving out, or that retirees (aged 70+), who, according to Figure 2, have longer lengths of stay, tend to be mostly in the middle-income range.
In summary, we see a clear correlation between a tenant’s length of stay and the CoreLogic SafeRent Score, age, and monthly income during screening. There is further information within the application which may show a stronger correlation with the length of stay, such as length of stay in previous addresses, employment or occupation information, family size, etc. It is possible to predict a tenant’s tendency of a longer stay at the time of completing the application screening. CoreLogic can help take the guesswork out of resident screening decisions and apply leading intelligence to help property managers successfully manage their rental property portfolios.
 see for example: http://propertymanagementminutes.com/turnover-totals-the-financial-benefit-of-reducing-moveouts/ ; http://expressrpm.com/property-management-blog/cost-tenant-turnover
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