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Tenant screening

Introduction

The property industry is one of the many industries that have been greatly affected by the advancement of technology especially the use of machine learning (ML) and artificial intelligence (AI). Over the last few years, these technologies have been applied to the tenant screening, which is an important element of property management. Tenant screening is a procedure that entails evaluating candidates for tenancy for certain risks that may include non-payment of rent, damage to property among others. This has usually been a manual and thus very time consuming process and hence there is potential for these technologies to enhance the efficiency of the process. This paper will discuss the problems of the property industry in tenant screening, how the AI solutions can help these challenges, the advantages of these solutions and the ROI as well. It will also provide real-life scenarios of how ML and AI are being used in tenant screening to enhance the decision-making process.

Challenges

There are many challenges that are encountered in the property industry when it comes to tenant screening. First, the conventional ways of conducting tenant screening are that the data has to be collected and analyzed manually and this process is rather time consuming. This not only hampers the efficiency of the tenant acquisition process but also enhances the overall expense of the operation. Second, such processes are prone to errors as they are handled by humans, thus there could be a chance of ignoring some vital details or evaluating the matter incorrectly. Third, discrimination is also a big concern in tenant screening. The landlords and property managers may incline towards discriminating the potential tenants based on their personal prejudices. Fourth, there are concerns of privacy since the applicants’ personal information is dealt with during the process. Finally, it is hard to determine the rent paying potential of a tenant in the future due to the dynamic nature of the economy.

AI Solutions

These problems can be solved with the help of ML and AI. The use of AI algorithms can help to streamline the process of tenant screening, thus decreasing the time and effort needed. These algorithms are capable of processing large sets of data within a short time and with a high level of precision, thus minimizing the possibility of errors that are often associated with human beings. Discrimination can also be minimized as the AI models can be developed in a way that they do not consider aspects such as race, religion or gender, only the financial situation and the history of rentals of the applicant. In the same manner, AI can improve privacy protection since data handling is automated and access to sensitive information is limited to humans. Predictive analytics, which is a part of the sophisticated AI systems, can also go further and break down an applicant’s financial information to determine their potential to pay rent. For instance, Rentberry is a real estate tech company that applies AI to improve the rental application and screening processes and, thus, makes them more efficient and straightforward.

Benefits

There are many advantages of integrating AI and ML in tenant screening. First, it increases efficiency by streamlining certain aspects that would otherwise require a lot of time and effort, thus increasing the speed of tenant acquisition and decreasing the costs of operation. Second, it enhances the accuracy and the consistency of the evaluation of the potential tenants thus minimizing the chances of admitting a defaulting tenant or one who will cause damage to the property. Third, it also helps in reducing discrimination as it is based on the quantifiable factors. Fourth, it also helps in enhancing privacy as only certain people can have access to certain information. Lastly, through predictive analytics, it improves financial security since it can reliably estimate a potential tenant’s rent payment capacity in the future.

Return on Investment

It is possible to realize a high ROI when implementing AI and ML in tenant screening. This is because with efficient and accurate tenant screening methods, property managers are able to minimize vacant units and turnover costs hence improving their rental revenues. It also reduces the operational costs which in turn translates to higher ROI. Also, by minimizing the likelihood of default or property damage, AI can enable property managers to prevent huge losses. For example, MyRental, an AI-based tenant screening solution state that their service has helped property managers save $2,200 per eviction on average.

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