User Performance Rating System at PlaceToRent and the Power of Data

To improve experience on our platform and provide our users with more usable and reliable data to aid in more efficient and smarter decision making, PlaceToRent will utilize a rating system calculating the relative performance level of its users, akin to social credit score. We anticipate that our user performance/reputation rating system will become an official recognition of all the data on the PlaceToRent users collected and circulating and will impact them in a multitude of ways. Anything that influences our users points will be backed by official documents and immutable transactions recorded on the blockchain.

The platform will enable tenants, landlords, and third-party providers to rate each other by submitting reviews for each transaction, an immutable and verifiable record of which will be stored in the applicable user’s profile. These reviews will be processed and analyzed by our unique algorithms powered by Artificial Intelligence (AI) technology to calculate performance ratings based on multiple criteria, which will then be appended to the applicable user’s profile.

The criteria will be custom-tailored to each specific user category and will receive an input from every corresponding transaction recorded on the blockchain, as well as standard criteria like FICO scores, employment history, etc. For example, in the landlord category, data such as security deposit disputes, maintenance/repairs performance, building safety upkeep, and tenant eviction cases, among others, will be collected and analyzed. For tenants, the evaluating criteria will include such data points as their payment/nonpayment history, property rules compliance (noise, animals, after-hours activity, etc.), property damage claims, eviction history, schools attended, area of study, academic performance/GPA, standardized test scores, work history, and other relevant information. Third-party providers will be evaluated for their job performance, timeliness, any disputes and their resolutions.

Each user’s relative performance level will be calculated and assigned a score representing the quality of potential risk. The higher the score, the less the risk, and vice versa. Our performance rating system will enable users to connect through the power of these holistic peer evaluations, build community, facilitate more tailored interactions with each other, add knowledge to our user groups, identify unfair users, and elevate the accountability of those who are being rated.

PlaceToRent will strive to engineer responsible social behavior of our users on the platform with AI and data. How we negotiate our social conduct in society will be directly proportionate to these new kinds of credit scores that will brand not only in our access to services and privileges, but in the social contracts we embark on with society at large.