According to a report published by EY, real estate firms are now realizing they need to shift to the changing technology landscape to stay relevant and gain an edge on their competitiveness. With the increasing demand for tech-enabled real estate platforms, some trends like the use of AI, machine learning, and RPA can witness significant momentum in 2021. Such technologies enable a systematic and comprehensive evaluation of a large spectrum of properties in real-time.
AI has significantly optimized the decision-making process with regard to asset identification and selection. AI platforms use algorithms and machine learning to process big-data sets to identify correlations, patterns, and relationships across a broad spectrum of parameters and variables. By identifying such variables and evaluating their impact on multi-scenario probabilistic models, the asset selection process over time has evolved from subjective evaluation to deterministic and quantifiable in nature. Well-designed AI algorithms constantly test the feasibility and impact of different parameters – this can often result in significant insight triggering a “butterfly effect“. The butterfly effect is the idea that small changes can have non-linear unpredictable impacts on a complex system. AI can also help in the prediction of any safety hazard or construction defects saving time and money.
AI helps in property valuation that is it can determine the rates of the property with the use of a “predictive analysis” algorithm. Predictive analytic algorithms evaluate the probability of occurrence relevant events:
- changes in a demographic pattern of the micro-market;
- income distribution of individuals in the vicinity;
- projection/viability of future competitive supply;
- amongst many others.
This aids in determining the true intrinsic value of a property. Often markets tend to not align with an intrinsic value which provides a compelling opportunity to identify assets via such algorithms that have a higher intrinsic value than the prevailing market rates.
Robotic Process Automation
It refers to the use of software or bots, to automate regular clerical jobs at the site, which do not need high-level decision-making. For example, regulating contracts and coordinating signatures and approvals amongst multiple vendors. Other frequent clerical duties that can be automated with the use of bots include data gathering on buyers and sellers, data maintenance, and data compliance reporting.
It is a more cost-effective option. Companies that have implemented RPA have witnessed a 10% to 40% reduction in operational costs. RPA allows an employee to focus on higher-value duties, such as interacting directly with potential buyers and sellers. This enhances the likelihood of more deals being closed, resulting in a direct contribution to a company’s revenue. It significantly reduces the chance of human error, resulting in more dependable results. As a result, data compliance becomes simple.