How Data-Driven AI Is Transforming Risk Management for Multifamily Operators


With the onset of the pandemic, the usually innovation-averse multifamily industry was forced to embrace new technologies. Today, those automations and technology platforms are becoming the standard in property management.

While artificial intelligence (AI) remained at the tail end of technology implementation, the industry is finally realizing its potential roles in improving leasing, operations, and property performance. Below, our in-house technology and engineering expert explains the foundation of AI, its impact on risk management, common misconceptions, data challenges, and integrated solutions.

Interview With Multifamily Engineering Executive: 4 Takeaways to Unleash the Power of AI Risk Management

With two decades building software solutions and creating and scaling cloud-based statistical analysis system (SAS) solutions in the multifamily space, our chief technology officer Sudip Shekhawat is no stranger to innovation.

“AI goes back well beyond 20-25 years, when all we knew about AI came from ‘The Terminator’. We really just didn’t exactly know how to use it. To me, ‘augmented intelligence’ sums it up better. That says that anything you can do as a human being we can augment the intelligence positions through machine learning and machine processes.”

While twenty years ago artificial intelligence was out of reach for many operators, today it’s a necessity, offering tools to streamline business operations and accelerate growth. Shekhawat dispels some common misconceptions about AI technology and discusses the main challenges and opportunities ahead:

1. Data Is the Foundation of AI & Machine Learning

Thanks to self-driving vehicles and the widespread use of chatbots, most people now have a basic idea of how the technology works. However, AI is still often confused with analytics applications, or misunderstood as technology that is too complex and out of reach. Shekhawat reminds us that AI is all about data.


“It’s critical to remember that without data, there is no AI. The recording of data and the access to those recordings, as well as the digitization of more processes helps us to build AI and enhance machine learning. We are sitting on this wealth of data supplied by property management systems. There is an immense amount of untapped potential in that data.”

2. Data-Driven AI Is Transforming Risk Management

AI gained its first foothold in multifamily in leasing and marketing, but the opportunities to optimize operations through AI go much further.“There has been a lot of focus on using AI for human interactions in the leasing offices and organizationally, with chatbots, as well as lead generation and lead management,” Shekhawat explained.

“It’s making more inroads to creating better customer experiences, increasing operating efficiencies and improving decision making. With better decision-making, we can optimize asset performance and better manage risk. That’s where I think AI is going, taking on risk management.”

Shekhawat believes that through the use of AI in fintech and insurtech platforms, multifamily companies can make more accurate forecasts for their assets. When AI has access to the data and analytics, machine learning can drastically improve the process of underwriting, asset insurance and claims.

“The application for AI in insurtech has been developing a faster claims process and quicker fraud detection,” Shekhawat said. “Those are two areas where other industries have seen great success with AI.”

3. Multifamily Data Protection Challenges


While AI has the potential to continually improve property performance, the increasing data volume can create challenges for the industry in terms of data storage and protection. Shekhawat illustrates this concept with a good example.

“Virtually all property management is through software right now. Each transaction, each event is being recorded somewhere and generating a data point. Each day, we get exponentially more data points. With so much data, the challenge is how to store and access the data securely.”

Increasing data volume can slow down data analysis and make it difficult to determine which data points to prioritize. Operators are strategically deploying AI to run multiple scenarios, significantly streamlining the process to identify the most optimal business approaches.


“AI enables you to make decisions faster because you’re not looking at the data on a granular level. You’re not just looking at raw data over a set period of time. AI should save time and impact the bottom line. It should continue optimizing and improving asset value.”

4. Overcoming Data Gaps Through Fully Integrated Solutions

When it comes to integrations and the ability to overcome data gaps, it’s important to select the right AI supplier/partner who can bridge the gap.


“Do they have sound and seamless integrations, or is that going to take time to develop? Are they aligned with your organization’s long-term focus? These are questions that must be answered. Suppliers must be data driven, think data first, and be a data organization. As suppliers, we have the responsibility of solving for missing data points.”

Moving forward, multifamily must seek out opportunities in the lease lifecycle that are optimizable through AI. It is imperative to look outside the industry for potential solutions and partnerships. Most importantly, organizations need the right processes and people in place to collect and record the important data required to effectively derive the benefits of AI.

“Fifteen years back, somebody said, ‘Data is the new oil.’ They were so right. Now, what you do with the data is the new oil. Data and AI technology will enable firms to make more informed decisions, but I think AI is still in its infancy in multifamily. We have a lot of runway yet to be covered.”

To get full insights from the industry analytics and business intelligence veteran, read the full article here.

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