Artificial Intelligence Multifamily

From downturn to upside: using AI to help retain renters

First off, a little bad news. 

According to Freddie Mac’s multifamily Midyear outlook, apartment rental growth is slowing across the country while vacancies are on the rise.

In the report, Freddie Mac speculates that apartments could weather a 9% drop in collections before they breach any covenant headroom on DSCR (that’s assuming 1.25x). 

Okay, that’s not so bad. 

What’s more, falling interest rates are creating a double whammy on both higher cashflows (through lower debt payments) as well as tighter cap rates on real estate.

But this begs the question: in this market, with a wildly uncertain future, does retaining customers even make sense? 

Absolutely, for these three reasons.

(1) Applicant credit quality: In previous recessions (take 2008 for example), consumer credit quality was massively impacted. In fact, FICO data shows that consumers with higher scores saw their scores drop for up to five years after the recession. So it pays to keep heads in beds.

(II)Concessions on new leases: These are only going to rise as we’ve already seen in Q2 due to poor demand and oversupply.

(III) Turn costs: With new amenities (e.g. smarthomes) and increased sanitisation, “turning” a unit will require both a higher capital expenditure and time than in years past.

Current Residents - Renew Your Lease by September 30th! — College Station  Apartments | Student Apartments in Normal, IL

With a recession in mind, Beekin developed Leasemax.

Utilizing a multivariate model, Leasemax allows apartment operators to accurately predict who will stay, and helps retain your best customers at the right price.

Over the past 6 months, in the midst of the COVID-19 crisis, Leasemax has picked longer-staying renters – and retained them!

Check out these results for yourself:

Expected Beekin renewal probability band% of residents who actually renewed No. of happy residents
Retention Study: How 1,000 leases performed in the midst of the COVID-19 outbreak. NB: The 75% renewals in the 0-19% band are statistically skewed by only 4 leases.
Cartoon Move House Stock Illustrations – 1,139 Cartoon Move House Stock  Illustrations, Vectors & Clipart - Dreamstime

As with all machine learning approaches, stability and objectivity matter.

That’s why our data science team spent time ensuring that our model didn’t violate fair housing. That meant eliminating variables which were considered “protected class.” Of course, when we did this, a fair amount of our model accuracy was lost. Maybe having kids does make people move, we’ll never know!

To recoup some of this accuracy loss, our team feature-engineered variables while augmenting the datasets with internal data that was purchased, curated and normalised. This included neighborhood, mobility, and demographic data across thousands of neighborhoods in the US. 

The Beekin datastore, painstakingly constructed over the past 18 months, began to deliver big results, with our feature-engineered model performing flawlessly across MSAs!

Play offense – or defense.

Think of Leasemax as the ultimate data strategy play. It’s built to optimise pricing by overlaying strategies, much like stock market strategies.

Or for fans of Moneyball, we empower data to help transform you from a regular “scout” to a pennant-winning, come-from-behind underdog. In fact, our resident node which predicts whether a resident will stay or pay, is codenamed “Billy” for that very reason!

Get closer than ever to your customers. So close, in fact, that you tell them what they need, well before they realize it themselves.

Steve Jobs

Use Leasemax to find the perfect customer for your assets. It’s a natural win-win for landlord and resident, alike. Thanks for reading.

To learn more about what Beekin can do for you, we invite you to reach out personally at for a free portfolio analysis. 

Artificial Intelligence Leadership Multifamily

Leaders in Asset Management: Ralph Pickett

Bio: Ralph Pickett is the former founding President and CEO of LivCor, backed by The Blackstone Group. LivCor currently owns 80,000+ apartments in the US. Prior to LivCor, Ralph was an SVP at Aimco (NYSE: AIV). Ralph is currently CEO of Graphite Multifamily consulting.

Beekin: Ralph thank you very much for being here, let’s jump right in. We’ve seen a lot of investment dollars flowing into workforce housing. Based on your experience, what are three of the biggest challenges that you’ve seen in managing workforce housing communities?

Ralph: Yeah I think there’s 3 big ones. Workforce housing and regular market rate housing are pretty similar with these [salient] exceptions.

One, resident income stability is a little more challenging, so you tend to see more skipping and evict situations, residents requesting some sort of work-out for their rentals or their financial situation to try to make it to the next month, so you tend to have to manage through that quite a bit more. 

Number two, this is these folks’ homes and they tend to have a lot more stability, which is nice in terms of retention. But the people living there also tend not to complain. They just want to not bother the operator. You tend to see less reporting of maintenance issues, leaks and leaky toilets and things like that that can create cost issues or bigger maintenance issues down the road. And your chance of getting in that unit because the retention is higher, you’re in there less frequently, your service team is in there less frequently, so it’s harder to catch these issues early.

And then the last and probably the most challenging aspect of it is the capital need for capital investment to maintain an asset, the opportunity for ROI on capital investment that you get in a B plus, A minus or better asset. Where you really have an opportunity to push the rate. Rental rate doesn’t really exist in workforce type housing as much, so you’ve really got to figure out how to balance that need for maintaining the asset with capital investment to get some kind of return around the capital you’re putting in.

Beekin: Great. Moving on to a different kind of theme that we’re seeing now because of the COVID situation, what are your views on possible conversion of hotels to apartments? Is this a successful turnaround strategy that some companies can implement?

Ralph: Well, I’d say it’s probably too early to make that call. That would imply a structural change versus a cyclical one.

However, if you’ve got an asset, a hotel or a motel asset, that was underperforming pre-COVID, then it’s certainly not going to all of a sudden pick up going forward.

On Hotels to Apartment Turnarounds

I think the fact that you’re not getting any, you’re not really having to give up any revenue. I mean, that’s always a challenge of conversion as you’ve got to shut down the existing operation and move on in the renovation without any income. Currently, in this COVID situation, there is no income anyway. 

As we’ve seen in prior cycles with conversions of old warehouses and downtown spaces and things like that, and old sort of obsolete office space, we saw a lot of that conversion and some motel conversions from previous iterations. I think that again, there is an opportunity for underperforming hotels right now to make a move like that. And if this gets to be a long-term structural issue for hotels, then that is another opportunity they could look at for conversion.

Beekin: Going along with what is going on right now, some people are calling it the COVID crisis. What are some of the similarities that you have seen now and back in ‘07 and ‘08 when the financial crisis hit?

Ralph: Yeah, it’s an interesting one. I think the bigger similarities I see is really COVID being sort of an extended version of the 9/11 situation. However, you know, similarities to 2008 in a way; I think it really forced companies to adapt and look at everything they were doing and get more efficient. It was just a very lean time.

So, you really had to kind of dig deep and look at your organizational structure, how you could get more efficient on site, things like that. I think the COVID situation is forcing companies to adapt as well.

But what I see here is sort of an acceleration to forced acceleration to adopting technology that enables a more touchless experience for both the onsite team through E-deposits, and virtual leasing too with virtual tours, self-guided tours, etc. Then E-leasing at the end of it so that people can sign their lease remotely. These have been in the industry for a decade now, but the adoption of has been pretty slow outside of a handful of REITs.

On COVID and PropTech

And I think this has obviously forced that and forced people to really look at whether a lot of these preconceived notions of people liking to have a leasing agent tour them around; or go see a model. In reality, when you do surveys, you realise that people like to do their own tours, they do not really want to see the model, they want to see their own unit. [COVID is making this a reality]

So these sorts of things, this COVID situation I think is forcing the acceleration of the adoption of some of these technologies to enable this touchless experience.They have existed for nearly a decade pre-COVID, but the pandemic is forcing efficiency and re-evaluation of status quo in many ways.

Beekin: It’s interesting that you mentioned technology. When you look at FinTech and banks, LegaTech and law firms, it has disrupted those sectors. And now with PropTech , what other ways can you see technology changing this industry going forward?

Ralph: Yeah, I think there are a number of opportunities and you mentioned them. I think sustainability technology with solar, for instance, is a lot more efficient. I really think probably from a technological standpoint, the biggest opportunity is in the space you guys (Beekin) are playing in revenue management, big data, bringing that all to bear on the way you test and push revenue.

I think that the revenue management systems out there, while good, have been in place pretty much in their early form for well over 10 years now and really are ripe for innovation.

I think that is probably where the biggest opportunity lies.

On Big Data and Revenue Management

Other than that, from an operator standpoint, I think it is largely about blocking and tackling and doing what they’re already doing better. While we’re upgrading a lot of units and giving residents control of their thermostats and things that are going on their unit and being able to see who’s coming and going and those sorts of things, and those are all nice, but in terms of really driving revenue, obviously 90 percent of revenue is on the rental side and revenue management, perfecting or improving revenue management, is really going to be your biggest opportunity there.

Beekin: And just to be clear, when you say perfecting revenue management, you mean screening better residents, reducing turnover, having clear insight in terms of rent increases and offers to give to tenants, is there something that I missed?

Ralph: It’s all of the above, yes, I think, again, the Big Data concept bringing that to bear on the revenue management matrix is a big opportunity for all those reasons you mentioned, on renewals, on prospects, you name it.

Beekin: Ok, great. And since we are on the theme of revenues, owners are looking to increase ancillary revenues to improve their bottom line, do you see any opportunities for this for multi-family?

Ralph: Yeah this is where I go back to again. This is the blocking and tackling. I mean, operators have been adding bells and whistles here and trying to pile on different ancillary opportunities. I really think the focus should be on the right now, on primarily the ones that are in place.

Going through and reviewing your RUBS (ratio utility billing system) program, and making sure that’s being effectively implemented and optimized is a huge opportunity we’ve found.

Parking programs, revenue share opportunities that might be converted to internalized fees such as insurance captive, big upside there. Another one that tends to get overlooked are the basic fees that properties charge for applications, for late fees, whatever it may be.

Some operators let that stay at or have that decision made at the property,  so you tend to see a lot of fees getting waived or not being implemented consistently and centralizing those decisions or controlling the decisions around fees and making waiver of fees (an exception that needs to get elevated) can really impact your ancillary revenue pretty significantly.

Then the other area I think that isn’t really on the revenue line item as much, but can help on your bottom line impact are the E.V. (electric vehicle) programs, E.V. Rentals, Solar EDI’s (being electric vehicle charging solar programs particularly) and LED retrofits, which may not really drive a benefit to your revenue side, but will in the long term help your NOI.

Beekin: Ok, it seems to be a point to have a consistent approach whenever you try to do ancillary revenue, like you mentioned with the fees, applying it consistently. The follow up question would be, do you ever feel like certain owners go a little bit too overboard, maybe with what you said, “the bells and whistles” that they may offer?

Ralph: Yeah, it’s funny. I think trying to do too many things is the recipe for getting nothing done. And I think I’ve done that myself, trying to get too many things done at once and not really getting anything accomplished effectively.

So, figure out where are your biggest opportunities are and execute those extremely well first before just adding a whole laundry list of initiatives and bells and whistles type things that may not drive revenue. They may not really be that important to the residents, and could be a big distraction to your team.

Beekin: Lastly, more of an personal question. In your experience, what has been your favorite community which you’ve invested in or lived in and why?

Ralph: Well, which one am I going to pick? Okay, well you know, the first one, I hated this place, it was my first investment of any scale in multi-family. I bought it with a couple of partners, bought a deal down in Texas that just crushed us. It was awful.

But I’d say that’s my favorite community, because in the long run, I learned a ton out of that. I mean, it was an expensive experience, but it was extremely valuable in so many ways.

One, making sure you know what you are buying. Looking around for location matters. Being able to get to it or get an employee out to it easily and quickly, to put some eyes on it or to jump in, in an emergency situation and be there, is very important. For example, I was living in California at the time, so getting to Texas was not going to be easy.

Scale matters.The asset was only 70 units; it was two little buildings. So how do you staff that efficiently? How do you put technology in place in a small property like that and allocate those fixed costs over such a small property?

On his favourite multifamily investment and what not to buy

What is the municipal and governmental regulations and behavior towards that asset class? This asset was in an area of Texas, a city in Texas that was known to be extremely difficult to new buyers of apartment buildings. They came through and tagged us for missing light bulbs and 800 violations; we thought they were going to bulldoze the place which is what they wanted to do for an expansion of their roadway. So just understanding some of those dynamics internally was important.

So, again, while I would say at the time and for years after I hated that property, it really taught me a ton. So, I would put that in my favorite category in the long run.

Beekin: Would you go back to Texas now to invest?

Ralph: I have been, with two companies that were invested in Texas pretty heavily and even in that one city that we were in and it just gave me awareness of what they’re like and how to navigate them more effectively.

So in the end it worked out in a lot of ways, that’s the only reason that thing could make it onto my favorite list.

Beekin: Ok, great. Anything else you wanted to say to wrap this up to all our viewers on multi-family?

Ralph: I still think it’s the best asset class out there right now; probably that and Industrial given where we’re at. People still need a place to live.

That’s one of those things you can’t outsource, and you can’t skip the components of a supply chain or distribution like you might be able to going around Retail. It’s here to stay. I think there is a real shortage of it, so I think it’s a great place to be from an investor standpoint.

On Multifamily as an Asset Class

Beekin: Ok. Well, thank you, Ralph. Appreciate your responses and your insight. It was a pleasure having you on.

William Marin conducted the Interview on behalf of Beekin. William is a former senior consultant at Deloitte, and an MBA at The University of Chicago, where he is a Toigo fellow.

Artificial Intelligence Multifamily

Residential REITs: Ready to Bounce?

TLDR: REITs that own apartments, single family homes and manufactured homes have seen drops in prices in the wake of COVID-19. Data shows that they will bounce back.

Over the past few months, REITs have been impacted by adverse economic circumstances. However, not all sectors have been impacted in the same manner, nor are expected to perform similarly in the future. Overall, REITs have shown signs of bouncing back, with apartment REITs performing especially well compared to other sectors.

Fundamental performance drivers – ability to collect rent 

NAREIT conducted a rent collection survey of listed equity REITs which own and operate c. 10% – 20% of US commercial real estate . The results indicated an improvement in rent collection with collections for apartments moving from 93% (May) to 97% (June) vs. Shopping centers from 49% (May) May to 60% (June) . Free standing retail improved from 70% in May to 79% in June. Some of these are slated to change as “second waves” of COVID-19 emerge, or not. 

Macro-economic factors and money supply

Looking back in time over 1994 to 2019, we can understand patterns in performance through periods of economic uncertainty and credit expansion. From 1994 to 2019, we have seen stability in apartment REIT dividend returns as highlighted by the standard deviation of these returns which is lower than other sectors.  This is correlated with the beta of these sectors where only healthcare had a lower beta as of November 2019. Beta measures the standard deviation of the returns as measured against a benchmark (risk free interest rate in this instance). A higher beta implies more volatile dividends, which real estate investors don’t like.

SectorMedian 15-year dividend return (%)(+/-) Standard Deviation (%)Beta
Residential (1)5.362.19.48
Dividends across REITs look fairly healthy, with residential showing the lowest volatility (1) Includes apartments, single family homes, manufactured housing

But what can we expect for the future of apartment REITs? If the past is any indication of the future, then based on previous performance of apartment REITs post economic crisis as interest rates rose and the economy recovered from adverse circumstances, such as the dot-com crash/terrorist attacks of 2001-2002 and the global recession of 2007-2008, we can expect price returns to grow strongly in the next few years. 

According to research conducted by S&P Global, this is because:

  1. Rising interest rates are often associated with economic growth and rising inflation, both of which tend to be positive for real estate investments. 
    1. A strong economy usually signals greater demand for real estate and higher occupancy rates, supporting growth in REIT earnings, cash flow, and dividends. 
  2. During periods of inflation, real estate owners have the capacity to increase rents, and REIT dividend growth has historically exceeded the rate of inflation as a result as can be seen from the chart below 
  3. The chart below highlights the positive correlation from 2002 – 2004 and 2008 – 2013 between REITs and interest rates

The price return for apartment REITS for 2002 was -13%, but then rebounded in 2003 and 2004 with price returns of 17% and 26% respectively. Congruently, GDP growth rate increased from 2.86% in 2003 to 3.8% in 2004 and interest rates rose from 4% in January 2003 to 4.3% in December 2004. Similarly, after producing a negative price return of -29% in 2008, apartment REITs produced a return of 22% in 2009 and 41% in 2010 once the housing market began resurging from the recession as the GDP growth rate increased from -2.54% in 2009 to 2.56% in 2010 and interest rates increased from 2.46% in January 2009 to 3.3% in December 2010.

If we extrapolate from these times to predict movements for 2021 and beyond, it seems likely that positive price returns for apartment REITS will return as COVID wears down, GDP bounces back, and interest rates increase as demand for credit rises. We may even see gains as large as the double digit returns seen in years past.

Moreover, beyond past quantitative indicators, future market trends such lower affordability of homes and increased credit restrictions by lenders predict continued demand for apartments.

About the Author: William Marin is a former Deloitte senior consultant with 5 years of experience covering financial services institutions. He worked in the Advisory practice helping clients improve their regulatory and operational capabilities across various functions of their organization. He will commence his studies at The University of Chicago Booth School of Business this fall. The views expressed above are personal, academic and do not constitute investment advice.

Artificial Intelligence Multifamily Screening Tenant Risk

Machine learning creates 250 happy homes

Artificial Neural Networks in Practice - Towards Data Science
Beekin’s workforce housing product helps pick renters who pay well

18 months | 135k lines of code | 5 PhDs | thousands of false positives later..

.. we have an answer – a renter is much more than their credit score.

Today we celebrate 250 happy families who rent a home in a community they love, thanks to Beekin. The zipcodes for these properties reflect high crime rates, low college attainment levels and the distribution of credit scores is poor.

Experian’s 2012 analysis shows that your zipcode can influence your credit score, and that’s a bias in society which fintechs are arbitraging by giving loans to people.

As we look back on Riskpro, our workforce housing product, which picks great residents from screening rejects, we can’t help but feel proud. The residents approved through Riskpro performed great compared to those approved by a traditional credit score based screening approach.

Moreover, given the areas where Riskpro is deployed (low-income mid west), it provides affordable rental housing to the Nation’s workforce (employment data is a positive input in credit performance and Riskpro’s approach).

Particularly relevant at this time, as there is understandable outrage against racism and attitude towards minorities. It is in times like these, where we remind ourselves that science can build a better society. Such as giving someone a home to live, when a 60 year old credit score deems them unworthy.

Everyday, machine learning, mathematics and data is help us better understand space, medicine, online shopping. The same toolkit can remove biases and build efficient markets where few exist.

To every data enthusiast we know – think hard about using your toolkit to solve problems. The end goal is beautiful.

As we look back on our 18 month journey for Riskpro, the Beekin analytics and engineering teams send thanks to – Dr. Marina, Prof. Tony, Dr. Christian, and Chao. Your efforts at applying science to everyday problems have paid off. Big socially distant pat on the back since COV-19 makes everything else impossible.

And finally, to all the Riskpro residents – you will never know who we are, but we hope you enjoy your stay.

For more details on Riskpro read our 2019 paper here

Artificial Intelligence Data Engineering Multifamily

Are Americans moving more?

Average Length of stay for Renters across apartments and homes in 11 cities in the United States, and 5 year change

It is a known fact that renters move. Some more than others, and sometimes it’s a happy move (moving for making more $, larger family, better weather) and sometimes, well, it’s not.

Landlords, in their search for utopia, want renters who (1) keep paying them higher rent every year than the year before (2) pay their rent on time (3) don’t wreck the place and (4) stay for extended periods of time. Utopia may not exist, but thankfully data science does. It can not make you young, taller, but it can find patterns about why people move, and once known, can predict when someone is likely to move.

In our quest for THAT answer, Beekin data science analysed 5 million renters using their mobility data, rent data sourced from 12 different public and private datasets. A few months of hard work, but some cool results that we feel pretty excited about.

We found resoundingly similar patterns across cities, and an understanding of when people are likely to move which depends on both their demographics, the property as well as the area they live in. Duh, but wait, this is a quantitative model versus a judgement.

In the first part of a 3 part series, we output the- renter tenure or length of stay across a few cities in the United States. This helps guide both investment and asset management decisions.

Overall – Los Angeles did well compared to most cities, with renters staying for an average of 5.7 years and an increasing rental tenure. We’ll get back to why that could be in a bit.

In contrast, most cities saw a marked drop in rental tenure over the past 5 years. This is proven and probable: things like lifestyle changes, job transitions and new rental housing stock in these cities all contribute to people moving a lot more.

Interestingly, all of the cities with falling tenure have seen strong net migration as well as net new construction starts. Specifically, people moved a lot more into – Dallas, Denver, Atlanta, Washington D.C.

The more red a state, the higher the net migration into it. No pun intended.

A snapshot of 2018 Census data below, shows us in-state moves and moves into the state (net migration %). With some obvious skews (D.C. as a state is small, but people live in VA, MD), there is a visible trend toward the sun belt states.

The graph below shows you how many people lived in the same house 1 year ago, how many moved in-state and a % of out-of-state and international migrants in as a proportion of state population.

US census 2018, net migration into the 11 states for the 11 cities

In the spirit of compliance, while understanding these relationships, Beekin data science “muted” variables which could be considered discriminatory including marital or family status, ethnicity or race. The results are robust, fair and scalable. And if done right, can lead to a happy renter and happy landlord.

Hope you have fun using them.