Applicant & Renter Quality

Transcription

1 Applicant & Renter Quality A Special Presentation to NCAHMA 2008 Multifamily Market Demand Summit Applicant & Renter Quality An NMHC/InnesWorks Consulting Research Project

2 Origins How has the sub-prime mortgage crisis affected the multi housing industry? Applicant & Renter Quality An NMHC/InnesWorks Consulting Research Project

3 Specifics How has renter quality changed? Why? Are evicted homeowners becoming renters? How is the industry treating applicants with mortgage stress? Are renewals up? What s the industry s view for 2008? Applicant & Renter Quality An NMHC/InnesWorks Consulting Research Project

4 Methodology Direct interaction with industry experts Screening companies First Advantage/Safe Rent RealPage RentBureau RentGrow ResidentCheck TransUnion Applicant & Renter Quality An NMHC/InnesWorks Consulting Research Project

5 Methodology Direct interaction with industry experts Owner/operators (790,000 units) AIMCO AEC Realty Equity Residential Lane Pinnacle Riverstone Residential Applicant & Renter Quality An NMHC/InnesWorks Consulting Research Project

6 Limitations Data is always backward-looking Optimistic bias, especially the data providers Timeline issues: How long before world events begin to show up in the data? Weeks, months, quarters? Understates the scale of beliefs Optimism, though prevalent, is tepid Pessimism, though rare, is strong

7 Renter & Applicant Quality Renter quality How someone performs as a renter Socially Economically Applicant quality How likely someone is to fulfill the lease obligations

8 Applicant Quality Risk Management Need to predict risk of default Risk measured as a score Three major components Credit reporting agencies Court records Previous rental history (where available)

9 Scoring bands Accept Accept with conditions Sometimes cut more finely Requires ameliorating up-front payments to offset additional risk Deny Increased deposit amounts Additional months rent Co-signers

10 Rules Many landlords supplement score acceptance with rule filters that screen out certain applicants Criminal background Mortgage default

11 Risk Management Most prevalent trend in industry Where scoring bands are set Conditions attached to the middle score band Nature of rules Attempts to mitigate risk to NOI

12 Risk Managment Strong economic motivation to accept 45-60% of applicants accepted without conditions 25-40% accepted with conditions 10-20% denied 2-5% subsequently accepted with conditions

13 Empirical/Quantitative Scoring Risk mitigation requires validated, predictive scoring models Only available since 2001 Have largely replace rule-only approaches Provide consistency over time

14 The Middle Band From a risk management perspective, receives the most attention Managing risk at the margin The conditions imposed help minimize non-performance risk when sub-optimal applicants are allowed to lease The riskier the applicant, the more conditions

15 Are Scores Predictive? Major scoring models are validated Three major axis Court records Rent payment history Financial predictor Psychological predictor Credit history

16 Uncertainty Can validated scoring models predict unforeseen life events? Yes, in the aggregate No, for an individual Strategies High rent-to-income ratios Early warning systems

17 Uncertainty Increasing? Industry sources disagree Some see no upward trend in unforeseen life events Others find the current economic crisis unsettling, putting pressure on consumers Defaults Job losses Reduced discretionary income

18 What Does the Data Show? Multifamily Applicant Risk Index Q '05 2Q '06 2Q '07 1Q '06 2Q '06 3Q '06 4Q '06 1Q '07 2Q '07 3Q '07 4Q '07 1Q '08 2Q '08 94

19 50.0% 45.0% 40.0% 35.0% 30.0% 25.0% 20.0% 15.0% 10.0% 5.0% 0.0% What Does the Data Show? RentGrow: Renter Quality Trends % Perfect % A % Rejected July '03 Jan '04 July '04 Jan '05 July '05 Jan '06 July '06 Jan '07 July '07 Jan '08

20 What Does the Data Show? Applicant Quality: ResidentCheck Q1 '03 Q2 '03 Q3 '03 Q4 '03 Q1 '04 Q2 '04 Q3 '04 Q4 '04 Q1 '05 Q2 '05 Q3 '05 Q4 '05 Q1 '06 Q2 '06 Q3 '06 Q4 '06 Q1 '07 Q2 '07 Q3 '07 Q4 '07

21 70% 60% 50% 40% 30% 20% 10% 0% What Does the Data Show? RealPage Acceptance Levels Denied AWC Approved Q4 04 Q1 05 Q2 05 Q3 05 Q4 05 Q1 06 Q2 06 Q3 06 Q4 06 Q1 07 Q2 07 Q3 07 Q4 07 Q1 08 Q3 04

22 Conclusions No real downward trend in applicant quality Steady state or only slight declines All consumers are feeling credit stress, not just applicants Risk management techniques sufficient to offset any slight decreases

23 Conclusion General feeling of optimism barring a significant economic downturn or recession

24 Are the Foreclosed Flocking to Rentals? Some experts, outside the industry, say Yes. The industry, based on its data, says, No, at least not to multifamily

25 Applicants with Mortgages Holding Steady Percent of Applicants with a Mortgage 27.0% 26.0% 25.0% 24.0% 23.5% Percent 23.0% 22.0% 21.0% Jan-04 Mar-04 May-04 Jul-04 Sep-04 Nov-04 Jan-05 Mar-05 May-05 Jul-05 Sep-05 Nov-05 Jan-06 Mar-06 May-06 Jul-06 Sep-06 Nov-06 Jan-07 Mar-07 May-07 Jul-07 Sep-07 Nov-07 Jan-08 Month SafeRent data Applicant & Renter Quality An NMHC/InnesWorks Consulting Research Project

26 Applicants with Mortgage Stress Percent of Applicants with a Past Due Mortgage 6.0% 5.5% 5.5% 5.0% 4.5% Percent 4.0% 3.5% 3.0% Jan-04 Mar-04 May-04 Jul-04 Sep-04 Nov-04 Jan-05 Mar-05 May-05 Jul-05 Sep-05 Nov-05 Jan-06 Mar-06 May-06 Jul-06 Sep-06 Nov-06 Jan-07 Mar-07 May-07 Jul-07 Sep-07 Nov-07 Jan-08 Month SafeRent data Applicant & Renter Quality An NMHC/InnesWorks Consulting Research Project

27 Equity Residential During Q4, % of applicants had a record of a mortgage foreclosure The majority fell within our approve with conditions band

28 Foreclosures & Risk Tolerance Lower risk tolerance Rules to prohibit foreclosures from renting Higher risk tolerance Accept foreclosures If score is otherwise acceptable With additional conditions

29 Are foreclosures renting? Marginal impact RentGrow Foreclosed Applicants 1.8% 1.6% 1.4% 1.2% 1.0% 0.8% 0.6% 0.4% 0.2% 0.0% Aug-05 Aug-06 Aug-07 Applicant & Renter Quality An NMHC/InnesWorks Consulting Research Project

30 Foreclosures Represent between 2% and 6% of all applicants Industry opinion is split as to the level of current and future risk posed by those with foreclosure Some welcome them (with conditions) Other refuse them outright Applicant & Renter Quality An NMHC/InnesWorks Consulting Research Project

31 The Ownership Flood Is Over In most markets, the ownership wave is over Uncertainty about future Will homes continue to depreciate? What will my personal situation be six months to a year from now? Better keep renting! Much tighter mortgage requirements Applicant & Renter Quality An NMHC/InnesWorks Consulting Research Project

32 But Renewals Are Not Up Despite strong decrease in movement of renters into ownership Why? The market is resettling A B A A+ Applicant & Renter Quality An NMHC/InnesWorks Consulting Research Project

33 Impact of Resettling Possible tend towards recapture of former good tenants

34 Other Risk Factors Seasonality 2 nd & 3 rd Qs are the good months Most elective moves occur then 4 th Q and 1 st Q are the bad months Absence of elective movers means proportionately more non-elective movers Non-elective movers are statistically not as good risks as elective movers

35 Other Risk Factors Thin Credit Applicants Immigrants Newly graduated college students

36 Other Risk Factors Medical Defaults 36% (and growing) of applicants have a medical default As opposed to roughly 2-6% with mortgage defaults Many algorithms don t capture this data

37 New Data Realms to Capture Cell phone bill payment history Utilization of pay-day lenders Utility bill payment history

38 Findings: Guarded Optimism Data is comforting; no real change in applicant scores No wholesale degradation from turmoil in financial, housing, or other markets Foreclosed individuals are not flooding into multifamily housing The wave of move-outs to ownership has crested Applicant & Renter Quality An NMHC/InnesWorks Consulting Research Project

39 Findings: Guarded Optimism Bad debt ratios holding steady Current risk management strategies and practices seem adequate to protect NOI Many markets recovering Better supply/demand ratios Occupancy up; Fewer concessions Modest net rent increases Traffic up Applicant & Renter Quality An NMHC/InnesWorks Consulting Research Project

40 Justified? What effect will continued economic deterioration have on renter quality? Uncertain employment outlook Higher prices for basic goods and services Delayed impact of foreclosure consequences Applicant & Renter Quality An NMHC/InnesWorks Consulting Research Project

41 Thanks Time for questions..