Transcript Dream House Calculator

Dream House Calculator
Helping people find the house they
need, love and can afford
UROPs: Ana Chen, Mary Hong
Advisors: Dan Ariely, Marko Popovic
MIT Media Lab
Center for Future Banking
Have you ever…
Thought you “needed” a house with 6 bedrooms, 3 guest
rooms and a huge living room
…then discovered you really didn’t?
Bought a cozy cottage that seemed perfect at the time
…only to get married a few years
later.
With elderly in-laws moving in and children on the way,
suddenly the “perfect” home seemed way too small
At Thanksgiving dinner, your obnoxious cousin
constantly brags about his new 3-story
colonial in the suburbs with French doors and
that amazing spiral staircase
Next time, you find yourself sinking money into
a house even bigger and fancier than his, but
completely unaffordable
…before you know it, you are mortgaged for all your
worth
Defining the
Problem
Current Resources
(1) Real Estate Search Tools:

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“Checklist questionnaire” - criteria by physical
attributes
“Filter” approach
Examples: Coldwell Banker, Prudential, Zillow
Problem: Doesn’t help user decide what is necessary – or not
“Filter” too general or too absolute
(2) Mortgage Calculators:

Calculate maximum mortgage buyer can pay
Problem: Doesn’t calculate what buyers should borrow
Result
Many people don’t:



Plan adequately for the future
Make a distinction between what they need
and what they want
Consider how circumstances change over
the time span that they plan to live in the
house
Mortgage Crisis
•
•
In 2007, delinquency and foreclosure rate for
all mortgages was 7.3%
5.7% of home equity lines of credit were
delinquent or in default at the same time
Take-away
Buying a house is one of the biggest
financial decisions in a person’s life

It is a complex, highly personalized process,
in which it is easy to make mistakes

When people make the wrong choices, it
causes problems for them and the bank
Solution:
a new kind of Real Estate and Mortgage
Application
Strategy
Guide
Quantitative
-lifestyle
-statistics
-wants/needs
-algorithms
-dreams
-future
-hedonic pricing
model
(economics)
-priorities
-searching &
sorting
Concept:
process in 8 parts
Backyard
Study
Good school
district
No
lead
paint
Hopes, dreams and the
future
Golf
3 kids
Husband
Priorities
Dog
Garden
Hiking
Dining
room
Entertain
guests
Comfort
Bar
Eat out
Modern
Patio
Most important
• Family
• Career
• Education
Very Important
• Neighborhood
• Health
Lots of
light
Work (artisan)
Foyer
Not so important
• Lifestyle
• Aesthetics
• Leisure etc.
Studio
Garage
Tool shed
…
2 car garage
2 car garage
…
…
Hopes, dreams and the future
Most important
• Family
• Career
• Education
Pool
…
Very Important
• Neighborhood
• Health
Not so important
• Lifestyle
• Aesthetics
• Leisure etc.
Many windows
Single level
Good school
district
Finished basement
Financial Boundaries
Eat-in kitchen
Shed
Round peg, square hole problem…
Hopes, dreams, future
Financial constraints
Hopes,
dreams,
Solutions
future
Financial
constraints

Trade-offs:
- Deform circle
-
Cut the circle
Hopes,
Hopes,
dreams,
dreams,
future
future
Financial
constraints
Financial
constraints
Financial
constraints
Hopes,

Change size of square*
dreams,
future
* Greater financial risk
Comparison
Hopes,
dreams,
future
Financial
constraints
A

Hopes,
Hopes,
dreams,
dreams,
future
future
Financial
constraints
B
Financial
constraints
C
New metrics for comparing houses
House X is 80% like A at 110% of projected price
House Y is 60% like A at 80% of projected price
Demo

Interview
Design Screen Shots

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
Prioritization
Financial interview
Attributes Association
Trade-offs
Library / “Basket”
Search Results
Prioritization
Continue
Association
Trade-offs
Fill Your Basket
Library
Basket
House 1
June_30_08
Urban Cape
Dream home 1
My House
Kelly’s House
Small yard house
House 2
Urban Cape
My House
Kelly’s House
Small yard house
House 2
Add
Delete
Continue
Search Results
Recap: Information Flow
Interview I
(Lifestyle)
Prioritization
Basket
(metric)
Associations
Interview II
(Finances)
Trade-offs
Statistics,
Hedonic pricing model
Sorted Results
Recap: What’s New
•
Guides buyer through the process of finding the “right”
house –realistically and financially, in a way that is
logical, but natural
•
Considers buyer’s present situation and future plans
•
Helps buyer compare houses that may be very different –
in features and price
•
Allows buyer to accurately evaluate trade-offs between
what he wants and how much he’s willing to pay
•
Makes sure buyer doesn’t spend more than he can afford
Hoped for Results

More happy and financially stable buyers

Decreased risk for mortgage provider

Overall healthier real estate and mortgage system
Completed Work
-
Running Interview user interface
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Suggested attributes for various lifestyles
-
Design of rest of application
Future Challenges

Statistical analysis to build realistic hedonic
model of projected prices

Working prototype for Boston area listings
=> eventually expand to entire US

Cognitive system that “learns” from user
responses to give improved attribute
suggestions

Redesign questions and relevant attributes
based on user feedback
For Bank of America
Differentiate from other mortgage businesses



Not just a customer-conscious financial
product, but comprehensive and useful tool
Perfect part of the suite of other financial and
life planning tools in development at BoA, CFB
Reinforce message as a bank that helps plan
your life and your future -- worthy of lifetime of
trust
Thank yous
Dan Ariely
Marko Popovic
Kwan-Hong Lee
Dawei Shen
Shrini
Deb Roy
Aithne
Fellow UROPs:
Ryan
Stephen,
Oscar,
Leslie (“UROP”)
Irum,
Andrew
Questions?