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Dream House Calculator Helping people find the house they
need, love and can afford MIT Media Lab
Center for Future Banking UROPs: Ana Chen, Mary Hong
Advisors: Dan Ariely, Marko Popovic
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:
“Checklist questionnaire” - criteria by physical attributes
“Filter” approach
Examples: Coldwell Banker, Prudential, Zillow
(2) Mortgage Calculators:
Calculate maximum mortgage buyer can pay Problem: Doesn’t help user decide what is necessary – or not
“Filter” too general or too absolute Problem: Doesn’t calculate what buyers should borrow 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 Result 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
-lifestyle
-wants/needs
-dreams
-future
-priorities
Quantitative
-statistics
-algorithms
-hedonic pricing model (economics)
-searching & sorting Concept:
process in 8 parts Hopes, dreams and the future 3 kids Modern Garden Eat out Dog Entertain guests Golf Hiking Husband Work (artisan) Comfort Lots of light 1 2 Priorities Backyard Study Good school district No lead paint Dining room Bar Patio Studio Tool shed Garage Foyer 3 4 Financial Boundaries Hopes, dreams and the future 2 car garage 2 car garage Pool Many windows Good school district Finished basement Shed Eat-in kitchen Single level … … … … Round peg, square hole problem… Financial constraints Hopes, dreams, future Trade-offs:
- Deform circle
Cut the circle Solutions * Greater financial risk Change size of square* Financial constraints Hopes,
dreams,
future Financial constraints Financial constraints Financial constraints Hopes,
dreams,
future Hopes,
dreams,
future Hopes,
dreams,
future Comparison New metrics for comparing houses
A B C Financial constraints Hopes,
dreams,
future Financial constraints Hopes,
dreams,
future Hopes,
dreams,
future Financial constraints House X is 80% like A at 110% of projected price House Y is 60% like A at 80% of projected price Demo Design Screen Shots Prioritization
Financial interview
Attributes Association
Trade-offs
Library / “Basket”
Search Results Interview Prioritization Continue Association Trade-offs Basket
Urban Cape
My House
Kelly’s House
Small yard house
House 2 Library
House 1
June_30_08
Urban Cape
Dream home 1
My House
Kelly’s House
Small yard house
House 2 Fill Your Basket Continue Search Results Recap: Information Flow Interview I (Lifestyle) Prioritization Interview II (Finances) Associations Trade-offs Statistics,
Hedonic pricing model Basket (metric) Sorted Results 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
Recap: What’s New 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
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
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