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.

Dream House CalculatorHelping people find the house

they need, love and can afford

MIT Media LabCenter for Future

Banking

UROPs: Ana Chen, Mary HongAdvisors: 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

Concept: process in 8 parts

3 kids

Modern

Garden

Eat out

Dog

Entertain guests

Golf

HikingHusband

Work (artisan)

Comfort

Lots of light

Priorities

Backyard

Study

Good school district

No lead paint

Dining roomBar

Patio

Studio

Tool shedGarage

Foyer

Financial Boundaries

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

BasketUrban CapeMy HouseKelly’s HouseSmall yard houseHouse 2

Add

Delete

LibraryHouse 1June_30_08Urban CapeDream home 1My HouseKelly’s HouseSmall yard houseHouse 2

Fill Your Basket

Continue

Search Results

Recap: Information Flow

Statistics,

Hedonic pricing model

• 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

Questions?