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How Big Data is Changing the Real Estate Industry .pdf


Original filename: How Big Data is Changing the Real Estate Industry.pdf
Title: The Real Estate Industry in 2017 (2)

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HOW

BIG DATA ANALYTICS
IS CHANGING THE

REAL ESTATE INDUSTRY

DATA MINING AND ALGORITHMS
TODAY

2025

BIG DATA
What data?
100 exabytes

· Company data
· Economic data
· Market data

1 zettabyte

Data mining using automated algorithms
SMART DATA
What data?

Sentiment analyses

Predictive analytics
Cognitive computing
AI

eg : Market reports
Support during decision-making
Risk analyses
Forecasts

CHANGES IN ANALYSTS’ WORK BETWEEN NOW & 2025
TODAY

2025

Analysts compile the data necessary

Big data applications usually run in the

for their analyses from a host of sources they

backgroung and generate output for

must themselves find and assess

analysts in the form of small / smart data

80%

20%

Data
gathering

Data
gathering

Information searches

Big data

and data gathering

queries

Smart /

People

Unstructured
sea of data

Small data

Smart /

People

Big data
application

Small data

20%

80%

Data
analysis

Data
analysis

• Research

• More accurate forecasts / predictions

• Ad-hoc queries

• Identification of complex relationships

• Forecasts

• Market reports

• Evaluation of decision-relevent

• Analyses

market in formation

• Working with probabilities

• Market reports

• Automatic statistician

• Analyses

POTENTIAL OF BIG DATA IN THE REAL ESTATE SECTOR

BUILDINGS

SERVICES

MARKET

Huge volumes of
technical data
are analyzed in real time.
Owners can modify buildings
to enhance efficiency that will
reduce operational costs.

Transparent customer
profiles ensure providing
better fit, high quality and
personalized offers for clients
which they can’t resist.

Big data strategies can
produce financial, investment
and market insights that help
with assessing risks and
making decisions.

However, big data does not have the same impact on every field and business division in the
real estate sector.

HOW STRONGLY WILL IT IMPACT DIFFERENT
REAL-ESTATE FIELDS & BUSINESS DIVISIONS

Major Impact

Medium Impact

No Impact

• Transaction Consulting

• Fund Management

• Property Investment

• Property Finance

• Building Management

• Project Development / Implementation

IMPACT OF BIG DATA ON RESEARCH/MARKET ANALYSES
36.4%
41.2%

Research will become more
important as a result of big
data

Quality will improve in the
research sector and the
work of researchers
(output at work : 80%
analysis, 20% data
gathering; more accurate
statements about future
developments in the real
estate market)

21.5%
Researchers can use big
data to supplement their
work

0.9%
Big Data will make research
redundant as a market
segment

REAL ESTATE INDUSTRY SECTOR THAT WILL
UNDERGO THE GREATEST CHANGES DUE TO BIG DATA
35

30.5%

Property
Investment

30

25

23.8%
20

Transaction
Consulting

14.3%

Fund
Management

15

5.7%

10

16.2%

Building
Management

9.5%

Property
Finance

Project development /
Implementation

5

THE OVERALL IMPACT BIG DATA CAN HAVE ON THE
REAL ESTATE SECTOR

67% - Big data

59% - Big data

51% - Enhanced

49% - Positive

brings transparency
to the markets

helps minimize
risks

standardization across
the real estate

contribution to
investment decisions

48% - Enhance

19% - Gathers

6% - Management

5% - Cannot see big

risk adjusted
investment decision
making

automated KPIs such as
take-up and investment
volumes

has less autonomy
when making decisions

data having any impact
on the real estate
sector

WILL MORE DATA LEAD TO MORE STABILITY ON MARKETS ?
Agree in part

49.1%

Disagree

31.1%
Agree strongly

16.0%
Disagree strongly

3.8%
0

10

20

30

40

50

60

TYPES OF BIG DATA ANALYTICS ENTERPRISES ARE USING
Customer Experience &
Customer Relationship
Management

Data
Discovery
Tools

Mobile Commerce
Analytics
Business
Intelligence

Not So
Popular

Popular
Financial
Analytics

BigData
Database
Technology

Social Media
Monitoring

External
Data Sets

WHY SHOULD INVESTORS CARE ABOUT REAL ESTATE
ANALYTICS?
Top Opinions of the survey participants on why should investors adopt Big Data
Analytics :

71% –

62% -

39.8% -

Improves
transparency of real
estate markets

Helps
Predictive analytics
(using historical data to
forecast/ identify trends)

32% - Optimizes

25% - Provides

22% - Improves

property investment
models

accurate property
evaluation

communication for
market participants

It improves / supports
decision-making
processes

52.8% Minimizes risk

5.5% - Other

WHAT DOES PREDICTIVE DATA TELL A REAL ESTATE
INVESTOR?
How good a
market is for
investing

How does this
data help them
get rich?

How much money
other investors
are making

Tells them the
competition

Shows what property to
pick and what strategy
to use

How much money
they could be
making

KEY BIG DATA APPLICATIONS FOR BANKS,
REAL ESTATE INVESTMENT TRUSTS (REITS) & BUYERS
Better understanding
communities and local
markets

Guide capital
decisions on
acquiring property

Leverage Big Data to
perform more granular
modeling of their MBS
portfolios

Focussed and
predictive real estate
marketing and
boosted pitching

Making
Construction
Administration
Better

For REITS

Risk Data
Aggregation &
Calculations

For REALTORS
Highly customized
servicing

Detect and Prevent
Money Laundering
(AML)

Smart Cities, Net New
Investments and
Property Management

Target the right customer
with the right offer they
can't resist

Banks can use big data
resources to determine whether
a foreclosure or short sale is
really worth what a buyer or
investor might be offering

Property Dealers can't fool
customers about the value
of certain property

Easily find the best
property that matches
their preferences

For BANKS

For BUYERS

The knowledge of actual
property value can help
them wait for a genuine
buyer rather than a
smart investor

Make more informed
decisions based on
real data

Feel more confident
and satisfied about
their decisions

BIG DATA’S PROS & CONS

PROS

CONS

More accurate forecasts /
predictions

Big data doesnot have the same
importance at all companies

Market
Transparency

More expensive
to harness

Identifying previously
unknown potential

Privacy and data protection :
who is allowed to use the data?

Faster and more
comprehensive analyses

Swarm stpidity ? -> “Percieved
connections” ?

Faster reactions by
management
Improved customer
service

USA | INDIA | UAE

info@fingent.com | www.fingent.com

Source :
https://ww2.frost.com/event/calendar/big-data-analytics-whos-buying-what-and-what
-are-they-missing/
https://www.catella.com/Documents/Germany%20Property%20Funds/02_Research
/01_Studien/Catella%20Resarch_Big_Data_%202015_english.pdf

Copyright © 2017 Fingent Corporation. All rights reserved.


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