Download Establishing Support System for Risk Management in Real Estate Investment

Establishing Support System for Risk Management in Real Estate
Investment
1
TANG Xiuli1 YANG Zijun2
School of Logistics, Beijing Wuzi University, Beijing, China, 101149
2
Hebei Software Institude, Baoding, China, 071000
Abstract: Risk management is crucial in real estate investment. It increases the difficulty in risk
management that attributes to the characteristics of a certain real estate investment and the uncertainty
of external environment as well. The aim of this article is to set up a fundamental decision support
system of real estate investment by conducting sound theoretical knowledge stems from system
management and decision support system, for the purpose of assisting the risk management decision
support system with decision making of real estate investment.
Based on the goals of risk management of real estate investment and the principle of being
scientific, systematic, comprehensive, compatible and extendible, the article, first, designs and plans the
function module according to the procedure of risk management. The function module is composed of
five subsystems, which includes risk identification, risk quantification, risk evaluation, risk response and
the post evaluation of risk management. The five subsystems are mutually independent and organically
integrated. Second, it presents the architecture of real estate investment Risk Management Decision
Support System (RMDSS), which includes data warehouse, model base, method base, knowledge base
and their management systems. Third, it explains the key technologies and the relationship among them
of RMDSS, which compose of data warehouse, data mining and on line analytical processing.
Keywords: Real estate investment, Risk, Risk management supported system
1 Introduction
Real estate are faced with a series of risks that attribute to such characteristics as high investments,
continual reward, long time construction and running, dependence on the professional management etc.
The theories of projects risk management then have been studied widely since the 1980s, and they have
been successfully put into practice in risk management of large real estate investment.
Because risk management for real estate investment covers a large field and has much professional
models, the flexible response, and the different levels of risk manager, the management system need to
be established, in which computer is used as a tool with its interfaces being easily understood and being
convenient for operation, and in such system, computer can help the manager to make decisions. As the
risk management system for real estate investment focuses on the quantitative analysis of the projects
investment risks, and the decision support system emphasizes particularly on the qualitative analysis, it
is of great importance to integrate them into risk management decision support system (RMDSS) in
theory and practice.
2 The Framework of RMDSS for Real Estate Investment
American experts of risk management, Robert I Mehr and Bob A Hedges, point out that “the goal
of risk management is to keep profits before loss, and recovered it after loss”. Therefore, the total goal
of real estate investment management is to reduce the risks loss to a minimum low cost, and to make the
investment secure. It needs all factors of real estate investment management to form into an organic
synthesis, which is differentiated mutually, interrelated and interacted, based on the internal demand.
Then the theoretical knowledge of Decision Support System are applied to combine persons’ sense and
computers’ information process, and make further integration with data warehouse, model base,
knowledge base, arithmetic base and their management system[1], and establish real estate RMDSS to
assistant decision-maker and management to reach their goal of risk management.
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3 The Function Framework of Program for RMDSS of Real Estate Investment
Based on the goal of risk management for real estate investment
The collection
and the principles of being scientific, systematic, comprehensive,
of risk factors
compatible and extendible, this article establishes the function
module according to the procedure of risk management. The function
modules consist of five subsystems, which include risk identification,
Risk identification
risk quantification, risk evaluation, risk response and the post
evaluation of risk management. The five subsystems are mutually
independent and organically integrated. The program framework is
shown in Figure 1.
Risk quantification
3.1 The subsystem of risk identification
Risk identification is an essential step in risk management of
real estate investment. Only the risks of investment process is
identified completely and correctly, can we carry on risk
Risk evaluation
quantification, risk evaluation and decision so that risk management
can be based on a good foundation. The main function is to find out
all risk factors that affect the realization of risk management as much
as possible, classify them correctly, and analyze the causes one by
The post evaluation
one[2]. The general ways to identify risks are expert investigation, the
of risk management
technology of filtering- monitoring-diagnosing
methods of
malfunction tree, financial report forms analysis, flow chart, and
insurance investigation etc.
Fig.1. The program framework
3.2 The subsystem of risk quantification
Risk quantification is to describe risks of real estate investment
quantitatively, and whether the level of risk is high or low is judged according to it, besides, it also
provides a basis for making certain of the degree of subsequent impact. The main function of the
subsystem of risk quantification is to assess the probability of an undesirable occurrence, the degree of
seriousness, and the subsequent impact if risks do occur. The general methods of risk quantification are
subjective judgment, objective analysis, damage assessment, the balance analysis of profit and loss,
sensitivity analysis, related effect estimates etc.
3.3 The subsystem of risk evaluation
The subsystem of risk evaluation is not only to evaluate the probability, but their level of impacts
as well. It judges whether the level of risk is high or low, (e.g. the probability of an undesirable
occurrence ,the degree of seriousness, and the subsequent impact if it does occur). The main functions of
the system are to evaluate the impacts synthetically, to analyze the cost and profit of risk management to
the concrete risks, and to make a basis for the latter decision.
3.4 The subsystem of risk response
The subsystem of risk response consists of two subsystems, risk decision system and risk process.
The main function of the subsystem of risk decision is to set up relevant measures for the risk
management, to make multi-plans of risk management, to consider carefully the status and long-term
goal of real estate investment, and decide the best and the combined strategies of risk response. The
main methods and the strategies of risk management include risk avoidance, risk control, risk transfer by
insurance, risk transfer by non-insurance, risk retention, diversification of risk, and risk speculation.
The subsystem of risk process is mainly run to establish an organization of risk management, to
specify one’s duty, to make concrete plans, and bring them into effect in real estate investment.
3.5 The subsystem of the post evaluation of risk management
The risk manager shall monitor the four steps above, especially the risk response, and analyze the
effects of risk management. They must assess whether the risk factors have be omitted, whether the
implementary circumstance have changed, whether some new risk factors appear, whether the measures
are right or not, whether the evaluation is all-sided, whether the decision is reasonable, whether the
plans for risk management need to be supplemented or perfected whether the implement of the plans
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achieved, which process need to be enhanced, and whether the goal is realized. After all the above
problems are settled, the process of the periodic risk management are considered, and the experience
and lesson should go back to the next period.
4 The Logical Structure of Real Estate Investment
Decision Support System(DSS) is a cross discipline between computer science and management
science. It emphasizes particularly on the quantitative analysis of risk management of real estate
investment by means of computer information technology, combining management science and
operational research[3]. With the application and popularization of expert system, executive information
systems, and data mining, the separate DSS will disappear. Consequently, to improve the level of real
estate investment management, it is good for the integration of the qualitative analysis and quantitative
analysis to integrate DSS and risk management into the support system for risk management. Figure 2
lists the logical structure of risk management support system for real estate investment.
User
Human-computer Interaction System
interaction system
Risk identification
Risk quantification
Risk evaluation
Risk response
The post evaluation
of risk management
Data Integration and Interaction
Model base
Knowledge base
Model Base
Management System
Knowledge Base
Management System
Arithmetic Base
Arithmetic Base
Management System
On Line Analytical Processing and Date Mining
Data warehouse
Fig.2. The logical structure of risk management decision support
system for real estate investment
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4.1 Data Warehouse and DM_DW
Data warehouse is the collection of data, which is the process-supported of management decision,
subject-oriented, integrated, stabile, and time different. The information comes from different databases
and other sources[4]. Firstly, a data flat that is uniform, field oriented, and integrated is established.
Secondly, the analytic topic is founded, and the data analysis model is constructed by the technology of
OLAP. Finally, the information is obtained from the end-user tools, and the results of analysis are
produced on the basis of such data as report forms and graphs etc. The new data warehouse is
subject-oriented, which is the striking characteristic that is distinguished from the traditional one. The
subject is a standard that classifies the data in a higher level, in which the datum of information system
are integrated, classified and also are carried on the data abstraction (of the analysis and utilization).
However, datum of the traditional date warehouse are organized, being object-oriented,
application-oriented. The data warehouse of decision support system in the paper is the relatively
original data and information, which is extracted out for risk identification, risk quantification, risk
evaluation, risk response and the post evaluation of risk management in real estate investment. The
process is based on the original database of risk factors and dealing with data, in which the data is
classified, extracted, concluded, and processed. The internal, external data and the governmental data
are all included. Furthermore, the data of risk management case for real estate investment is also
included. The data and the information of the post evaluation of risk management are to be put into the
module of database. All the data and the information above are kept in the database in the forms of base
files and graphs.
The DM_DW manages the operation of all system, is the engine of the system. It includes the
extraction of data of OLAP, market reports and all kind of files. The clearance and conversion, the
division of dimension, the decision of the physics memory structure, the copy and restoration of data are
all included.
4.2 Arithmetic base and arithmetic base management system
Arithmetic base covers the methods to resolve problems, and more approaches to the data
management are also included, which is absolutely necessary for DDS. Based on the model, arithmetic
base computes in the right way, which makes the problems resolved with one model and many solutions.
Based on data warehouse, arithmetic base includes the methods used by the OLAP and DM, which
provides more ways for them. The arithmetic base management system, which is responsible for the
compilation of the uniform interface of methods, is used to increase, delete and change the methods of
the arithmetic base.
4.3 Model base and model base management system
Model base is an aggregation, which stores all kinds of models of the function modules about risk
management for real estate investment in the determinate framework and format. According to the nature
of model, it can be classified into four categories: the mathematics model, simulation models, data
processing model, report format model. There are a large numbers of models in the risk management for
real estate investment, all of which the Monte Carlo Simulation, risk measuring model, CIM, VERT,
cost-benefit analysis model and fuzzy comprehensive evaluation are in common use.
Model base management system provides ways to intervene directly many models, in order to
support the making, compiling, analysis, rebuilding, evaluating, maintenance and other operations of the
model.
4.4 Knowledge base and knowledge base management system
Knowledge base is the extension and outspread of data base in the field of knowledge disposal. It
works mainly to store the knowledge of risk management for real estate investment in certain forms.
Both the fundamental knowledge and experiential one from the experts of risk management are
included[5]. For example, the fundamental risks in all the stages, the measures of risk response, the
organization and culture of risk management, insurance, bond, and counterclaim are all included.
Knowledge base management system will perform the functions of the input, examination and
maintenance of the knowledge rules described in the previous part. Its process emphasizes on the
consequence of knowledge, in which the system assists the manager to manage the risks by certain
principles of consequence, according to the data information input by the manager.
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4.5 Human-computer interaction system
Human-computer interaction system manages the man-machine conversation, which goes through
the risk management in which the support system is used and the hardware, software and the
characteristics of data conversation are bound. The physics system such as the mouse, keyboard ,local
area network and internet are also included in human-computer interaction system. The system help the
manager to make decisions by processing data, computing the model and inferring knowledge, and
produce in the written forms such as reports, diagram, words etc.
4.6 User
In the risk management support system, user is the person who manages the risks of real estate
investment and who also does consulting such as the investor, the owner, the engineers, the designers,
the material suppliers and so on.
5. The Key Technology
5.1 The technology of Data Warehouse
There are two types of data: the operation data and the decision support one. The first is derived
from the processing of routine, and the second is shaped after the former is processed. The operation
data is used for the processing of the routine while the decision support one is run for the increment of
information. The system of decision support data is presently regarded as data warehouse in theory. The
storage and process of vast amount of datum, which the data warehouse is good at, will be of the
greatest importance, when the uniform information platform is established in all systems and is needed
to provide information for the managers and users.
5.2 On Line Analytical Processing (OLAP)
OLAP is a tool for the decision analysis. It is a technique derived from the access of relational
database to special problems and the analysis of data. It can inquire and process complicatedly the large
number of datum quickly and flexibly according to the request of user, and offer the results to all the
decision-making persons. OLAP is the process of data analysis and data process, and is also the user
interface of data warehouse.
The decision-making person is able to process the data of projects flexibly, observes the state, and
knows the changes of project, based on OLAP, an analysis technique separated from the data warehouse.
There are five methods of analysis in the technique of OLAP. They are slice, drill, rotation, free
combination of latitude, free switch of diagrams, and the results of which can be illustrated by the
user-friendly and plentiful report forms.
5.3 The technology of Date Mining
Data mining is the process of seeking credible, new and valuable information in large databases. It
is the crossed-subject covering the database. It integrates techniques from database, artificial intelligence,
neural network, and machine learning.
Data Mining extracts hidden, intelligible and operable information from vast amount of databases.
The goal of data mining is to help the user seek the relations among the datum, and find the factors
neglected, which are of great important. The common technology and algorithms include the decision
tree, neural network, concept tree, genetic algorithms, fuzzy mathematics and so on. The function of
data mining is to realize the prediction of future trends, the analysis of relation, cluster analysis, and
fault detection. It can be implemented by the following steps:
Data sampling
Data groping
Data adjust
Data modeling
Model evaluating
Implementing
Data warehouse, OLAP, and data mining exist in three techniques absolutely. But they grow with
the settlements of decision support problems. Because they are interrelated and complementary, the
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integration of them is a settlement for the DSS based on the technology of data warehouse. Among them,
the data warehouse is used for the storage and organization, OLAP for collecting and analyzing the data,
data mining for the automatic discovering of knowledge [6].
6 Conclusion
The aim of this article is to set up a fundamental decision support system of real estate for the
purpose of assisting the risk manager to identify, quantify, evaluate, respond the risks, to reduce the risks
by relevant measures, and to make the post evaluation of the risk management go back to the system,
which helps the managers to accumulate the knowledge and cases and help them make decision of risk
management.
The whole framework is fundamentally established in this paper. To bring the system to perfection
and concretion, the further advanced study needs to be made. With the development of the computer, the
deepening of the decision support system, as well as the improvement of managers’ ability, the risk
management decision support system would be implemented widely in the risk management for real
estate investment.
References
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[3]Eom, SB. Decision Support Systems Research: Reference Disciplines and a Cumulative Tradition.
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The Author can be contacted from Email: [email protected]
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