About Estater Meter

Estater Meter use the power of Geographic Information System (GIS) and Data Science to make smart real estate decisions. Estater Merter is prominent tool for decision making in real estate property valuations and overview the various property attributes such as Amenities, Highways, Visibility, corner....etc.

Estater Meter Compare and estimate the values of similar real estate properties at the same point in time.

  • ​Instant property valuation​
  • Prominent tool for decision making in real estate
  • Valuation based real time actual characteristics of property​
  • Objective, non-biased and cost-effective tool​
  • Comparable tool provides quick estimates w.r.t. property’s attributes.
  • ​Largest Real Estate Database that you can rely on
  • Interactive GIS maps to accurately visualize volumes of property information
  • Based on advance machine learning algorithm and artificial intelligence in order to provide accurate valuations
  • Statistically more accurate at producing valuation in aggregate​

How It Works

Estater is a propTect company which use AVM module to refine their data

Buying and selling real estate properties has become easier with emerging PropTech companies.

1AVM Objective

AVM is a modern term used to describe service globally that fuses statistical and mathematical model

Read More

2 Data Science

Data Science is practice of organizing and analyzing of data to gain insights that can be helpful for human making decision.

Read More

3Machine Learning

Machine learning is a subset of data science that allows software to become more accurate at prediction or estimate future values.

Read More

4Methodology

  • Property Valuation Methods
  • Hedonic Regression
  • Methodology (read more...)

Read More

EM is a simple solution/helps to answer a variety of users

What Is AVM

AVM is a term used to describe service that provide real estate property value by using advance statistical and mathematical machine learning model. It uses land transaction data and characteristics of property data e.g., land, highways, visibility and amenities to arrive at an estimate property value.

Read More

Why AVM

  • Fast and easy access of land property
  • Easy to overview the property characteristics
  • Save time and cost for both lender and consumer
  • Results are based on past transaction and property characteristics
  • Accurate and consistent property valuation
Read More

How AVM In Estater Meter Estimate Property Price

  • In Estater meter, AVM use statistical and mathematical model to predict the current market value of respective property.
  • Our research team analyses the data, check property in different geographics area and identifying and examine the relationship between property rate and attribute characteristics.
  • Based on these relationships and identified pattern our team develop a statistical model and improve the accuracy level to estimate the property’s current market value.
Read More

Features

  • Provides real time market value estimation of a property subjected to various feature e.g., Corner, Visibility, Amenities...Etc.
  • ​​Minimizes the need to personally inspect and scrutinize each property ​
  • Estimating considerably different pricing according to the land property​
  • In AVM Individual characteristics of each property separately priced, to control for differences across land attributes, proximity to amenities, roads category and past transactions data​
  • Separately show the price of land property with respective of district and block.​
  • Provide information about nearby amenities.​
  • Provides nearby geographical locations characteristics.​
Read More

Objective of AVM Exercise

  • Minimize the threat of a crisis in the financial and economic sector​ Decision-making algorithm​
  • Decision-making algorithm​
    • 1. For credit decision purposes
    • 2. For the recognition of invalid ssessments/Transaction​
  • Compare and estimate the values of similar real estate properties at the same point in time.
  • To select a property for valuation.
  • To evaluate the property supported desired attributes
  • From a cluster of properties, identify comparable properties for valuation.​
  • Property valuation based on required characteristics/attribute such as Highway, Amenities, Area, Visibility, Corner…etc.​
Read More

Our AVM Users

Mortage Services
Government Agencies
Investors​
Valuators / Appraisers​
Lending Institutions​
Real Estate Agencies/Realtors​
Investment Professionals​
Read More

What Is Data Science

Data Science is practice of organizing and analyzing of data in order to gain insights that can be helpful for human making decision. Data Science is a combination of multiple fields, including Machine learning, statistics, data analysis and scientific method used to extract meaningful information from noisy data. It gives hidden insights and trends about the market which helps users to take valid steps in future.​

  • With the help of emerging Data science and predictive analytics tools and technologies, we can quick and accurately organize and qualify data, recognize market dynamics and optimize business strategies in various sectors.
  • ​Data Science in Real Estate helps identify and manage risks, forecast customer behavior and increase engagement to offer more personalized solutions to clients.​With the help of various Machine Learning models like multiple regression, Decision Tree, Time series models are capable to predict the current market value.
  • ​In real estate data science plays vital role to analysis the market patterns, recognize risk and study customer behavior.​
Read More

Concept of Data Science

  • Artificial Intelligence and machine learning based algorithm in AVM automatically detect vital patterns and trends in the data.
  • ​Analysis based on real time market value of property.
  • Find correlation between the market value with other attributes which triggers the value of market.
  • Uses Statistics concepts, machine learning, and programming language such as Python or R.
Read More

Type of Data Used in Estater Meter

  • Categorical data: Basically, used to denote a unique ID for a particular parcel so that it can be distinguish and also can be used to denote yes or no in the data, or in binary language 1 or 0. ​
  • Continuous data: These are the numerical data which can goes to infinity for example price of land. Based on these relationships and identified pattern our team develop a statistical model and improve​
  • Discrete data: These data show the count value of a variables or features. It doesn’t go beyond a particular value.
Read More

Data Sources​

  • Spatial data (GIS).​
  • Transactional data.
  • ​Amenities data.
  • Land Zone data.​​​
  • Road Infrastructure Data​​​
  • Location Data
  • Land Feature​​​
  • Quotations​​​

Data Science Perspective for AVM

  • Gives initial insights about AVM performance.
  • ​Uses Data science tools to generate insights reports.​​
  • Using Visualization tools for finding trends.
  • Helps to make highly accurate forecasts as data technology progresses which able to make more profitable decisions.
  • By considering property characteristics and demographics situations, helps to forecast property returns in selective neighborhood.
  • Uses statistical tools for getting basic information and making assumptions.

Automated Valuation Model based on ML algorithm​

AVMs in the real estate sector are algorithms (basically a combination of Machine Learning techniques) that are trained on large amounts of data such as transaction data and land property attribute in order to predict the values of properties.

AVM-

  • ​Statistic-based computer programs.​​
  • Use property information (e.g. transactions and property attributes etc.) to generate suggested value.
  • Produces a market valuation through mathematical modelling.​
  • Variety of statistical and algorithmic approaches​​​​
  • Analyzing the relationship between the price/value of a residential property and the property’s underlying attributes.
  • Application of statistical methods and Mathematical Modelling such as multiple regression analysis (MRA)​​​

Automated Valuation Model based on ML algorithm​

AVMs in the real estate sector are algorithms (basically a combination of Machine Learning techniques) that are trained on large amounts of data such as transaction data and land property attribute in order to predict the values of properties.

AVM-

  • ​Statistic-based computer programs.​​
  • Use property information (e.g. transactions and property attributes etc.) to generate suggested value.
  • Produces a market valuation through mathematical modelling.​
  • Variety of statistical and algorithmic approaches​​​​
  • Analyzing the relationship between the price/value of a residential property and the property’s underlying attributes.
  • Application of statistical methods and Mathematical Modelling such as multiple regression analysis (MRA)​​​

About MRA

Lorem Ipsum is simply dummy text of the printing and typesetting industry. Lorem Ipsum has been the industry's standard dummy text ever since the 1500s, when an unknown printer took a galley of type and scrambled Lorem Ipsum is simply dummy text of the printing and typesetting industry. Lorem Ipsum has been the industry's standard dummy text ever since the 1500s, when an unknown printer took a galley of type and scrambled

Concept of MRA

Concept

  • Statistic-based computer programs.​​

Objective

  • Statistic-based computer programs.​​​
  • Use property information (e.g. transactions and property attributes etc.) to generate suggested value.
  • Produces a market valuation through mathematical modelling.

Equation

  • Statistic-based computer programs.​​​

Multiple Regression Analysis (MRA)​

Multiple regression analysis is a significant technique used for predicting the unknown value of a dependent variable (y) from the known value of two or more independent variables (x).​​

Multiple Regression Analysis (MRA)​

  • ​Applied technique of statistical analysis and modelling​.​​
  • Understand the relationship between variables​.
  • Statistical technique to predict the value of one variable based on another variable​Uses several explanatory variables
  • Measure of how strongly one variable influence the other variable​
  • Shows the nature of relationship between variables
  • Calculate the variance in the dependent variable​
  • Helps in establishing the functional relationship between two or more variable​​​

Performance evaluation and measurement of each model​

AVMs in the real estate sector are algorithms (basically a combination of Machine Learning techniques) that are trained on large amounts of data such as transaction data and land property attribute in order to predict the values of properties.

AVM-

  • ​Statistic-based computer programs.​​
  • Use property information (e.g. transactions and property attributes etc.) to generate suggested value.
  • Produces a market valuation through mathematical modelling.​
  • Variety of statistical and algorithmic approaches​​​​
  • Analyzing the relationship between the price/value of a residential property and the property’s underlying attributes.
  • Application of statistical methods and Mathematical Modelling such as multiple regression analysis (MRA)​​​

MRA​

Challenges-

  • ​Identify the attributes responsible for value of a property​​​
  • The scarcity of correct transaction data​
  • Identity the source of all these attributes​​
  • Discover methods to quantify and digitize these attributes
  • Identify verified sources of transaction or quotation data​
  • Develop model to test AVM
  • Develop prediction

MRA

Benefit-

  • ​Confidence in the accuracy of the result​​​
  • Less human intervention post-initiation​
  • Risk Analyzing Tool​​
  • Supporting tool in decision making system​
  • Provide sufficient statistical output​
  • Convenient, fast and low-cost alternative to a full valuation​​​​​