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. In layman terms, AVM is an automated appraisal which takes fraction of seconds to generate a property value estimate on the other hand a manual appraisal takes many days to estimate property value. It minimizes the human intervention and estimate the real estate values quickly which helps to save time of both lender and consumer. It works on the principle of data science and machine learning.

Case Scenario for Banking Sector

Problem:

For any banking sector it is obligatory to access their real estate portfolio for accounting and regulation compliances as well.

Traditional Method:
  • Contact real estate
  • Visit house
  • Looking for comparable property
  • Estimate value (Average property price)
AVM (With advance Machine learning algorithm)
  • Accessing neighborhood properties
  • Collect previous transaction data and property characteristics data e.g., land, highways, visibility and amenities
  • Develop the machine learning model and improve the accuracy level
  • Predict each property rate in the neighborhood
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
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.
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
  • Ability to provides Comparable analysis of equivalent land properties.
  • Separately show the price of land property with respective of district and block.
  • Provide information about nearby amenities.
  • Provides nearby geographical locations characteristics.
  • Uses Statistical and mathematical modeling with data set to find out the accurate real estate price of a property.
How It Works
  • AVM uses previous land transactional data having various number of features related to land, Highways, Visibilities, and amenities characteristics of subjective parcel.
  • Automatically clean and analyzes the data and find the correlation between rate and other attributes.
  • Uses advance machine learning mathematical and statistical algorithmic model.
  • Performs all possible iterations before selecting final model for price validation.
  • Select the best fit model for predicting the land property price from all developed model.
  • Finally, estimates the value of all the neighborhoods properties.
AVM Perspective to Real Estate and Data Science
  • AVM helps to understand the property market in the present, by harnessing large data sets to assess fair current transaction prices​
  • Helps clients to understand the present condition of real estate market, by using transaction prices
  • With the help of Data Science, AVM predict the property price based on land attributes, category roads and essential amenities usually preferred by everyone like proximity to schools, mosque, hospitals etc.​
  • Helps homebuyers in evaluating their investments with the price quoted by the sellers.
Objective of AVM Exercise
  • Minimize the threat of a crisis in the financial and economic sector​​
  • Decision-making algorithm​
    • For credit decision purposes​
    • For the recognition of invalid assessments/Transaction​
  • Compare and estimate the values of similar real estate properties at the same point in time.
  • 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.​
Our AVM Users

Mortgage Services​

Government Agencies​

Investor

Valuators / Appraisers​

Lending Institutions​

Real Estate Agencies / Realtors​​

Investment Professionals​​​

Challenges
  • Identify the attributes responsible for value of a property​​​
  • The scarcity of correct transaction data​
  • Bulk deal
  • 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​
Benefits
  • 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​
  • Minimize the time spend on valuation.​​
  • Less manual efforts mean lower risk of human error.​​
  • Greater precision on the fair market value of a property
  • Reduces the cost associated with traditional property appraisal method.