The idea behind this software is to enable a user to identify a development site where they can make a profit via using software, based on artificial intelligence.
The overall idea is to create software that can differentiate a pre-developed site and a developed site. Then, the software will analyze how many new properties are created following the development.
Following this, it will eliminate the one not matching the user's expectations.
The software then will search through the database for pre-development sale figures and post-development sale figures to identify the difference between two timeframes.
If the figures will return a reasonable percentage of profit following the associated cost for development, the software will demonstrate the property data to the user on a map with a
detailed breakdown next to it. The software can also make predictions for future property prices via reading historical data to outline how much money they can make in the following years.
Initially, the software will be focusing on the residential market and it will be available on PC, android, and IOS to make it more accessible.
It is said that the property market in Australia is growing too fast. Therefore, the home-ownership dream has become harder day by day.[1]
Although this is a sad fact for mom and dads, it creates an opportunity for the investors and developers who are looking for a development site to generate profit.
I was a partner of a development consultancy company up until 3 years ago. I have professional knowledge of experience the difficulty to identify a development site worth investing in.
There are so many consultants involved in the process. The analysis and decision are done by going through a significant amount of information within a very limited timeframe.
Therefore, high consultancy fees even before committing to the site, inaccuracy for the results due to the time constraints for analysis, and sometimes inconclusive results become inevitable.
This creates a niche market for MoneybyLand which takes multiple factors and makes a decision and most importantly displays the result on maps.
When we start talking about property development, there are multiple factors that we need to take into account.
You are looking for a rough diamond! Most importantly you are not the only person looking for it. Therefore, you need to act quickly and make an accurate decision within a very limited timeframe.
MoneybyLand comes into play in this scenario.
As a developer, you know how much money you can invest to purchase the property. You may know have how many properties you want to get following the development.
Based on the defined purchase value, and other criteria, the software will scan through the database and look for properties that were sold within the identified price range.
However, instead of returning all the properties,
it will return only the properties developed, subdivided, and sold separately as individual properties. Several main questions that need to be clarified about the process;
How does the software know if the site is developed?
How does the software know how much the developer paid prior to development?
How much was the resale value for the individual lots following development?
How is the feasibility study going to be conducted?
The general pattern of the neighborhood usually has similar property styles. This may include, patterns, sizes, orientation, etc. The software will be trained to identify the differences between a regular undeveloped site and a developed site.
The information relating to individual sites will be stored as attributes and communicated to the Geographical Information System who holds the other attributes for cadastral lots.
REIV (Real Institute of Victoria) and Institution like Consumer Affair Victoria provides historical information for properties, sale figures even rental information during the past years.[2] [4]
This dataset will be linked to the Geographical Information System via matching the address to the address attributes of the polygon data in the software.
Once the software identified a property matching the criteria, the REIV data will be searched to shortlist the recent sale figures for the individual lots,
the number of the dwelling within the developments, a safe construction fee for the development fee, government fees, tax, and other expenses will be calculated according to the current rates.
Finally, the software will return the profit by using the calculated return on sale and initial expenses, also outlining the other costs that will occur during the development.
Finally, the software will outline the possible profits in the future if you choose to keep the properties on your portfolio.
The software will identify the area. However, it will not nominate any specific property unless they are confidentially provided by the listing agent and they match with users’ search criteria.
The database will be updated regularly to accommodate the changes i.e. regulation changes, rate changes, new sale figures, etc. Therefore, each field requires a team to keep the software updated.
The biggest complication to be overcome is to refine the returned result in line with the local government changes affecting residential development.
For example, you may not develop the property or achieve the desired number of dwellings or types of dwellings following a regulation change in local or state government.
A legal team will be engaged to protect the company via agreements and disclaimers before using the software.
The following software will be required, Python, SQL to make the calculations. A specific tool named “scikit-learn” will be used to identify the property type by using the classification method of the tool. [5]
To demonstrate the result, ArcGIS will be used. ArcGIS is a powerful Geographical Information System tool that I used at university. They recently implemented a Python API to combine these two powerful tools to create, analyze, display, and share data geospatial maps.
Python is also a critical programming language for the development of this application for decision making. In addition, SQL is also important to communicate with the database.
The software will be running on the cloud server to reduce maintenance requirements and increase accessibility from multiple platforms.
First of all, it is necessary to understand how the development industry works, which I developed within the last 14 years. Secondly, to create a successful outcome, I will learn and improve my skills in SQL, Phyton and scikit-learn to cluster the information. In addition, ArcGIS knowledge is crucial to demonstrate the spatial data. [3] ] Besides, I need to improve my overall knowledge of statistics and economics to understand and refine the overall software and the way the results are calculated. Moreover, project management skills will be required to engage and manage other consultants like quantity surveyors, architects, planners, real estate agents, other experts in related fields to check the database and figures to make more accurate predictions.
Once the application is complete, external consultants will be engaged to develop Mobile apps for both Android & iOS.
Lastly, a legal team will be engaged for copyright, legal contract, checking against the recent laws and compliances, and preparation of legal disclaimers.
The current market heavily relies on decision making by relying on various consultants. This can be both costly and time-consuming.
If the project is successful at the end of the development stage, MoneybyLand will be one of the most dominant residential development platforms. It will also have the potential to expand into the commercial market in Australia as well as into the overseas markets. The businesses in real estate fields will want to be members of the platform to promote their listing to attract the developers. Also, individual investors will require a membership to be able to access the software and its features.