Solving the Problem

My Solution

     My solution deals with the problems people face when purchasing a house, specifically the struggle to find the right deal and the best time to buy. I learned previously that mortgage interest rates can fluctuate on a weekly basis, which is incredible when you consider that these mortgages are a financial burden for decades for many buyers, where the difference of a fraction of a percent can mean thousands of dollars saved in the long run. Also, housing price fluctuation can result in buyers paying for overvalued property, only for it to drop in value soon after purchase following an inevitable price cycling, as was seen quite dramatically in 2008. Thus, my product would extract and analyze multiple figures of the buyer's housing market, the most important factors being average interest rate and average housing cost in the area where a user desires to buy. The web service would then compare these rates to historic values over different time scales (e.g. weekly, monthly, yearly, and decade averages) and determine if current trends demonstrate a good time to buy or not, albeit roughly. This could be a powerful tool in the hands of potential home buyers, because most buyers' primary source of market information is their realtor, who has a conflict of interest when reporting whether or not markets are currently buyer-friendly. By parsing this widely available data and serving it to consumers in an easily digestible format, my product would hopefully prevent severe cases of overpaying for housing and potential financial ruin. Additionally, I recognize that I do not have an expert understanding of the housing market and price bubbles, so further research is needed to determine the best way to analyze current data and compare it to previous figures for the lowest likelihood of over paying.

Comments

  1. John DillonFebruary 9, 2020 at 4:19 PM

    Hi John,

    Great solution! I really like this approach and your proposed technological solution. I agree that this wouldn't be all too terribly hard to do so long as you had access to someone who could build the tool, scrape data and build some form of analytic implement.

    Aside from this, I'd be curious as to how you intended to make money from this. There would be a good bit of upfront cost in paying a developer to make this (upwards of the tens of thousands potentially), and it may take a while before any revenue came in. These would be things I'd recommend you keep in mind and evaluate as you progress. I'm curious to see what you can come up with!

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  2. SkylarFebruary 9, 2020 at 6:23 PM

    Hi John, your solution is so well described and complex! I can definitely see a product like this flourishing in the market. I would say overpaying is an opportunity that many home owners have experienced. I am curious to know how you would go about implementing this. It is a great idea in theory but it sounds so complicated. Good job!

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  3. Miguel LucasFebruary 10, 2020 at 1:22 AM

    Hi John, after reading your solution I felt that this can be a very big thing in the app store for a huge amount of individuals. For example, not only will it work for home buyers, but it will work for realtors too! It would make their job a lot easier and cheaper by choosing a house at a cheaper rate. What this would do is cause them to sell the house at a cheaper rate since the initial buying price was way cheaper. This will almost create a ripple affect that should push for a healthy market. You can make a lot of revenue off this app, I feel like. You can create a subscription type of account that charges like $50 a month or so to save them thousands in the long run!

    I want to be a real estate agent in the future and I can say that this would be great for finding deals! Hope this actually happens!

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