Why haven't there been personal finance apps or softwares that use regression modeling or A.I.?
What would they be trying to predict?  The value YNAB and Mint provide is objective truth about what you've spent. They can force you to think about the tradeoffs inherent in budgeting by showing that you've overspent one category, and making you decide where to find the money to cover it. They can call your attention to a credit card swipe that's larger than you intended, to a subscription you didn't intend to keep, etc. by just generally getting you to read and think about your transaction history and the sums of transactions per category and overall. Prediction doesn't really enter into it. One way to understand Mint's business model is as a service that collects training data for machine learning models that do try to predict things, such as how stock prices will move or whether users will click on certain ads. How would they make money from it?   They sell you the software for $100 (US example; could as easily be 100 Euros or 10,000 Japanese Yen).  You use it to make recommendations on your blog.  Your blog becomes rich from advertising.  They sold $100 worth of software.  If they spent $1 million in labor developing it, they're way behind.   Another problem is that the software would stop working and need adjusted periodically.  This is easy to do on a server but annoying on a PC.  And who pays for the adjustments?   Put both those things together, and it's a lot easier to do on a server.  Another advantage is that a server can get a better data feed as well.  Pay a premium for the detailed information rather than relying on public sources.  And people are used to renting server access where they expect to buy software once.   Another issue is that they are unlikely to beat the market this way.  Yes, AIs have done so.  But that's the latest AI, constantly adjusted.  This is going to be a previous generation AI.  It's more likely to match the market.  And we already have a way to match the market:  an index fund.   If someone had a brilliant AI, the best use would probably be to sell it to a fund manager.  The fund manager could then use the AI to find opportunities for its existing investors.  Note that a $10 billion fund with a 10% return that gives a .1% commission would be paying $1 million.  And that has no marketing or packaging overhead.  Think $10 billion is a lot?  Fidelity has $2 trillion. "Consumer facing finance is heavily regulated. You are liable for the recommendations you make; if they are based on a black box you risk problems when sued. It is difficult to explain in a court of law why a neural network came to a particular conclusion. It is much easier to provide advice (models) in the ""educated counterparty"" market. Not only do institutional investors in general expect to pay for a quality advice (consumers in general expect to get online advice for free) but the legal implications are different."
They are quite literally picking the taxi industry to be the winner and uber to be the loser. Uber provides more value to customers than traditional taxis and they have been successful because of it. Why should the government get to tell me I can't use an app to call a car to pick me up? It's utterly ridiculous. Google Finance and Yahoo Finance have been transitioning their API (data interface) over the last 3 months. They are currently unreliable. If you're just interested in historical price data, I would recommend either Quandl or Tiingo (I am not affiliated with either, but I use them as data sources). Both have the same historical data (open, close, high, low, dividends, etc.) on a daily closing for thousands of Ticker symbols. Each service requires you to register and get a unique token. For basic historical data, there is no charge. I've been using both for many months and the data quality has been excellent and API (at least for python) is very easy! If you have an inclination for python software development, you can read about the drama with Google and Yahoo finance at the pandas-datareader group at https://github.com/pydata/pandas-datareader. "Do you think that publishers haven't thought this through pretty carefully already? You can't *easily* make a thousand copies of a dead-tree book and give it to all your friends, or make it available to millions on the internet. (Possible? Sure. But not without a ton of work and hassle.) Publishers rely on customers buying paper books for their personal consumption, and figure that they might loan the book out once or twice - big deal. They still get paid.  Without DRM, publishers would basically be inviting the public at large to steal their e-book product. Marginal costs to copying a ""book file"" are nothing, unlike in the paper comparison, so everyone would do it if they could. Sure, the DRM is easy to hack, but the vast majority of the public isn't going to do that or know how. Just like for video games - the publishers know some folks will do it, but enough don't that it makes the product profitable. DRM is what creates the whole business model for e-books in the first place.  By the way, Amazon's DRM doesn't lock you into using the Kindle. The official Kindle app for the iPad works just fine, and I read many books with it." "As others have noted, in the U.S. a checking account gives you the ability to write a check, while a savings account does not. I think you know what a check is even if you don't use them, right? Let me know if you need an explanation. Personally, I rarely write paper checks any more. I have an account for a small side business, and I haven't bothered to get new checks printed since I moved 6 years ago even though the checks still have my old address, because I've only written I think 3 paper checks on that account in that time.  From the bank's point of view, there are all sorts of government regulations that are different for the two types of accounts. But that is probably of little concern to you unless you own a bank. If the software you have bought allows you to do the things you need to do regardless of whether you call the account ""savings"" or ""checking"", then ... who cares? I doubt that the banking software police will come to your house and beat you into unconsciousness and arrest you because you labeled an account ""checking"" that you were supposed to label ""savings"". If one account type does what you need to do and the other doesn't, then use the one that works." Put your money in a  big company automating their workforce and in 20 years you'll see above historical returns year over year.   Interest rates have some short term impact but long term technological improvements will be dramatic. "Thanks for the response.   I am using WRDS database and we are currently filtering through various variables like operating income, free cash flow etc.  Main issue right now is that the database seems to only go up to 2015...is there a similar database that has 2016 info?  filtering out the ""recent equity issuance or M&amp;A activity exceeding 10% of total assets"" is another story, namely, how can I identify M&amp;A activity? I suppose we can filter it with algorithm stating if company's equity suddenly jumps 10% or more, it get's flagged" "I'm currently using You Need A Budget for this. It lets you track spending my category and ""save"" money in particular accounts from month to month. They also have some strong opinions about how one should manage one's cashflow, so check it out to see if it'll work for you. It's neither web-based nor free, but the licensing terms are very reasonable." I  found that  an application already exists which does virtually everything I want to do with a reasonable interface.  Its called My Personal Index.  It has allowed me  to look at my asset allocation all in one place. I'll have to enter: The features which solve my problems above include:  Note - This is related to an earlier post I made regarding dollar cost averaging and determining rate of returns.   (I finally got off my duff and did something about it)