Chip – the Algorithmic Savings App

I came across an App, while aimlessly surfing, it’s an algorithmic savings plan. I think that is the best way to describe it, or at least its a way to describe it. The point of Chip is that when you sign up you get a savings account, held by Barclays Bank PLC, and the app figures out how much money you could save (and not miss), and when. So every now and then Chip determines, via the magic of algorithms, an amount of money that you could save and not miss too much.

On the default savings rate it seems to be similar to the cost of a large latte and a chocolate bar. Chip then congratulates you your saving, you can back out if money is short. If you leave it to its own devices that sum of money disappears from your nominated current account to reappears in your new savings account.

Am I Using it?

Yes, I have signed up for the app. I thought that in general this isn’t a bad way to save. I have standing orders for saving a modest sum of money every month but I always thought I could do a little more. What Chip does is allow that to happen in a flexible way, no need to commit to a particular amount at the start of each month, and no need need to remember into get on internet banking to do it manually. Chip does it for you, and if you are a bit short one month you can stop the transfer. Great if your income is irregular and saving a fixed sum might be tricky.

Similarly, should you suddenly find you need money, you can easily get at the funds out of the savings account. This in my mind this makes this a sort of slush fund. Which you can dip into should need to, or are tempted to. I still think longer term savings are also a good idea. Putting a little away somewhere harder to get at, and also make sure you have a pension as soon as you can!

Saving Made Entertaining?

Chip makes saving about as entertaining as it probably could be. You get congratulatory memes when you save, and Chip is well chipper, and encourages you along your savings journey. The chipperness might drive some users slightly mad, but I think they got the balance about right. It does seem to work, or at least it does for me, after 103 days using the app I have saved slightly over £200. Which, although not a massive sum, is £200 more than I otherwise would have. I set a goal, rather arbitrarily, of £1500. Weirdly Chip seems to report that I am always about 95 weeks away from my goal… but whatever, I can see the amount saved go up and the amount left go down. Thats progress.

What About My Data?

In order to do all this Chip needs read-only access to your bank account. Now that is not data that should be handed over lightly. Sure your bank knows it, but your day to day transactions is very personal data. It provides a lot of information about how and where you spend you money, and thus who you are in a way. Chip is regulated by the ICO and they encrypt the data.

Chip has a data control licence – you’ll find us on the ICO register – and we always act in full compliance with the Data Protection Act. Your online banking login details are protected using 256-bit encryption and Chip does not store your data.

Chip FAQ

This was the part of the process that made me wince a little. However, if they are going to calculate a savings rate then they need (at least some of) this information. So, if you want in, this is the price you pay. I wanted to have a more detailed look at what and how they use my data. So I asked them a few questions, but they are yet to reply…

The Expression of Emotions in 20th Century Books

A new paper is out (PLoS One so free to all), lead by Alberto Acerbi (Bristol Uni), and co-authored by Vasileios Lampos (Sheffield uni), myself (Durham Uni) and R. Alexander Bentley (Bristol Uni). Its a really fun paper looking at the changing pattern in the use of emotion words in the English language during the 20th Century. We make use of Google’s Ngram data. Google scanned approximately 4% of all books and generated a dataset of yearly world frequencies. We mined this dataset to extract the changing frequencies of emotion words throughout the 20th century.

In the data we can see the frequency of words expressing emotions such as anger, fear, joy, sadness, and disgust changing in line with historical events. Large social/cultural events like the World War II, the roaring 20s and the swinging 60s all show up as frequencies changes of words. Interestingly the World War I doesn’t seem to appear in the data, however the Great Depression in the 1930s does. We also expected, due largely to cultural stereo typing, that US books would be more emotional that UK. This is supported by the data, but the split occurs much more recently than we thought it might.  Generally throughout the 20th century the frequency of emotion words has been declining, with one exception, fear. Could that be linked to the climate of fear that has developed during the latter half of the 20th century?

Figure 2. Decrease in the use of emotion-related words through time.
Difference between -scores of the six emotions and of a random sample of stems (see Methods) for years from 1900 to 2000 (raw data and smoothed trend). Red: the trend for Fear (raw data and smoothed trend), the emotion with the highest final value. Blue: the trend for Disgust (raw data and smoothed trend), the emotion with the lowest final value. Values are smoothed using Friedman’s ‘super smoother’ through R function supsmu().

The paper has been really well received in the media, Alberto was interviewed for BBC Radio 4s Material World by Adam Rutherford. Alex and myself were interviewed for NPR.

Articles:

Word Diffusion in Climate Science

Our new data mining and modelling paper is out today, “Word Diffusion in Climate Science“. Investigating the diffusion of climate science words in the Google ngrams dataset. We make observation that there is often a disjoint between the findings of science and the impact it has in the public domain. This existence of a disjoint is particularly significant when it is important the science reaches the public. Our hypothesis is that important keywords used in the climate science discourse follow “boom and bust” fashion cycles in public usage. If these cycles are linked to the science leaving the public eye then perhaps scientist need to think about they can do to ensure important findings reach as many people as possible.

Durham university press release (including a rather-too-big-for-my-liking picture of me).

Off to theODI Open Data Hack Day

Being something of a fan of big data the opening of the ODI comes with great interest. I am about to head down to London for their Open Data Hack days. Not exactly sure what to expect, haven’t been to a hack day that is like this exactly, but I am looking forward to seeing what comes out of it. Just getting a sense of what they are about will be worth the trip. My own use of big data thus far has been more with close data sources that have been created to answer particular questions. Not including Google ngrams, which is very much a large open data source.

I am however rather beginning to think that this wasn’t really a good time to run a much needed update on Mac Ports. It better be finished fairly soon.