The banking system is about to be changed forever, and your industry might be next.

That’s the message of a massive new piece in the Sydney Morning Herald, which circles around to some recent demands for banks to release consumers’ data (so ordered by the Government earlier this year).

“If customers were more willing to shop around, the argument is that banks would have to compete more fiercely, through sharper interest rates, lower fees, and better service,” the piece argues.“Open banking” is the broad term the industry uses to describe all these changes. But as the piece explains, the ability for consumers to move their data freely between institutions is really just the precursor to a wider change that could see similar things happen in a variety of industries.

Of course, security is a massive issue. And as the SMH piece points out, consumer groups are concerned about “profiling for profit”: “targeting consumers who take a long time to repay debts, thereby racking up a big interest bill”. But it’s just the beginning:

“As the banks’ data vaults are prised open, expect to see even more financial services players vying for your business in the digital world.”

In other news:

We know we’re drowning in data.

The digital platforms we have access to now – Twitter, Netflix, etc – are continuously creating new information. They use algorithms called “streaming algorithms” to calculate things like trending topics, and more businesses are using them.

But they’re imperfect because they ignore a lot of data. Now, scientists have developed a better way of analysing this information: and it could actually impact smaller businesses that are struggling to deal with huge data sets.

The actual heart of the algorithm is complex, but as Wired explains, it enables businesses to analyse data and keep it around for further analysis. For a lot of businesses that’s huge, because it means you can use all your data instead of a portion of it.

“This new work shows that given the right way of encoding a lot of information, you can end up with the best of all possible worlds: You can store your frequent items and recall them, too.”

Meanwhile, MIT researchers have come up with a new way to crowdsource data analysis.

The method of doing this is actually a collaboration tool called FeatureHub. Data scientists use it to log on to a central site, then give recommendations for a particular data set. Software on the back-end tests those recommendations and then implements the best ones.

It’s working, too: in tests the tool has chosen specific suggestions from a group of examples, that researchers already knew were efficient. It’s also choosing them faster:

“I do hope that we can facilitate having thousands of people working on a single solution for predicting where traffic accidents are most likely to strike in New York City or predicting which patients in a hospital are most likely to require some medical intervention,” says Micah Smith, an MIT graduate student who helped develop the project.

Worth a read:

The internet of things is more than doorlocks and thermostats. The head of a business-based IoT platform says its customers are saving up to 20% on their electricity bills – and it’s just raised $23 million. AFR.

China is seeing a bunch of those bike-sharing services pop up. But the real value isn’t helping people get around the city – it’s in the data they collect. AFR.

Until next week.