It’s unavoidable that much commentary around emerging technologies focuses on what might happen at some unspecified future date. But every so often, you can glimpse the unevenly distributed future in the present and make reliable predictions about where most industries are headed.

Unfathomable amounts of data are now being generated but less than one per cent of it is being analyzed. There are several reasons for that. One of the main ones is that big businesses aren’t in the habit of sharing their data sets with academics, start-ups, competitors, industry associations and governments.

But what would happen if businesses in a couple of huge industries chose – or were obliged to – loosen their grip on their data? Could that somehow end up benefiting those businesses, as well as their customers?

Take some inspiration from two industries that are already leading the way. Read on to gain an understanding of bank and insurance data collaboration in action.

Banking data collaboration

Open banking
Open banking is ‘open’ in the sense it allows people to share their financial data with a range of financial institutions. In the bad old days, it wasn’t clear whether you or your bank owned your financial data. Either way, your bank was neither obliged nor inclined to share that data with another financial institution offering you, say, a car loan or credit card. Nowadays, governments across the globe are now compelling banks to share their customers’ data (when the customer in question consents to having it shared).

Partly as a result of open banking, fintechs now pose an increasingly serious competitive threat to large, long-established banks. What’s more, open banking is just the opening salvo of an open-data war between incumbent behemoths and agile disruptors that will spread to many industries. For example, having forced the country’s ‘Big Four’ banks to provide their competitors with access to product and consumer data, the Australian Government now plans to make businesses in other industries do likewise. (Australia’s utilities and telecommunication providers are already preparing to compete in an open-data environment.)

Data-rich bank partners with start-ups
A world of liquid data isn’t necessarily bad news for long-established companies. After all, these companies typically have plentiful data sets and the money to pay clever people to analyze and leverage them.

Take, for instance, Westpac – a two-centuries-old ‘Big Four’ bank with around 40,000 staff and 14 million customers. It decided to drive growth through data collaborations with start-ups. After partnering with fintech-hub Stone & Chalk, data-sharing platform Data Republic and Amazon Web Services, Westpac launched an accelerator program called FUELD, and supplied selected start-ups in the program with anonymized bank transaction data. Any start-up that came up with a new data product got to sign Westpac up as a customer. The Stone & Chalk CEO noted, “Never before have start-ups had access to such a rich data set with which to rapidly develop, test and commercially launch a new product”.

And, as one of its executives observed, Westpac got to “solve customer and industry problems by leveraging the best data scientists in Australia and backing them to build new data businesses which address those real-world problems”.

Insurance data collaboration

Data-pooling
There is no shortage of attention-grabbing, data-enabled insurance products. Some, such as cheaper home insurance contingent on agreeing to have your dwelling fitted out with monitoring devices, are already available. Some, such as selfie-based life insurance, are expected to drop soon.

But it’s data pooling – that is, insurers making their data available to partners, subsidiaries and possibly even competitors – that insurance-industry experts typically get most excited about. Once insurers have access to larger pools of data, they are able to do things such as detect fraud more easily and price risk more accurately.

Bigger data pools and more powerful data analytics tools won’t be all upside for consumers, particularly those flagged as being high risk. But it will reduce costs for insurers, which should translate into lower premiums for many policyholders.

Data-rich insurer joins forces with academics
Australians are notoriously underinsured. In part, that’s due to the hassle involved in getting certain types of insurance. After all, who wants to spend hours filling in forms then wait up to a month to discover whether a life insurer will deign to offer you a policy?

With that in mind, insurer ANZ OnePath provided the Advanced Analytics Institute (AAi) at the University of Technology Sydney (UTS) with 10 years of data. It asked the UTS academics to investigate whether the life-insurance application process could be made easier. After unleashing their bleeding-edge AI and ML (Machine Learning) on the data, the boffins discovered that ANZ OnePath could safely reduce the number of questions it asked potential policyholders from 32 to 7.

A turnkey data-collaboration platform

These bank and insurance data collaboration examples are just the tip of the iceberg of what’s possible. If your organization hasn’t already got with the data collaboration program, it will probably soon need to. Data Republic’s secure platform makes the data collaboration process near frictionless by taking care of governance, privacy, legal, licensing and logistical issues. Read our case studies to learn more about how our secure technology enables data collaboration.