Risky business? Mobile banking, big data and cloud computing

By Jonathan Forbes | 4 March 2016

Mobile banking, big data and cloud computing share a number of common requirements, at the forefront is trust. Professionals in each field go to great lengths to develop, strengthen and retain trust in their offering. They know that if we do not trust their brand, people and products, then their solutions just cannot compete in the marketplace.

Any kind of transaction, be it financial or otherwise, has trust at its heart.

Brands must ensure the places where trust could be lost are secure and protected. And there is still much work to be done with some areas having a long way to go.

Mobile Payments

As the mobile payments market becomes increasingly open and competitive, trust will be more important than ever. High-speed connectivity, legislative backing and watertight regulation will be the norm. Competition will lead to lower transaction costs for both the consumer and the merchant. But we must have security, confidentiality and non-repudiation in place for each real-time transaction.

A major change to the way mobile payments are both made and perceived will come with the continued adoption of blockchain technology. Blockchain uses encryption techniques and distributed systems to provide a super secure ledger of digital transactions. They are very hard to tamper with and, once understood by the public, will give rise to a higher degree of trust that transactions using this technology are accurate, complete and up to date.

But there are still risks:

  • Commercial – due to loss of traditional transaction fees on payments, banks may be forced to recover losses by raising the costs of other services.
  • Barrier to entry – we will expect the same levels of security and control whether you are an established multinational or a start up.
  • Technology– that is risks in the technology itself. Despite being stress tested and ethically hacked at outset, a single vulnerability could affect millions of people if a weakness is found in a popular piece of software or device.
  • Information Security– transactions maliciously intercepted or manipulated and the loss of metadata such as encryption keys. Do we trust a centralized ledger such as that owned by a bank or is a distributed solution more attractive?
  • Platform – can we trust payments industry companies to work with each other so that it is easy to extract data or transition between different service providers?

Cloud Computing

The advent of cloud computing allows businesses to move IT spend from the traditional, build your server and pay upfront model, to renting capacity and pay as you go. The cloud gives startups and smaller companies access world-class services and capabilities they couldn’t afford to create on their own.

The cloud also provides innovative businesses with the opportunity to experiment in a low risk, low cost environment. Business ideas can be trailed quickly, scaled and moved to a capital budget if they work or binned if they fail. This economic flexibility allows entrepreneurs to enter and build businesses in markets that previously would have been too costly.

Risks in the cloud:

  • Information security – the physical loss of data and leakage. However, cloud providers simply can’t afford to make mistakes in this area. They rely on international data security standards, active defences and extensive governance to reduce these risks. Add to this regular security testing using such techniques as third party hacking and we have a system with levels of security and oversight that most companies couldn’t afford.
  • Platform – due to the proprietary nature of cloud services it may not be straightforward to move an off-the-shelf service from one provider to another. Do we trust the industry to work together to agree standards and protocols to allow this? Should there be a regulator?

Big Data

Big data is a relatively new term for a discipline that has been around for some time. It is a catch-all to describe a set of tools and techniques that help to solve problems arising from the storage, processing and analysis of large, fast moving, heterogeneous data. If you think this is new then speak to a particle physicist.

The amount of data we have to work with has increased exponentially thanks to rise of mobile devices that capture every click and swipe. We are constantly adding to a volume of data that can be mined to extract insights, target customers and forecast behavior.

There are risks with manipulating data sets:

  • Analysis risk – the conclusions reached by mining large data sets using machine learning can be incorrect and in some cases create more issues than they solve. Can we trust automated analysis based purely on data over the slower, more human processes that we are familiar with?
  • Legal risk – the rules on data privacy are going to get tighter. Eventually the insights collected via mobile devices may become subject to the same privacy restrictions. Is it possible we’ll see cases of mis-selling resulting from automated recommendations or decisioning systems? In short, do we trust machines to make the right choice for us?
  • Participation risk – will there be a point where the drawbacks of sharing one’s data will outweigh the benefits? People will only accept a certain level of intrusion and the return must be at least commensurate with the risk. If this is not done properly we’ll see a withdrawal of willing participation. Are we confident that large companies with ‘skin in the game’ of marketing and commerce will not abuse a position of trust?

Advances in technology, methodology and process will always need a level of trust from those who it has an effect on. There are potential risks in all of these fields but they can be mitigated to allow business, individuals and the larger economy to reap the benefits of innovation.

By Dr. Jonathan Forbes is Chief Architect at Aquila Insight.

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