Real-time risk management in a consumer driven open data market

The other day I went to my local grocery store and noticed even they had implemented the ability for me to pay via ApplePay. Australia is undergoing a revolution – particularly when it comes to payments.

We are on the cusp of:

  • the introduction of a National Payment Platform (NPP) that will enable organisations to offer real time payment via various channels such as SMS or chat bots.
  • A data sharing scheme to be implemented in Australia by the end of 2018.
  • For those with data subjects in Europe, the introduction of the revised Payment Services Directive and the EU General Data Protection Regulation.

All of this will impact organisations in many ways, particularly within 3 specific areas:

  • Customer expectations will change
  • The enablement of data driven product innovation
  • Having multiple Regulators locally and globally monitor compliance

To remain competitive, this fast-paced data-driven innovation will need to be balanced with ensuring consumer information is accessible and managed in accordance with consumer expectations whilst managing risks in real-time.

Customer expectations will change

Customer expectations will change and it will start with the introduction of the NPP in Australia. Customers will expect to be able to make a real-time purchase of anything using faster and easier technologies that they are already used to such as chat applications.  If organisations choose not to evolve, they will be left behind.

Customers will also be savvier with data. They will understand their rights to not only have access to and port their data, but also to question decision-making. Customer support functions can expect an increase in the number and complexity of questions from customers regarding how their information is being used.

Enable data driven product innovation

Whilst opening data sets is a scary thought, it provides the opportunity for organisations to create new services that provide a better customer experience. Organisations will be able to access each other’s data sets to augment or create new services. This will lead to cross-pollination of products and services across industries. How we pay for electricity today may not be how we pay for it in the future.

This innovation will not come without risk exposure– organisations will need to review where data sets are located and potentially consolidate them, whilst ensuring that various data laws regarding data sovereignty, privacy and data protection are being adhered to. The speed at which transactions occur also mean there is a higher risk of fraud as financial institutions may not be able to look into suspicious transactions in real time.

From a compliance-centric to a consumer-centric organisational culture

Compliance will initially be a key driver for change for incumbent organisations. These organisations will need to undergo a transformation internally to support the new open data economy. In particular, there will need to be a shift to a consumer-centric culture within organisations when using data if there isn’t one already. This is because for some of the laws introduced, the consequences are beyond just penalties; under the EU GDPR for example, a Data Protection Authority can instruct for processing activities to cease, such as customers purchasing online – hitting an organisation where it hurts most.

What to do?

These impacts will require significant investment initially for organisations to transform – however, the entrance of ApplePay into the Australian market has already heralded a new era for data management transformation to keep up with the benefits of speed, convenience, ease of use whilst ensuring data protection.

Solid privacy and data management program to support open data services

The open data economy will flip traditional data management practices within organisations on their heads. Where traditionally data management would have been inward focused, increased transparency required by the open data economy will mean organisations will need to implement an open data framework that is underpinned by a strong privacy program which is technology agnostic. Timothy Pilgrim (Privacy Commissioner) has reiterated this point that a successfully data driven program will need to be supported by a solid privacy program.

Such programs will in particular need to focus on:

  • Assessing privacy risks of new technologies such as algorithms, artificial intelligence and chatbots
  • A practical strategy for obtaining and managing consent across an organisation’s products and services beyond ticking a box
  • Access to information considering third parties, customers as well as internal staff
  • Third party risk management
  • Open data set and API management
  • Quality and accuracy of data to be shared and disclosed.
Customer education

Consumers will have the power to do more with little time to learn of the consequences across many different channels. Given the projected real-time economy of transactions, consumers will be also learning in real-time the need for the appropriate collection and use of their information. It is important to define clear responsibilities for ensuring data privacy by both the organisation and customers, as customers may pose a risk to themselves by how they handle their own information.

Machine learning to combat real-time risk

Real-time risks means real-time risk management.  Robo-risk managers will be required to help manage risk in real time. This could mean identifying a person on a blacklist or verifying either an identity or the ability to pay back a loan – transactions will need to be stopped in real-time for investigation.

There is no doubt that organisations will be undergoing a major transformation in these exciting times that will provide a faster, more convenient and easier way to create new  products and services through data-driven innovation. This means that it will become imperative for organisations to have a strong framework to manage the identities as well as the privacy of their customers.

Real-time risk management supported by a technology-agnostic open data framework will help ensure that organisations are balancing the risks and benefits from data driven innovation.

If you do have any questions regarding how an open data framework could transform your organisation, please contact Marta Ganko.


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