Written evidence submitted by Experian (BIG0022)
1.1. Experian is a leading global information services company, providing data and analytical tools to clients in more than 80 countries. The company helps businesses to manage credit risk, prevent fraud, and automate decision making. Experian also helps individuals to check their credit report and credit score, and protect against identity theft. Experian has a dedicated data analytics team and provides clients with insight and understanding.
1.2. Experian plc is listed on the London Stock Exchange (EXPN) and is a constituent of the FTSE 100 index. Experian employs approximately 16,000 people in 41 countries and has its corporate headquarters in Dublin, Ireland, with operational headquarters in Nottingham, UK; California, US; and São Paulo, Brazil.
2.1. Experian’s default position is that the world of data is undergoing a transformational change. This world is moving fast as data becomes more accessible, attributable and analytical:
2.2. Consumers remain nervous on how their data will be used and protected but there has been a gradual shift to more openness;
2.3. Big data can now be seen as extremely useful, thanks to improvements in technology, data storage and processing, computational and statistical methods;
2.4. Big data analysis is seen into virtually every field: science and academia, financial services, law, industry, government;
2.5. Along with opportunity comes significant risk – for organisations and consumers. On a technology level, organisations need to tackle key challenges of data deluge, data quality and consistency and the need to link data together from all kinds of channels;
2.6. For consumers, Big Data needs to demonstrate value – and there are always costs related to loss of privacy to grapple with;
2.7. Government needs to set out a clear path, working with organisations and consumers, to ensure that we have a regulatory, legislative, technological and educational approach to Big Data that allows for the rapidly evolving nature of this data.
3.1. The opportunities for big data, and the risks
Experian’s default position is that the world of data is undergoing a transformational change. This world is moving fast as data becomes more accessible, attributable and analytical:
• Long-held expectations around data are changing and being challenged
• Sitting behind the surge in digital services is data and therefore data is of increasing importance to all organisations, both D2C and B2B
• It also has a high-profile position on the agendas of Government and Regulators
• Consumers remain nervous on how their data will be used and protected but there has been a gradual shift to more openness
3.1.1. Big Data Opportunities
It is undeniable that big data is continuing to transform all industries. But, there are two general points worth making which have enabled organisations and consumers to exploit the value in big data:
a) Technology Enablement. What’s really different in the Big Data age is that there has been a transformational change in both the amount of data generated by all of us, and in the cost of storing that data for future processing. But it is only with substantial changes in technology that organisations can more effectively process the vast volumes of data being generated.
b) Data Insight and Analytics. Big Data in itself does not create value – for organisations or consumers. The promise of Big Data really lies with the advances in insight and analytics that enable us to find patterns and extract value from the volume and variety of data that is now an integral part of our society. So, when people talk about “Big Data,” what they should really be talking about is “Big Data” insight and analytics.
Big data analysis is now found in virtually every field: science and academia, financial services, law, industry, government. Modern data analysis is revolutionising previously held ideas, enabling us to drive useful insights from huge volumes of data now available in every field:
But, all of this value, of course, does not only depend on having the data, but there must also be a wise application by the owners and analysts of the data: asking the right questions, designing tests, drawing conclusions from the data collected and applying these findings for positive outcomes.
3.1.2. Big Data Risks
Along with the huge opportunities that Big Data offer for organisations and consumers, there are significant risks – in both the nature of the data itself and the ability of society to drive value from this data.
For organisations:
For organisations, the key risks and challenges of Big Data we see are as follows:
• New channels and new data which are available for decisioning purposes are creating significant data deluge, overwhelmed by the volume of incoming data and consequent challenges for integration across organisations
• Data quality and consistency. At the same time, data quality and consistency issues are also hindering organisations' big data initiatives. With the extent and variety of data coming in, organisations' big data management capabilities are being put to task for ensuring the data is reliable and accessible for its given purposes – and many are creaking!
• Complexity of interactions between channels is increasing exponentially and businesses struggle to navigate this. They are struggling to transform Big Data into Agile and Actionable Insight and few have a strong capability when it comes to using cross-channel or cross-device data for real-time decisioning and personalization. A key challenge for them here is in connecting offline data to online silos.
• Lack of Big Data skills. Since big data is still a young field, it is not surprising that many organisations are finding it difficult to obtain the skills they need. There is a shortage of analytical and managerial skills necessary to make the most of Big Data.
• Extracting business value. At the heart of all this is Value – big data in itself is of no use unless it is generating benefits and providing relevant and timely insights to a particular market problem, client requirement or customer need.
• Data governance and compliance. Any organisation that uses Big Data is facing a “perfect storm” as the issue of data governance and data compliance becomes highly visible through a combination of negative press activity; increased regulatory concerns; and the awakening of consumer attitudes to data privacy in general and to the uses of their data in particular. Brands have to get it right. In order to alleviate consumer confusion and concern, a growing number of companies are moving towards “privacy by design”, becoming overtly transparent around data usage and value. In this context, whether it’s Big Data or not, provenance of the data right back to origin will be key to generating trust. Understanding complex consumer attitudes to use of data will be crucial.
• Data security. Big Data has also changed the nature of the game when it comes to protecting data assets, and made it harder too. In this scenario, analytics have an increasingly important role to play in data security and are already transforming intrusion detection, differential privacy, digital watermarking and malware countermeasures. Strong security practices, including the use of advanced analytics capabilities to manage privacy and security challenges, can set businesses apart from the competition and create comfort, confidence and trust with customers and consumers.
• Legal implications of Big Data. Big Data’s increasing economic importance also raises a number of legal issues, especially as data is fundamentally different from many other assets. Data can be copied perfectly and easily combined with other data. The same piece of data can be used simultaneously by more than one person. Questions about the IP rights attached to data will have to be answered: Who “owns” a piece of data and what rights come attached with a dataset? What defines “fair use” of data? There are also questions related to liability: Who is responsible when an inaccurate piece of data leads to negative consequences? Such types of legal issues will need clarification, probably over time, to capture the full potential of big data.
So, organisations need to take a privacy-led approach to customer data collection to ensure that consumers are more loyal to, and willing to share data with, brands they trust. Once consumers trust you with their data, and they feel that they are getting a “fair” exchange, you can leverage this for the benefit of all. Value needs to exist in a bidirectional model between organisations (including government) and consumers and your users.
For consumers:
The power of data is real, but we must remember that that are always costs associated with Big Data, and these costs do include some degree of loss of privacy for consumers. This manifests itself in several ways:
• Data vulnerability. The proliferation of data has left consumers feeling exposed and vulnerable to the way their data is being used. As they think about the issues and learn more they don’t always get more reassured – in fact it makes some more worried because they were previously unaware of how much data is collected and used
• Transparency and trust. Consumers are increasingly demanding transparency and trust from the brands they engage with. The tech-savvy consumer is willing to sacrifice some privacy as a trade-off to the benefits of digital technology and personalized marketing, but under their own preferences and conditions. Increasingly, consumers want to be informed about data use and value the ability to easily opt-in or out at any point in time
• Ensuring understanding of data usage. A key risk is removal of consumer consent to use data because consumers don’t understand what their data is being used for and why. This relates back to the Value point above but organisations will need to ensure educate and ensure that consumers understand what their data is being used for – and the benefits to them and not just to organisations. Currently data concerns dominate the conversations rather than data opportunities. More needs to be done to explain to consumers the benefits of data flowing between businesses rather than the risks.
3.2. whether the Government has set out an appropriate and up-to-date path for the continued evolution of big data and the technologies required to support it
The rise of Big Data has created a number of challenges for Government – the wider use and dissemination of Big Data for public good, the skills required within government to champion and educate on Big Data (to citizens and to other government bodies and local authorities) and the technology to enable Government to lead in creating value from Big Data.
• Regulation. The data explosion has been accompanied by a clear government and regulatory desire to provide greater consumer control and transparency over data use, and encourage free movement of data to help increase competition in markets deemed to be failing the consumer. However, this data explosion has, at the same time, led to multiple sources of developing and emerging regulation with both the regulators and industry struggling to keep up, particularly with the evolving digital data marketplace. We see a global trend towards governments and institutions developing more codified and extensive protections for consumers. It will be vital that regulation does not stifle the further growth of Big Data and technologies at UK level. Understanding where flexibility in law is required will be vital to ensure that the trend towards growth in this area can continue. The recognition in legislation that use of Big Data may go well beyond the initial use case needs to be recognised.
• Government’s role in consumer education. Further work by Government to educate consumers on data, whilst supporting innovation and start-up activities, would be a positive method of ensuring that there is the correct environment for growth, and consumers feel empowered to understand and appreciate the move towards big data use. It would be beneficial for the Government to work with commercial organisations to figure out how best to explain to consumers the benefits of data flowing between Government, businesses, citizens and consumers rather than the risks.
• Digital data. As an ever larger amount of data is digitised and travels across organisational boundaries, there is a set of policy issues that will become increasingly important, including, but not limited to, privacy, security, intellectual property, and liability. The Internet of Things will present further regulatory challenges – with a complex mesh of people, devices, systems and network connections, as well as different locations where data is stored or transported it will be essential that each part of the system can only access, manage or share data that it’s allowed to.
• Technology. Government technology to enable the efficient use of Big Data will need to evolve and adapt more quickly than it does so at the moment. Technology will be as important as policy in addressing Big Data security issues and there needs to be a joined up approach to this across Government.
• Open data. Good work has been done on the path towards the opening up of Big Data and its democratisation through open source solutions and APIs and through business, government and social movements to release non-personal data into the economy. Whilst part of Government have been embracing this trend, there is a lack of a clear joined up directional policy around open data and the technology to facilitate and deliver value from this. Data.gov, the Digital Catapult scheme and the Open Data Institute are gaining support from both government and organisations to promote data sharing in order to drive greater innovation and competition in existing markets.
• Internet of Things. Technology that controls physical activities and the Internet of Things will continue to get a lot of consumer attention. Government and businesses must plan thoroughly for the good - and bad - potential consequences of these capabilities. Government have a role in setting industry wide standards for IoT data transfer and exchange and technology – and regulation needs to be flexible enough to deal with rapidly changing technology and use cases that we don’t even know about yet!
3.3. where gaps persist in the skills needed to take advantage of the opportunities, and be protected from the risks, and how these gaps can be filled
There are several areas where there are well documented skills gaps to enable the potential in Big Data to be exploited and the risks minimised but what can/should be done to address this:
• Data Science analysts. The problem is not necessarily finding people who are technically capable (since many analysts have coding skills). What is difficult is finding people who can conduct the coding from an analytical perspective – who will not only ensure that results are reliable but also relevant to the commercial aims they have been set. To address this:
• Analytically savvy business managers. There is a skill gap amongst business managers and in the make-up of senior management teams in being able to translate results from Data Science teams into meaningful implications for the business. More is clearly needed to ensure that these skills are developed and instilled into the business over time as a necessary part of the organisational structure:
• Data protection officers, data security experts, Big Data legal skills. There are a number of potential skill gaps arising in the area that is most crucial to the sustained success of Big Data - data regulation, legislation and security. For many organisations, existing data governance functions are not sufficient to cope with growing data requirements and increased regulatory concerns – let alone the legal and IP issues associated with digital Big Data. With the support of Government, organisations will need to wake up pretty quickly to the needs here and work towards filling these skill gaps in time for pending EU legislation. We’re not sure there is any quick fix here as there is a critical shortage of suitably qualified DPOs in Europe and there is going to be fierce competition to train, retain, recruit these individuals.
3.4. how public understanding of the opportunities, implications and the skills required can be improved, and ‘informed consent’ secured
It is important that consumers and wider public are informed and educated around the benefits of data use to make sure that they not only understand their rights in relation to data protection and privacy, but also appreciate the many incremental benefits that could be felt in a more innovative, data led society. This may mean earlier stage education in schools, and an obligation on companies and market participants to provide clarity in notifications that are provided to the public around their data being used. It will be key to focus on the benefits of data flowing between government, organisations, citizens and consumers rather than the risks.
However it is important not to create a sense of fear in the use of data with the public, and by empowering citizens with the skills of understanding and appreciating their data use and the evolution of new technologies or applications, they will themselves be able to make the appropriate decisions on use.
3.5. any further support needed from Government to facilitate R&D on big data, including to secure the required capital investment in big data research facilities and for their ongoing operation.
There are immediate areas where further support is needed from Government to unlock the value of Big Data:
• Research facilities. Whilst there are moves to establish R&D facilities’ to enable the analysis of sensitive Big Data, many of these are only open to academic or other government institutions. It is only by Government, academia and commercial organisations working together that we will start to drive a unified message to the consumer around Big Data’s benefits to society. Several larger commercial organisations have experience in setting up and running successful R&D facilities within which they’ve had to grapple with many of the issues and risks identified above.
• Collaboration between Government and commercial organisations. As a key risk of Big Data is around consumer consent and ensuring a transparent, but non-onerous way for consumers to understand what their data is being used for and why, there is a clear benefit in Government and commercial organisations collaborating to solve for this e.g. using federated identity capabilities to verify the consumer up front, and then allow consumers to set permissions over data use, and grant permission when new requests are made. This needs to be designed from the consumer and the commercial companies’ perspective to ensure it works for all parties – so should probably be an industry led initiative with government backing. The risk here is that without a clear and agreed approach presented it becomes very difficult to implement.
September 2015