Data is increasingly recognised as a major asset in banking and underpins strategies to provide digital banking services. Future Banking talks with HSBC’s global banking and markets’ CDO Europe and head of data quality services Hany Choueiri about the growing importance of data in digital banking and in helping “operations” keep pace with trading innovations in inter-bank trading.
Future Banking: What can you tell us about the new role of chief data officer (CDO) in banks? Is your own experience in that role to date largely what you expected?
Hany Choueiri: This is an interesting question. It's clear that there is significant variance in the CDO role across the industry. This is indeed surprising when you consider that many of the leading institutions face similar challenges and objectives.
In my view, there are a number of contributing factors, not least the fluid nature of data. Other contributing factors include the size, scale and complexity of the organisation; the current level of maturity of data management; and the personal influence of those sponsoring the CDO organisation.
My view is that the The sheer scale of governing this crucial asset has lead organisations to ensure they set stakeholder expectations by drawing out and communicating clear CDO boundaries including explicit roles and responsibilities. We have been very fortunate, and have had strong leadership and strong business support for the CDO organisation within all areas including the global banking and markets (GBM) business.
This has helped us to articulate a persuasive data vision that has been led by our group chief data office, which has led to the formulation of a data policy, data standards and a comprehensive data-quality framework. The 'data journey' is never an easy one, but our well-established organisational structure with good GBM regional representation is proving to be the right model for us.
To answer the second part of your question, I would say "yes" only because I was fortunate enough to be close to the original formation of the CDO organisation.
Having said that, we are continuously adapting our size and scale to ensure we are as effective as possible, and have a significant portfolio of work within our remit, which is very exciting, empowering and, at times, a little daunting. I would like to close this question by saying that, without exception, everyone feels that we have a real opportunity to make a huge difference and, daunting as it may be, everyone is rising to the challenge.
Data is not going away. It continues to be talked about, whether it's the volume of data, or the speed at which it's growing or the different varieties and types of data and information that is being aggregated, compiled or analysed. As we move from an era of automating transactions to the era of data, what can you tell us about the information challenges that banks face around understanding and creating intelligence from information?
There is still a misconception that the volume of data is a barrier to success; in my opinion, this is no longer true. Technology has moved on in leaps and bounds with parallel commodity computing easily available at everyone's disposal.
What is more challenging is the meaning of data, and how that changes and evolves over time. Data itself is not static and to truly harness it over longer periods of time requires a framework that enables that same data to be interpreted - so we can compare apples with apples. The financial industry is unique in that way; it is more dynamic than most other sectors.
Areas such as regulatory compliance, customer insight and real-time operational management have benefitted by improving analysis of big data. How can banks set about improving the value of big data; meaning, create better understanding, insight and wisdom from all this data to better protect the bank or find new customer segments to increase customer revenues?
There is no doubt that the big-data revolution is here to stay. However, there is some education needed to avoid a 'big-data bubble'. I hear many peers in the industry see this as a solution to all their data-related problems - it's not. I would say used in the right way, big data equals big rewards.
The danger is where organisations embrace big data in lieu of the fundamentals of good data management; they go hand-in-hand.
For all the increasing amounts of data collected, having clean data is the critical bedrock to good data analysis. Flawed data leads to flawed discussions, whereas clean data leads to confident decisions and banks need to invest in a data infrastructure that provides reliable information. How, in your view, can banks ensure data is clean?
There is a little bit of a chicken and egg situation with this one. Recent advances in analytics and improved data-management tools are coming to the rescue. The most effective tools are those that allow you to bridge meta-data with the data itself. For example, linking a data policy to a data standard and enforcing a standard via a data-quality rule.
The advantage of such a holistic framework is that it can be kept up to date with changes. Sustainability of any data solutions should always be a key consideration.
The faster you analyse bank data, the better its predictive value. Since there is time value to banking data, how in your view can banks accelerate the analysis of big data in real time?
It's vital to get the basics right. Instil common identifiers, create centralised reference data systems and embrace industry standards such as legal entity identifiers (LEIs).
It is still possible to benefit from trends and insights but simply throwing data into big-data lakes, but the ultimate winners in predictive analytics will be the ones with the better data baseline. They'll have the confidence to click that button just that little bit faster than you.
Hitherto exclusively manual processes in banking are being digitised, leading to the emerging concept of the digital bank. Does this have relevance in investment banking as well as retail banking?
Yes, but the opportunities and challenges do differ between retail and investment banking in the digital space. This raises another important point regarding the benefits of internal digitisation, which are very significant in investment banking. There are external and internal-facing aspects of digitisation. Internal-facing digitised services can make the difference between a profitable and a not-so-profitable business line. These processes can significantly influence the bottom line, especially in types of business that have very small margins.
The rapid growth in equity derivatives trading and inter-bank trading is constrained by the ability of operations to keep pace with trading innovations. Solving some of the complexities in documentation, as well as developing some standards, is key to moving this market to a more automated environment. For you, as a CDO, what are the key problems right now for institutions looking to mitigate risk and ensure adherence with the most pertinent regulations?
My answer to this may be surprising, but it is almost that the reverse is true. Regulations have brought about positive change with a number of standards implemented already, such as LEI, and a number of other standards in the pipeline.
Regulators and financial institutions are recognising the value of this. Without agreed and global standardisation the regulators themselves cannot easily aggregate the data. This is essential for risk monitoring for example. Standardisation leads naturally to automation, and automation to improved risk mitigation.
One final thought on this, globalisation has certainly increased the size of this challenge. No longer can countries or regions develop standards in isolation. Hence, the time it takes to develop these globally coherent standards takes much longer than it used to. On a positive note, regulators and financial institutions are actively participating in industry and governance forums to the benefit of all.