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How Is Big Data Shaping Banking?

We sat down with Sreeram Iyer, Chief Operating Officer, ANZ

20Dec

Ahead of his presentation at the Big Data & Analytics Innovation Summit in Singapore on March 1&2 2017, we spoke to Sreeram Iyer, the Chief Operating Officer for ANZ Bank’s Institutional Banking business.

As the Chief Operating Officer for Institutional Banking, Sreeram is responsible for supporting ANZ’s business strategies across several countries; generating value for customers through Technology and driving Operations in all the regions of ANZ's business. His portfolio includes Institutional Operations, Property, Transformation and Major Programs. Sreeram has more than 25 years of experience in the banking industry, including 18 years at Standard Chartered Bank, with leadership roles across diverse functions, disciplines, and geographies. He has set up and ran the bank’s offshore Shared Service Centres and is an active sponsor and supporter of Robotics Process Automation in Operations.

How Do You Think Big Data Has Impacted Company Leadership In The Past Decade?

That’s a big question in the first place because it covers leadership and it covers a whole decade. But what comes to my mind is this phrase called Big Data which, on the one hand, is actually an aggregation of small data, and, on the other hand, characterised by high volumes of data.

The pace of technology has grown so exponentially, that the impact on Company Leadership is on two fronts.

One is that you feel overwhelmed with the volume of data and increasing customer expectations, while it’s also mandatory to respond to the regulatory challenges. So one is a sense of being overwhelmed, but, actually there is a sense of big opportunity in relation to how Company Management has been reacting in the recent past. That opportunity comes from many aspects of data, so it makes a whole world of difference between being unable to cope with Big Data and in seeing the business opportunity.

What Impact Has Big Data Had On Your Role Specifically?

I think Big Data, going back to my earlier point on volume, is a little bit too big to digest, if it is not properly addressed. Everything I read says it takes shape in three forms generally: one is that big data is a phenomenon based on ever-changing growing information, which affects the way we do business and depends on the habits of individuals with many different touch points. Second, it relates to capability, so it’s about gathering data, how you process data, and how you obtain sensible and valuable outcomes as to how well you can use the data. Third, it has become an emerging industry in its own right, leading to a profession and has led to a supply chain of both up-stream and down-stream providers of people who are data scientists, deep-rooted analysts and professionals on capturing data.

I see Big Data in the shape of a phenomenon, which is taking place in banking, as well as other industries. I also see it as a capability, which is around how you obtain valuable outcomes. And ultimately, it is also an emerging industry, which is spawning different kinds of specialist skills on the supply side of people and on the data capture side. So it’s quite a new thing, because of the ability of the technology to handle data that is becoming cheaper and cheaper every passing day.

How Important Do You Think Automation Through Data Is Going To Be In The Future?

Big Data has now led to different skillsets, such as data science, robotics, new complex algorithms, new models of anticipating customer behavior, et cetera. So in that space, there are different areas, where applications of Big Data within banking will be important. I’d like to say 3 or 4 areas, as follows.

One is Big Data being applied to improve transactional efficiency. So if we can use technology and Big Data in banking, we are in a position to improve the way we understand the transactions that flow through the bank. This can be transactions relating to the transfer of funds to and from certain geographies, it can be alert triggers relating to anti-money laundering, it can be mining of text and chatbots between retail customers and the bank. It can be a whole host of transactional matters for our Global Markets business. So there is an opportunity to improve the efficiency of transactional areas in a bank. This is not new, but we all see how consumer behavior is starting to play an important part in the way we run businesses - in areas such as credit cards, usage of credit cards and within that, analytics on how the card has been used. As an example, there can be so many perspectives that are about weekend usage, weekday usage and holiday usage.

One of the aspects facing banks today is that jurisdictional regulations are quite asymmetric. There might be some common factors, but there are many asymmetric expectations depending on which geography you refer to. So to be able to respond to regulatory expectations based on asymmetric jurisdictional requirements is another opportunity where Big Data plays a huge part. Within that area there are Sanctions, KYC, and Data Privacy matters. And they are each a topic in itself.

Lastly, there is an importance of Big Data in capital allocation models that banks are expected to manage. These are under different requirements from various regulators and industry bodies. How you manage the quality of data going into the capital models (because it is quite a big machine), could be a significant differentiator as well. The better the quality of data, the better the outcome that allows to fully realize the capital’s potential.

So in summary of my points on Data Automation opportunities, there is one chapter on transactional efficiency, there is another chapter on consumer behavior, and yet another one on regulatory and capital matters.

How Do You See The Use Of Big Data Changing In The Banking Industry In The Next 5 Years?

I honestly don’t know if I can see that far ahead because it depends on Technology and, as they often say, Technology changes every Monday morning. So five years is too long a time. But it feels to me, that almost anything that goes on in Big Data today is arguably somewhat foundational in nature.

So today banks are building foundational platforms in areas, such as Data Warehouses based on strategic reviews of what banks want to do using the Big Data. Once the establishment of organizational models is done, which is what many companies are currently going through, I don’t see banks having to spend too much time on organizational models to deal with Big Data - it will become a customary ability to handle data because it will become routine. Toolkits will be well-established and it will become something that you can track. As I said, there are new things surfacing, like Machine Learning, so that is still at an early stage of maturity. That will be a certainty in the next few years.

At the end of the day, my point is that current efforts from banks to figure out how to deal with Big Data will get sorted soon. I think technology toolkits will continue to improve. I think new areas of applications will come through, such as Robotics, which I am going to touch upon in my Summit presentation. Also, one can argue and debate whether Big Data will be a differentiator at all in the future, because I don’t believe it will be in a material way, since the abilities to handle it will become somewhat similar between any two institutions.

What Can The Audience Expect To Take Away From Your Presentation?

I think the only thing I can offer to share is what is my bank’s genuine on-the-ground experience in handling the topic of Big Data, what some challenges are in responding to both the opportunity of it and the overwhelming challenges of Big Data as an overall capability. And I think we can share our own experience on how to use Robotics to increase transaction efficiency. So those are the takeaways that I would like to share with the audience. 

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