Data in Banking Regulation- Back to the Future?

Data has always played a crucial part in Regulatory Change within Investment Banking, however recent activities in the Risk, Finance and Treasury Regulatory arenas have led to a significant change in both attitudes and applications of Data.

It can be hard to determine what these attitude changes will mean for the future of Banking, but I am already seeing some trends in how people speak about these issues, which indicate the potential impacts. In this blog, I’ll give a quick account of the short, medium and long-term scenarios as I read from the current indicators. I’ll provide a mixed bag of obvious realities, educated guesses, and pure conjecture, but it’s all rooted in consistent predictions from some pretty smart people in the industry.

Short-Term

Risk and Finance have hugely important immediate data challenges in the immediate term, and have begun to move closer together. The obvious challenges of likes of BCBS 239 and FDSF are similar to previous regulations: finding and reporting accurate data is a massive challenge given the complexity and volume of feed sources. This is nothing new, although the sheer scale and volume of data involved are bigger than we’ve seen previously.

The more interesting short-term challenge comes in Treasury- there hasn’t previously been much of a business-driven need to implement more advanced technologies or remodel processes. However, Capital Requirements regulations and Liquidity Reporting requirements have been the Lightning Bolt that has kicked the Treasury DeLorean to 88mph, and back into the future. (If you don’t get the reference, I’d stop reading. They’re only going to get more obscure). In the words of Stringer Bell, “the game done changed” (Told you. If you don’t get this one then stop reading as you need to clear some time to watch “The Wire”.)

The reason this is interesting is that I haven’t come across a situation where we need to move so quickly from virtually no data architecture to the most up-to-date technology available. It’s like upgrading from MS Dos to Linux- you’re not just changing the tool but the whole mode of operation. 

Medium-Term

The most obvious Medium-Term impact of the Data issues within the current regulatory landscape is a massive seed change in attitudes to Data Quality. This isn’t local to the Regulatory Reporting teams or Line Finance/Risk either. There are several large-scale bank-wide Data Quality initiatives, concerned with consistent data standards. The overarching strategy seems to be in managing Programme Leadership stakeholders horizontally, and driving agendas towards the common goal of clean data across the board. 

The biggest change in attitudes to Data seem to come from the Front Office. With the 2016 and 2017 deliveries, how trading activities are carried out, and crucially- how much trading activities occur will depend on accessible and accurate information on demand. 

While not everyone has come round to the data-driven approach yet, we’re likely to reach a point where you catch up or you drop behind. 

Long-Term

And now the conjecture- my favourite part. My honest reaction of where we stand and where we’re going is that it’s about time. The unregulated Investment Banking market created a situation where it was relatively easy for incredibly smart people to print money, they just needed to spend their time coming up with novel ways to structure products in a way that created both a supply and demand of new money. The finish line of this intellectual race wasn’t a place where we learned much about the real world, or even the nature of markets. The competition was to see who could create the most complex rules to a game where we all stand to win. In my opinion, this is a waste of talent for some of the world’s smartest people. This might seem rich coming from a Philosophy graduate, but that’s where the sentiment comes from- it frustrated the hell out of me to see geniuses spending their time coming up with complex abstract arguments that didn’t contribute anything to the real world.

If we get to where Investment Banking is aiming right now (Big if), however, the long-term result will be a mass of useful and accessible information for those smart people to pore over. It’s hard to say what that will lead to, but I would put my money on it leading to some genuine developments in our understanding of both market and cultural behaviours. This might seem like a stretch, so I’ll use an example.

Google became the top tech firm in the world by creating the best search engine and marketing it well. But they stayed the best, and grew to the mass they’re at now through one simple product- information. Google Ads uses information that we’d never have thought useful 10 years ago to target marketing strategies in an incredibly efficient way. Using high-quality data, we have tools that predict and play music you like on demand, recommend television programmes, decide what current account is best, and that’s just the simple stuff. The rest is much more interesting- Did you know that we can figure out which sentence structure is more likely to convince someone to buy a product by analysing click rates on adverts? We can. Not only can we do that, we can combine that with information from social media and browsing history to predict what sentence structure will be more convincing to you over your neighbours. Without no human being involved at any stage of the process. My point is that good data leads to incredibly precise, accurate behavioural predictions. 

In Investment Banking, we’re not just looking at abstract concepts anymore. We’re looking at behavioural change, we’re assessing market activity, we’re trying to find ways to measure things that were previously considered unmeasurable. The long-term impact of high-quality Data for money-rich machines like Investment Banks can only lead to a higher level of understanding of previously vague ideas. Imagine you could find solid information for every instinct you’ve ever had about how to make money. That’s where we’ll be.

And while I’m on to wild and barely founded predictions: South Africa as a Dark Horse for the World Cup, Andy Lee to knock Billy Jo Saunders out late on, and Dublin for Sam. Oh and hoverboards. It’s 2015. Where’s my hoverboard?

Victoria Walmsley's picture
Managing Director
vwalmsley@morganmckinley.co.uk

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