Machine Learning: View From the Top Featuring SmartStream

https://thefintechtimes.com/machine-learning-view-from-the-top-featuring-smartstream/
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There are plenty of defining years in the history books, and as 2020 draws to a close, it’s almost certain that the global pandemic will ensure that this year is featured prominently. With events cancelled, launches delayed, and country-wide lockdowns, the way we work has changed forever. Still, for financial technology and surrounding industries, this was also a year of challenge and opportunity. 

This December, The Fintech Times is asking industry leaders for their ‘View from the Top’ to gain an insight into the decisions behind the last 12-months. Today, we’re speaking to Haytham Kaddoura, the CEO of SmartStream Technologies Group. Kaddoura has over 20 years of experience in investment advisory, asset management, corporate restructuring, strategy formulation and execution for boards of some of the most prominent corporations across the GCC and the greater Middle East and North Africa region.

Here Kaddoura is interviewed by Chris Skinner, in his role as guest editor for The Fintech Times, about artificial intelligence, knowledge sharing and the future of fintech

How do you see fintech affecting the transaction lifecycle and where do you see the sweet spots?

Fintech is at the core of a lot of the developments in the trade posting world today. Whether you’re looking at a piece of best execution management, cash and liquidity and other collateral management or corporate action; banks and regulators are increasingly looking for greater transparency, much more timely availability of information and fintech is at the heart of it. It’s quite different from what we used to see five to seven years ago.

With artificial intelligence-enabled technology now we’re effectively pushing the boundary on where fintech used to be important to more strategic and more critical decision-making areas of financial institutions.

There’s lots of chatter about artificial intelligence (AI), machine learning, blockchain, and cryptocurrencies. How do you see these technologies developing?

I think it is the next best thing to sliced bread that has affected the industry. Three to four years ago everybody was talking about AI, blockchain and machine learning, but it wasn’t anything solid. It was a new concept and new theory that looked nice on paper, but there were very few entities that actually had products out there or that could really utilise this technology. Since then, the impact of AI on understanding masses of data and analysing it and enabling institutions to process the massive volumes of data very quickly is so valuable. For example, using predictive analytics – in terms of looking at trends in payment and treasury operations – has a massive influence on every bank’s decision-making capabilities today. Aside from creating efficiency, cutting costs and having met the requirements for regulatory reporting, the impact of AI in this very short period of time has had massive impact and we are only seeing the tip of the iceberg. As AI starts to roll out in different entities and different functions, it will have significant impact and great value for different stakeholders, whether it’s the shareholders, the regulators or us as consumers.

JPMorgan Chase is investing in blockchain and other technologies and has highlighted the long-term potential of distributed ledger technology (DLT). But would you agree that, currently, the best developments are from the outside community that services the banks?

Yes, 100%. What I’ve seen with a lot of our clients, is that they were very trigger happy – many institutions jumped on the idea of investing in new technologies, they set up innovation labs and allocated quite significant budgets to deal with it. With all due respect, a lot of these have failed in handling critical areas. You have to leave AI to the experts.

In the reconciliation space, where we operate, we work closely with both innovation teams and the institutions. It’s the difference between surgically tackling an issue and putting a Band-Aid on it. So, when you enable artificial intelligence ina thought process, it is completely different to putting a generic solution on top of a problem. What we do, is embed AI in what we provide. And, I should think that a lot of the fintech providers are in the same situation. It’s completely different than building a shell around a solution.

In a recent blog I wrote – Build or Buy to Build and Die – I highlighted how specialist companies were offering open APIs and interfaces to banks that could provide them with beautiful code to transact and do things that the bank just couldn’t do five to 10 years ago. In areas, such as open banking and payment, we’ve seen a big impact but less so in the capital market space. What’s your observations?

We still have the old value of tried and tested. So, when your building expertise is for something you’ve seen across multiple institutions, it does add value to any one institution that tries to newly dive into a process. What we’ve seen across Asia, the US, the UK and other European markets, is that every time you are able to transfer knowledge, it is much better than when a particular financial institution looks at it from their own particular window. There’s tremendous value in synergy and knowledge sharing and that’s certainly one of the key value propositions that global fintech providers bring to the table. It is surprising and somewhat mindboggling that even in today’s world, when you talk to a Tier 1 institution in New York and then you talk to the same institution in Europe, there’s very little sharing of knowledge. You’d think that things would be discussed more on a global front. But unfortunately, the institution is still heavily driven by local geographically constrained operations. We bring value to a normalised process across the globe within an institution. Unlike, say, a bank or an institution, we’ve done this for so long and we’ve seen everything. And, with our history, we’ve built with that in mind, and we’re ready for it – empowering a whole new way of thinking, new capabilities, new way of doing things.

Goldman Sachs has reportedly shrunk its trading floor in the last 12 years from hundreds to a few. With less traders, there’s also less need for management, so we are now seeing highly lean organisations going from investing $12 in humans and $1 in technology to eventually switching the other way around. Do you see that as a bleak prospect for most people’s jobs and futures?

Well, we’ve seen this many, many times before. When newspapers started getting published online, it didn’t kill their processes like it was initially feared. I think people get skilled and they get geared up for other areas. Let’s not forget, millennials are increasingly looking for a relaxed working environment. They want to have a healthier life-work balance more than our generation. So, the odds of having somebody doing a 12 to 15-hour shift is going to diminish as we progress. And, that’s what technology these days is enabling; giving people a stronger work-life load. But at the same time, there’ll be new avenues that are going to open up where people will be more smartly utilised. And, you’re also discounting expansion. Your argument is predicated that if I’m working smarter and more efficiently and more streamlined then my side stays the same side. You’re not saying, well, I’m doing better, then why wouldn’t I grow more? You know, nature abhors a vacuum. I would see more people relying on technology more because we can service more.

When you’re looking over the next cycle horizon of what’s coming downstream with technology, what are the top things that are on your agenda?

For us and others in general, we’ve barely scratched the surface of the capabilities of artificial intelligence, and machine learning will be an even hotter topic in the next couple of years. There are a lot of other new technologies coming up. I don’t know the situation with neural computing but there’s a lot of talk about it these days and neural networks. But technology is advancing every day and fintech space is just trying to keep pace. At the end of the day, the aim is to make operations much more efficient and institutions more capable in meeting client-to-client needs. Every day the march towards excellence is relentless. Without sounding brass, 100 years ago when somebody made the best wagon wheel, Ford then didn’t say, I love these wagon wheel makers, I have to stop making cars. Things are redeployed. Maybe it goes into research, maybe it goes to the personal relationship and the real logging of the work that technology now does better, faster, cheaper. That’s left to the computers or our solutions and the people doing what they’re good at, which is relating to people. It’s just like robots assembling cars instead of allowing people to get repetitive injury, as they used to say 50 years ago. This is the way of the world at the departures board.

The growing automation of corporate actions processing has left some CFOs and COOs concerned at the dilution of their power base and fearful that automation is inferior to human team administration. Is it difficult politically to get people to vote for Christmas if they are a turkey?

Yes, 100% but at the same time, regulators are not making it easy today. The impatience that regulators have with human error is quite strong, given that we have the technologies to overcome the need for any human to be involved. We have jurisdictions where regulators are mandating specific solutions for the fintech organisation that’s providing us. And this is what we expect to see if somebody decides to make or to do the same reports on Excel and there is an error, guess who is going to lose their job. The question is that, 10 years is a long time, can we afford not to do something now?

https://thefintechtimes.com/machine-learning-view-from-the-top-featuring-smartstream/