Hi, my name is Prakash Neehkantan. I'm part of Broadridge, a $4 billion firm, which is part of the S&P 500. We enable corporate governance and transactions in the capital markets in Broadridge. I am part of the copper strategy group, helping drive innovation and adoption of blockchain among our customers. Broadridge has a vantage point in this space, because we sit in the middle of investors, advisors to brokerage firms and operations, enabling products and services across all these parties. Broadridge processes more than $5 trillion worth of transactions in fixed income and equity markets. We also enable communication for 5,000 brands to more than 75% of North American households. We also manage shareholder voting in 90 countries. Broadridge is a fintech firm, actually. And fintech is, I think it's many things for many people. But if you look at it, automation is at the heart of every financial services firm. So it is very difficult to say that no financial services firm is not fintech, right? But what differentiates them is actually, financial services firm existing, there is existing financial services firms sit in the middle of lot of transaction data, which they've been servicing their customers for many, many years. And they leverage technology to deliver many of their services. What we have seen in the last 20 years is the growth of the web, the mobile, and aggregation of humongous amounts of data across the globe, by a variety of firms. What fintechs are trying to do different from traditional financial services firm, are leveraging this connectivity, and the data, and innovate on new business models to service this traditional customer base. Broadridge's strategy is very simple. We are in the middle of this transaction flow among all our customers, servicing this larger market of investors. Our goal is to make this market more transparent, efficient, and cost-effective, driving new services to our customers. We do that by adopting a next-generation set of technologies, which we call ABCD in short form. That is AI, blockchain, cloud, and digital in a broad sense. It's interesting too that we put it in the ABCD, but the reality is, actually, what we want to do is very simple. We want to drive all communication to customers in a digital native form, through a variety of channels. And servicing them anywhere through the cloud through a cloud hosted mechanism. And share data through blockchain in a sense, and solve innovative problems through AI. I would say that exists in our strategy. We believe in partnering, as well as working with our customers, and building these new solutions. We have invested also in startups, and other fintechs, and collaboratively work towards new solutions in this area. So when our customers ask us about fintech, or any of these new technologies, our first goal is to identify what business challenges and problems they're trying to solve for, right? For our customers, cost could be a driver. They want to deliver more efficient solutions. They might want to grow into new markets, new customer segments. They would also like to actually provide innovative new solutions to any of these customers. What we say is actually before choosing the technology, let's analyze the problem space at the business area. Figure out whether this is the appropriate technology to use and solve for. And then we work with them collaboratively, as well as actually technology providers to innovate and design new solutions. That's been our strategy always with customers. The goal is to actually understand the problem, and then solve for it using technology. Technology does not come first, whether it's blockchain or AI. For many people, blockchain is something is a technology looking for a problem, and that is true for many of our customers. To everybody that's been experimenting with this technology, our advice has been to actually focus on specific business areas from a broader perspective. We want to solve for what is called network effect. That idea is actually that the solution becomes more effective as more and more customers, and their business partners join the network. And we being in the middle of the data and the transaction flow can actually help them effectively manage this. Blockchain is such a technology which can actually enable, secure efficient sharing with confidentiality of data and transaction between multiple parties. And our goal has been to pick specific business areas, which can be solved using blockchain technology. So when we apply blockchain technology, right, we chose, say, a multi-pronged strategy. We decided to partner with startups in the space. We have investments in a firm, like digital asset. We are also members of actually technology consortiums like Enterprise Ethereum, and Hyper Ledger. We invested in these technologies, built pilots and proof of concepts, and then collaborate a jointly with customers like Santander Bank, and Northern Trust, JP Morgan, to build out solutions with specific use cases in mind, like proxy voting. Which brings in efficiency and trust into the corporate governance process. Fintech is, as I said, many things for many people. Established players, like us, actually, are using a fintech very efficiently and innovatively. One of the areas we are applying this, actually, there is still a lot of paper in our businesses. And what we are doing is actually extracting text from copies of the digital copies of these paper documents, converting them into specific attributes, which we can use. Say for instance, in a process like trade allocation, where the allocation instructions come as faxes, or actually emails, right? Or even actually paper documents, which are scanned and actually processed later. Extracting text from images is actually optical character recognition, which is a form of computer vision. And that is getting better and better, applying machine learning. And extracting actually information from text is actually natural language processing, which is also part of the AI. Data actually is available in plenty today. And so what could not be applied earlier becomes a new potential innovative area to apply technology. The classic example, for instance, markets. As you all know, being in the financial services space, which brings buyers and sellers together. Traditionally, liquid markets, like say for instance, NASDAQ or NYC, where the top 500 stocks are actively traded. You can always find a seller at a price which is actually available to you if you are a buyer. But in some markets like corporate bonds, and especially in the long tail of these corporate bond market, it's very difficult and expensive to find a buyer or a seller, or bring them together. What we are doing is actually trying to apply machine learning, based on the history of transactions of participants, to identify whether there are similar products that they have bought before. Which will actually make them buy, or actually show interest in buying this new bond, right? And that's an innovative way to think of it, actually like how Amazon works for you with recommendation engines. You bought these products in the past, so you might be a potential buyer for the similar product today, right? But we are applying a similar technology, actually, in the bond market. If you look at exciting fintechs, there are a range of fintechs. I mentioned that they apply innovative business models, solve problems. They can solve mundane problems. One company which has been a fintech for quite some time, a lot of people might be familiar with this name. It's Stripe, Stripe makes the traditional legacy payment infrastructure of banks, and the banking network simple to use through APIs. We think that that's a very innovative use of technology to take a backend back office problem, and simplifying the whole process for all these companies coming online and enabling payments. Another example is actually Acorns, which is actually start-up in the fintech space, which is solving savings. They do what I would call nudge based savings. They help you save by taking small chunks out of your regular transactions, and influencing your behavior. So that actually, you build up your savings account over a period of time incrementally, right? That's a very innovative model which combines behavioral science actually, and economics, right? Solving the problem, which is a very challenging problem in today's world, because with the savings rate in the US is actually very low. In my belief, singularity is still far away, right? Fintech, as we call it today, the ideal future would be that nobody calls it fintech anymore, and becomes part of everyday life, and that's been true of lots of technology. Today we don't talk about e-commerce, right? But everybody uses e-commerce, and the same thing for streaming media and Netflix, right? We have cut the cord, and it's become a natural progression of things. We believe, I think, the fintech world, it'll also evolve in a very similar fashion. Technology changes actually too fast for us, actually, to label it in different fashions. If you go back a few years, nobody would have started using the term Chief Data Officer. But today, many companies have Chief Data Officer. Well the last five years, many corporations also have digital officers who enable, actually, digital embedding, digital processes across every business. In a similar fashion, fintechs or financial services firms would have actually officers driving customer behavior, and varieties of forms applying technology. You might want to call them a fintech officer. You might want to call them actually somebody driving innovation and technology. You might want to call them somebody driving AI and blockchain. None of that matters, because the end result is actually that you're adapting to actually technology, and servicing your customers. Small businesses actually are the ones which can actually get maximum impact or a fintech. We always talk about the unbanked, but actually, we should talk about also the banked, which is actually lots of small mom-and-pop stores. Which actually service their customers either through credit card payments, right, and not cash. And also have a challenge of getting financing to stock the appropriate inventory for them to service their customers efficiently. What can happen in the future is two things, because they are willing to share their transaction history, banks can actually apply machine learning on that data, and actually build new models. Which can ensure that, actually, without traditional history, they are still a good bet to finance. Right, that's one dimension. Take the case of a student. There are many forms in which this can apply, right? The simplest form actually, fintech can apply student to student loans, right? The model is changing, there are new models being created for financing. We have seen some startups, actually, like SoFi, which are actually focused only on student loans. What you want is actually to enable a larger set of students to get loans at a lower rate if needed, and a potential for them to pay off. Actually, they are loans over a period of time, or even reduce those loans. So one area, right, so when we talked about financing, right, blockchain for instance, right? Right, let's take a large manufacturer. We just got actually a large supplier, right? For example, this is just an example. It could be a large car company, right? Which has got an automotive parts supplier. One supplier here, main supplier, say, in China, and that Chinese supplier has got actually 50 other vendors who supply to them. What happens in the traditional financing space is actually the large supplier to this car company can go to a bank and get financing as they supply actually parts to this car company. But the second and third firms which actually supply the final parts to this primary supplier are always in the middle of a process, where they do not have visibility to the final transaction of what part has actually gone into the manufacturing of the car. And when will they get paid? And this is where something like blockchain is actually transforming the supply chain, where every party to this transaction can actually track every part that the supply across the supply chain. And make it visible as they raise invoices to their banks, and the banks would, actually, now with confidence know that this part went into this larger component, which then got supplied to say General Motors. And so they know where in the pipeline this part is, and they can confidently lend to the small supplier. This way, I think small businesses across the globe can get transformed, and we are just seeing the start of this process today. There is no hard and fast rule about career today. You could in any, if you're looking at the fintech space, you could start on the technology side of the business, or you could start in the business side and the product side of the business. Now, if you are by training a technologist, it might be good to educate yourself in a particular domain in the financial services space. And because that's going to be more valuable, a technologist with business knowledge is more valuable than just actually say a developer or programmer, right? The same goes for the other side, because if you're a product manager today in a fintech firm, in your startup, actually, it's a small team. You need to actually roll up your sleeves and do lots of activities. You will not be a good product manager with lots of good domain knowledge unless you also know how that product can be realized in technology. So you need to know the limits of the technologies, how it can be applied, and also help manage technologists and developers, actually, to build this. That, I think, is a key skill. And so for business and financial professionals actually getting a better sense of actually technology, and understanding technology is, I think, a good supplement to what they are already learnt, right? The combination for both would be data, because if you are building something new today, the process of building something new is completely become analytic, right? You actually start with the concept validated the market, analyze, get people to use it. Look at the data, analyze it further, decide whether it's working or not, pivot to a new model. And this continuous process needs actually data and analytic skills, so I would always supplement something on data and analytics, along with your traditional degree.
