"Next:Money" entries
4 trends in fintech startups
An analysis of fintech competitions shows a focus on data, payments, lending, and small business.
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Fintech hackathons and competitions occur globally. In January 2012, Swift launched the Innotribe Startup Competition as an initiative to bring together disruptive startups and incumbents in financial services. It was one of the first of its kind and has been joined by similar events in subsequent years. Just this year, I counted 18 fintech hackathons and startup competitions — eight of which are happening later this year.
Fintech startups are aiming to disrupt financial institutions with their technology, products, and design. Meanwhile financial institutions focus on secure systems for money transfer, payments, and lending at a global scale. But the two are not necessarily at odds. It’s hard for incumbents to innovate existing businesses in house, and this is where startups thrive: testing new business models and pushing the limits of technology unencumbered by regulations or corporate baggage. Hackathons and startup competitions are where innovative ideas are tested. Read more…
The race to build ‘‘big data machines’’ in financial investing
Robot wealth managers and approaches will grow and offer alternative ways of investing.
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Editor’s note: This post originally published in Big Data at Mary Ann Liebert, Inc., Publishers, in Volume 3, Issue 2, on June 18, 2015, under the title “Should You Trust Your Money to a Robot?” It is republished here with permission.
Financial markets emanate massive amounts of data from which machines can, in principle, learn to invest with minimal initial guidance from humans. I contrast human and machine strengths and weaknesses in making investment decisions. The analysis reveals areas in the investment landscape where machines are already very active and those where machines are likely to make significant inroads in the next few years.
Computers are making more and more decisions for us, and increasingly so in areas that require human judgment. Driverless cars, which seemed like science fiction until recently, are expected to become common in the next 10 years. There is a palpable increase in machine intelligence across the touchpoints of our lives, driven by the proliferation of data feeding into intelligent algorithms capable of learning useful patterns and acting on them. We are living through one of the greatest revolutions in our lifestyles, in which computers are increasingly engaged in our lives and decision-making, to a degree that it has become second nature. Recommendations on Amazon or auto-suggestions on Google are now so routine, we find it strange to encounter interfaces that don’t anticipate what we want. The intelligence revolution is well under way, with or without our conscious approval or consent. We are entering the era of intelligence as a service, with access to building blocks for building powerful new applications. Read more…
The new fintech: mobile, decentralized, and friction-free
The O'Reilly Radar Podcast: Dele Atanda and Mutaz Qubbaj talk about their startup platforms and the disruption in fintech.
Learn more about Next:Money, O’Reilly’s conference focused on the fundamental transformation taking place in the finance industry.
In this Radar Podcast episode, I chat with Dele Atanda, founder and CEO of Digitteria, about the disruptive state of the financial tech industry, what he thinks is driving that disruption, and why smart data (as opposed to big data) is going to revolutionize finance. I also talk with Mutaz Qubbaj, CEO and co-founder of Squirrel, about about the Squirrel platform, accelerator programs, and how he views the big disruptors in fintech landscape.
We’ve started an investigation — and launched a new summit, Next:Money — here at O’Reilly to look into the disruption happening in the fintech industry, as burgeoning startups create services and products that threaten to disaggregate traditional finance incumbents. I recently had the opportunity to sit down with a number of fintech startup founders and will be featuring several of those conversations in upcoming Radar Podcasts.
Dele Atanda founded Digitteria, a startup developing sustainable identity and personal data management solutions for both consumers and enterprise. I asked him why the time is ripe for disruption — he pointed to the growing complexity of the landscape and compared the current state of the finance industry to the early stages of the Web:
There’s a significant increase in complexity, and in that complexity there’s a much more detailed and rich ecosystem. Banks, it’s difficult for them to be able to tackle all the ends and elements efficiently, so it’s interesting because it’s almost representative of, it’s lacking the evolution of the Web, but it mirrors it in very many ways. Initially, you had these monolithic sort of applications, or browsers, or services that tried to do lots of things, and then we moved into the mobile era where things became much more siloed and application centric, where you did one thing particularly well. That’s inevitably going to happen in the fintech space. They say that the currency of the industrial era was paper, and the currency of the knowledge era is the electron.
Money is primarily electronic now, so it’s inevitable that there’s going to become this confluence between the Web and finance in that regard. I think, of course, because of security, regulatory issues, and the cultural dimension of money, there’s been a lag and resistance. Now that the Web has reached a level of maturity that it can address those issues, I think that’s inevitable.
Filing cabinets, GAAP, and the accountant’s dilemma
The inability to take advantage of digital technology is as big a threat to financial organizations as any fintech startup.
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There’s plenty of news about the fintech, or financial technology, sector these days. Hundreds of nimble startups are disaggregating the age-old financial systems on which every transaction has relied for decades. There’s little doubt that this will continue — after all, more than four billion humans have a mobile phone, and 1.3 billion know how to use a Facebook feed, but only a billion are what we’d consider “normally banked.” Something’s got to give, and software is eating traditional financial systems one bite at a time.
But the existing financial industry isn’t just under threat from outside. Many of the processes and institutions of finance have been around for centuries, and their processes are tied to physical systems rather than digital ones. As a result, they’re unable to take advantage of digital innovations easily and remain competitive. Read more…
9.3 trillion reasons fintech could change the developing world
Modern fintech is going to create formal, standard records about economies where none existed before.
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A relatively commonplace occurrence — credit card fraud — made me reconsider the long-term impact of financial technology outside the Western world. I’ll get to it, but first, we need to talk about developing economies.
I’m halfway through Hernand de Soto’s The Mystery of Capital on the advice of the WSJ’s Michael Casey. Its core argument is that capitalism succeeds in the Western world and fails everywhere else because in the West, property can be turned into capital (you can mortgage a house and use that money to do something). The book uses the analogy of a hydroelectric dam as a means of unlocking the hidden, potential value of the lake.
But in much of the world, it is unclear who owns what, and as a result, the value of assets can’t be put to work in markets. In the West, we take concepts like title and lien and identity for granted; yet, these systems are relatively new and don’t exist around the world. As de Soto noted in his book, in the Soviet Union, unofficial economic activity rose from 12% in 1989 to 37% in 1994. Read more…
Here’s why finance is about to be disrupted
O'Reilly's Next:Money event helps business leaders understand the fundamental shifts reshaping finance.
Learn more about Next:Money, O’Reilly’s conference focused on the fundamental transformation taking place in the finance industry.
Editor’s note: We’re approaching an inflection point in all things “money” — currency, transactions, markets, and capitalism itself. Fundamental changes in the financial industry, driven by technology but with implications for every business and government, are beginning to manifest, bringing both disruption and opportunity. We created O’Reilly’s new conference, Next:Money to help business leaders understand and act on this shift. Below, investor and entrepreneur Paul Kedrosky lays out the forces and patterns that are reshaping the financial industry.
Finance has the three main characteristics of an industry likely to be transformed by technology:
- It traffics in bits, not atoms.
- Its services are often delivered remotely.
- There is little need for human contact.
Unlike other sectors with these characteristics — e.g., media, advertising, and travel services — finance hasn’t been disrupted. Despite huge technological change and a series of financial crises, the league table of the largest financial firms today, both in the U.S. and around the world, remains much the same as it has always been.
Granted, the $1.2-trillion U.S. financial services industry isn’t homogenous. Its main components — banks, brokers, asset managers, markets, payment networks, insurers, and credit card companies — are very different, and have seen widely varying degrees of technology-induced change. In no sense, however, is this industry as transformed by new companies and new business models as one would expect, given its disruption-ready characteristics.
So, why haven’t entrepreneurs transformed finance? There are (at least) five reasons: Read more…
Data science makes an impact on Wall Street
The O'Reilly Data Show Podcast: Gary Kazantsev on how big data and data science are making a difference in finance.
Learn more about Next:Money, O’Reilly’s conference focused on the fundamental transformation taking place in the finance industry.
Having started my career in industry, working on problems in finance, I’ve always appreciated how challenging it is to build consistently profitable systems in this extremely competitive domain. When I served as quant at a hedge fund in the late 1990s and early 2000s, I worked primarily with price data (time-series). I quickly found that it was difficult to find and sustain profitable trading strategies that leveraged data sources that everyone else in the industry examined exhaustively. In the early-to-mid 2000s the hedge fund industry began incorporating many more data sources, and today you’re likely to find many finance industry professionals at big data and data science events like Strata + Hadoop World.
During the latest episode of the O’Reilly Data Show Podcast, I had a great conversation with one of the leading data scientists in finance: Gary Kazantsev runs the R&D Machine Learning group at Bloomberg LP. As a former quant, I wanted to know the types of problems Kazantsev and his group work on, and the tools and techniques they’ve found useful. We also talked about data science, data engineering, and recruiting data professionals for Wall Street. Read more…