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Where is suptech heading?

Technology plays a huge role in nearly every aspect of financial services today. As the world moved online, tools and infrastructure to help people manage their money and make payments have burgeoned the world over in the past decade.

With much of the finance world now leveraging technology to conduct business, predict trends and deliver services, financial services regulators are also developing new technologies to monitor markets, supervise financial institutions and conduct other administrative activities. The emergence of purpose-built technologies to facilitate regulator oversight has, over the past few years, garnered its own moniker of supervisory technology, or suptech.

Interest in suptech is proliferating across the globe thanks to a diverse set of prudential and conduct regulators. A sampling of regulators developing suptech include the FDIC, CFPB, FINRA and Federal Reserve in the U.S.; the U.K.’s FCA and Bank of England; the National Bank of Rwanda in Africa; as well as the ASIC, HKMA and MAS in Asia. Several “super regulators” are also engaged in suptech efforts such as the Bank of International Settlements, the Financial Stability Board and the World Bank.

The strides in suptech demonstrate that creative thinking coupled with experimentation and scalable, easily accessible technologies are jump-starting a new approach to regulation.

In this post, we’ll examine a few core suptech use cases, consider its future and explore the challenges facing regulators as the market matures. The uses are diverse, so we’ll focus on three key areas: regulatory reporting, machine-readable regulation, and market and conduct oversight.

A quick general note: Nearly every financial services regulator is engaged in some type of suptech activity and the use cases discussed in this article are intended as a sample, not a comprehensive list.

But what exactly is suptech?

As a preliminary matter, we should quickly survey a few definitions of suptech to frame our understanding. Both the World Bank and BIS have offered definitions that provide useful outlines for this discussion. The World Bank states that suptech “refers to the use of technology to facilitate and enhance supervisory processes from the perspective of supervisory authorities.” It’s a little circular, but helpful.

The BIS defines suptech as “the use of technology for regulatory, supervisory and oversight purposes.” This is a similarly loose definition that describes the broader scope better.

Regardless of differences on the margins, the “sup” in these suptech definitions acknowledges the primacy of the idea that regulators’ objectives are to oversee the conduct, structure, and health of the financial system. Suptech technologies facilitate related regulatory supervision and enforcement processes.

Regulatory reporting

Regulatory reporting refers to a broad swath of activities such as financial firms providing trading data to regulatory authorities and regulators’ analysis of financial data or corporate information to determine the projected health or potential risks facing an institution or the market.

The MAS and FDIC are incorporating transactional and financial data reported by firms as a means to assess their financial viability. The MAS, in conjunction with BIS, has run tech sprints soliciting new ideas relating to regulatory reporting, while the FDIC has “a regulatory reporting solution that would allow ‘on-demand’ monitoring of banks as opposed to being constrained by ‘point-in-time’ reporting. This project is particularly targeted at smaller, community banks that provide only aggregated data on their financial health on a quarterly basis.”

The HKMA recently outlined its three-year plan for the development of suptech, which includes developing an approach to “network analysis.” The HKMA will analyze reporting data related to corporate shareholding and financial exposure to bring them “to life as network diagrams, so that the relationships between different entities become more apparent. Greater transparency of the connections and dependencies between banks and their customers will enable HKMA supervisors to detect early warning signals within the entire credit network.”

These reporting initiatives touch on a theme regulators have continuously struggled with: How to regulate markets and firms based on a reactive approach to historical data. Regulation and enforcement are often retrospective activities — examining past behavior and data to decide how to sanction an organization or develop a regulatory framework to govern a particular type of activity or financial product. This can result in an approach to regulation too rooted in past failures, which might lack the flexibility to anticipate or adapt to emerging risks or financial products.

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Facebook has a new job posting calling for chip designers

Facebook has posted a job opening looking for an expert in ASIC and FPGA, two custom silicon designs that companies can gear toward specific use cases — particularly in machine learning and artificial intelligence.

There’s been a lot of speculation in the valley as to what Facebook’s interpretation of custom silicon might be, especially as it looks to optimize its machine learning tools — something that CEO Mark Zuckerberg referred to as a potential solution for identifying misinformation on Facebook using AI. The whispers of Facebook’s customized hardware range depending on who you talk to, but generally center around operating on the massive graph Facebook possesses around personal data. While a camera might have a set of data points as a series of pixels, Facebook’s knowledge of you goes well beyond your list of friends and down to minute preferences you have — a set of data so large that it demands a new approach to speed up the process.

Most in the industry speculate that it’s being optimized for Caffe2, an AI infrastructure deployed at Facebook, that would help it tackle those kinds of complex problems. Customized silicon generally tends to be around optimizing inference (the “is that a cat” part of machine learning) or machine training (“this is what a cat is”). On either end, it’s based on speeding up relatively simple math operations based in a field called linear algebra. But we’ve been hearing about this for a bit now, and it seems like Facebook is about to be much more overt about the process.

FPGA is designed to be a more flexible and modular design, which is being championed by Intel as a way to offer the ability to adapt to a changing machine learning-driven landscape. The downside that’s commonly cited when referring to FPGA is that it is a niche piece of hardware that is complex to calibrate and modify, as well as expensive, making it less of a cover-all solution for machine learning projects. ASIC is similarly a customized piece of silicon that a company can gear toward something specific, like mining cryptocurrency.

Facebook’s director of AI research tweeted about the job posting this morning, noting that he previously worked in chip design:

Interested in designing ASIC & FPGA for AI?
Design engineer positions are available at Facebook in Menlo Park.

I used to be a chip designer many moons ago: my engineering diploma was in Electrical… https://t.co/D4l9kLpIlV

Yann LeCun (@ylecun) April 18, 2018

While the whispers grow louder and louder about Facebook’s potential hardware efforts, this does seem to serve as at least another partial data point that the company is looking to dive deep into custom hardware to deal with its AI problems. That would mostly exist on the server side, though Facebook is looking into other devices like a smart speaker. Given the immense amount of data Facebook has, it would make sense that the company would look into customized hardware rather than use off-the-shelf components like those from Nvidia.

Most of the other large players have found themselves looking into their own customized hardware. Google has its TPU for its own operations, while Amazon is also reportedly working on chips for both training and inference. Apple, too, is reportedly working on its own silicon, which could potentially rip Intel out of its line of computers. Microsoft is also diving into FPGA as a potential approach for machine learning problems.

Still, that it’s looking into ASIC and FPGA does seem to be just that — dipping toes into the water for FPGA and ASIC. Nvidia has a lot of control over the AI space with its GPU technology, which it can optimize for popular AI frameworks like TensorFlow. And there are also a large number of very well-funded startups exploring customized AI hardware, including Cerebras Systems, SambaNova Systems, Mythic, and Graphcore (and that isn’t even getting into the large amount of activity coming out of China). So there are, to be sure, a lot of different interpretations as to what this looks like.

One significant problem Facebook may face is that this job opening may just sit up in perpetuity. Another common criticism of FPGA as a solution is that it is hard to find developers that specialize in FPGA. While these kinds of problems are becoming much more interesting, it’s not clear if this is more of an experiment than Facebook’s full all-in on custom hardware for its operations.

But nonetheless, this seems like more confirmation of Facebook’s custom hardware ambitions, and another piece of validation that Facebook’s data set is becoming so increasingly large that if it hopes to tackle complex AI problems like misinformation, it’s going to have to figure out how to create some kind of specialized hardware to actually deal with it.

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Ethereum falls after rumors of a powerful mining chip surface

Rumors of a new ASIC mining rig from Bitmain have driven Ethereum prices well below their one-week high of $585. An ASIC – or Application-specific integrated circuit – in the cryptocurrency world is a chip that designers create for the specific purpose of mining a single currency. Early Bitcoin ASICs, for example, drove adoption up and then, in some eyes, centralized Bitcoin mining in a few hands, thereby thwarting the decentralized ethos of die-hard cryptocurrency fans.

According to a CNBC report, analyst Christopher Rolland visited China where he unearthed rumors of a new ASIC chip dedicated to Ethereum mining.

“During our travels through Asia last week, we confirmed that Bitmain has already developed an ASIC [application-specific integrated circuit] for mining Ethereum, and is readying the supply chain for shipments in 2Q18,” analyst Christopher Rolland wrote in a note to clients Monday. “While Bitmain is likely to be the largest ASIC vendor (currently 70-80% of Bitcoin mining ASICs) and the first to market with this product, we have learned of at least three other companies working on Ethereum ASICs, all at various stages of development.”

Historically users have mined Ethereum using GPUs which, in turn, led to the unavailability of GPUs for gaming and graphics. However, an ASIC would change the mining equation entirely, resulting in a certain amount of centralization as big players – including Bitmain – created higher barrier to entry for casual miners.

“Ethereum is of the most profitable coins available for GPU mining,” said Mikhail Avady, founder of TryMining.com. “It’s going to affect a lot of the market. Without understanding the hash power of these Bitmain machines we can’t tell if it will make GPUs obsolete or not.”

“It can be seen as an attack on the network. It’s a centralization problem,” he said.

Avady points out that there is a constant debate among cryptocurrency aficionados regarding ASICs and their effect on the market. Some are expecting a move to more mineable coins including Monero and ZCash.

“What would be bad is if there was only one Ethereum ASIC manufacturer,” he said. “But with Samsung and a couple other players getting into the game it won’t be bad for long.”

There is also concern over ICO launches and actual utility of Ethereum-based smart contract tokens. “The price of ETH is becoming consolidated as people become more realistic about blockchain technology,” said Sky Guo, CEO of Cypherium. “People are looking for higher quality blockchain projects. I believe a rebound in ETH’s price will come soon as panic surrounding regulations begins to fade.”

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