Overcoming crypto asset data intelligence challenges

Nothing is more important to a trading strategy than good information – but in crypto, that can be remarkably hard to find. That creates a pressing need for smart solutions that convert raw data to usable market intelligence.

All sound investment strategies are based on information – which is to say, on well organized and interpreted data. In crypto, that fundamental need throws up enormous challenges. On the one side, there is bad quality data, and on the other, there is difficulty in organizing, and acting on, this data.

The first problem is that market activity is spread over so many venues. Centralized exchanges provide plenty of data on their activity, but activity on decentralized exchanges (DEXs) – on-chain transactions – is much harder to track. And although most activity still takes place on centralized venues, these on-chain trades cannot be ignored; a single large transaction could have a serious impact on the value of the instrument itself.

Although it is sometimes thought that blockchain transparency must mean all the data needed is readily available, this is where the well-known difference between data and information really matters. All that disorganized on-chain data is just noise. It is not possible to shift through it to glean any useful insights without significant effort to process the data into a meaningful form.

To see through the opacity, there is a glaring need for meaningful crypto data intelligence. The obvious challenge is how to distill all the data into a form that is easily readable and understandable for the vast majority within the crypto space.

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The tools are not up to the job

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The digital asset market is famously volatile – and the available data provision has frequently shown itself to be inadequate to the task of keeping up with this rollercoaster. In May this year, the market lost over US$200 billion in a single day; no small sum considering that this is still a niche sector.²

Against this backdrop, even monitoring a single portfolio is a challenge, given that digital assets will be spread across multiple venues, including on-chain and custodial wallets, and none of the exchanges provide metrics to actively manage institutional-grade portfolios. If you try to get a view of the broader market, it becomes exponentially more difficult.

Portfolio managers cannot gamble with client funds: they need high-quality data to stay ahead of the fast-moving market. But DEX-provided APIs have proven to be unreliable and laggy – and since they are provided for free, the exchanges (which are focused on retail customers) have no incentive to improve them. In fact, the International Monetary Fund has found wide disparities in comparable data from various providers, underlining their unreliability.³

So investors will frequently be trying to make decisions based on old and incomplete information. On top of that, data gaps will have potentially catastrophic effects⁴ on predictive models and automated trading strategies. And the nature of the market also makes those models exceptionally vulnerable: huge, sudden swings in market sentiment are fairly regular in crypto. These so-called outlier events are not typically captured in data training sets, making AI predictions fundamentally flawed.⁵ 

These problems are a pressing concern for everyone from professional investors to regulators and law enforcement.⁶ This rapidly growing, unstable and inadequately reported market could threaten professional investors, especially given its reliance on smart contracts and the lack of robust risk-analytics. The lack of clear, coordinated information creates a playground for crypto crime. And the perceived anonymity of crypto also makes it a popular haven for criminals and money launderers and creates compliance headaches for fund managers.

Fixing the problems of digital asset data intelligence is an urgent need. Incomplete data is creating a real barrier deterring potential investors from entering the market, holding back maturation of the sector, tarnishing the reputation of digital assets and allowing criminals to flourish. For portfolio managers, the risk of allowing blind spots and incomplete information to drive investment decisions is untenable.

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We generate data intelligence to manage crypto risks

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Nuant was created to fill this gap, providing investment managers with the comprehensive, user-friendly analytics tools they need to harvest real crypto intelligence from the mass of confusing on- and off-chain data. Nuant’s dashboard delivers the always-on view that institutions can rely on, integrating on-chain and market sources and providing the high-quality insights that give investors the edge.

Portfolio managers will benefit from the essential market metrics as well as graphics, our industry-wide Data Explorer, and custom queries, using the domain-specific Nuant Query Language. Integrated wallet intelligence tools support KYC compliance and fraud detection.

While professional investors have long been accustomed to having their strategies supported by sophisticated, powerful intelligence tools and automations, investing in the digital asset sector can feel shockingly primitive. Fortunately, that doesn’t have to be the case. Nuant’s crypto data intelligence technology will enable institutions to unlock value and mitigate risks, with the right information always at their fingertips – as it should be. 

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Sources

1. Browne, Ryan (2022) More Than $200 Billion Erased from Entire Crypto Market in a Day as Sell-off Intensifies, CNBC. Available at https://www.cnbc.com/2022/05/12/bitcoin-btc-price-falls-below-27000-as-crypto-sell-off-intensifies.html 
2. IMF (2021) Global Financial Stability Report, October 2021. Available at https://www.imf.org/en/Publications/GFSR/Issues/2021/10/12/global-financial-stability-report-october-2021 
3. GDA Fund (2021) Addressing Some of the Biggest Data Problems in Crypto https://gdafund.medium.com/addressing-some-of-the-biggest-data-problems-in-crypto-228b6fc9a462 
4. Rodriguez, Jesus (2020) Five Surprising Challenges About Crypto Predictions that can Drive Data Scientists Crazy, Into the Block. Available at https://medium.com/intotheblock/five-surprising-challenges-about-crypto-predictions-that-can-drive-data-scientists-crazy-20cf54d07df5 
5. Alderman, J et al (2022) The Power of Blockchain Analytics in the Digital Asset Economy, Accenture. Available at https://www.accenture.com/content/dam/accenture/final/a-com-migration/pdf/Accenture-Federal-Blockchain-Analytics_v2.pdf 

Panel discussion at Blockworks Digital Asset Summit 2022, London. Video available at https://blockworks.co/events/digital-asset-summit-2022-london/?playlist=3842bbe8&video=2e228c6