Comply with regulatory requirements and minimize compliance overhead using Solidus’ machine learning-powered, crypto-native manipulation detection models and a one-stop-shop hub to manage all of your compliance streams
Leveraging the power of machine learning, Solidus offers powerful threat-detection engines that reduce false-positives by at least 30% and provide smart probability scores for better compliance decisions. Dynamic detection models are critical to tackling new and unknown forms of manipulation introduced by digital asset trading.
Solidus' Compliance Cloud was designed to address the unique challenges of compliance and manipulation detection in digital asset trading. Crypto-native means integral blockchain connectivity, accommodating crypto data, enabling real-time detection and reporting and extensive customization to address dynamic regulation and compliance strategies.
Solidus’ open platform gathers all your compliance feeds into one fully-customizable dashboard for comprehensive alert management, investigation and reporting. Utilize Solidus' machine learning-powered transaction monitoring and market surveillance alone or alongside other vendors, while seamlessly integrating additional external and internal feeds.
A few figures contextualizing the state of crypto market integrity and regulation. Sign up for our newsletter or visit our knowledge page to keep in the know.
of trading volume in major crypto exchanges is suspected of being driven by manipulation
false-positives produced by legacy surveillance systems when applied to digital assets
in penalties enforced by US authorities in 2018 against digital asset firms
jail sentence given to two crypto exchange owners in Korea for wash trading and manipulating volume
times the SEC mentions “manipulation” in its 90 page rejection of a recent bitcoin-ETF application
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Read MoreTackling digital asset compliance and market manipulation is not a one-company job. We’re proud to lead this effort alongside visionary partners who are changing the face of finance.
