The provider of Machine Learning-powered trade surveillance platform, Solidus Labs has raised a USD3 million in a seed funding round to address a major challenge preventing greater institutional and mainstream adoption of digital assets, trade manipulation and market integrity. The funding round was led by Hanaco Ventures, along with additional participants Global Founders Capital, angel investors, and Wall Street veterans.
Founded by former Goldman Sachs FinTech engineers, Solidus Labs’ web-based platform is already deployed in the U.S., Europe, and Israel with different clients from exchanges, hedge funds, broker-dealers and market makers. According to the company, the fresh capital will be utilized to expand the company’s engineering and Machine Learning teams, in addition to sales, marketing, and customer success operations. The company accommodates rising demand from digital asset firms, as those endeavor to assure increasing regulatory oversight and high compliance standards of traditional financial institutions. According to a recent study from the Blockchain Transparency Institute, more than 80 percent of top 25 Bitcoin pairs are driven by manipulation. Further, the U.S. Securities and Exchange Commission (SEC) Chairman Jay Clayton said in November last year that the agency wants to see effective market surveillance solutions to become approving Bitcoin ETFs at ease. Moreover, the SEC and Financial Industry Regulatory Authority (FINRA) have shown that digital assets will be an inspection priority this year and currently Congress is reviewing a bill meant to tackle digital asset market manipulation.
On this note, Solidus’ Founder and CEO Asaf Meir described that digital assets provide capital markets a huge value but also add plentiful new layers of intricacy to trading workflows. In this case, more intricacy means diverse kinds of data, operational needs, new manipulation schemes and emerging regulation that legacy surveillance systems are unable to sufficiently accommodate for. Thus, to address this challenge, Solidus’ utilization of Machine Learning detection models, lessening forged optimistic alerts by at least 30 percent, with additional benefits of improved case management workflows, back-testing, extensive customizability, investigative tools, and integrated regulatory reporting features.