RoboSig: Innovative High Yield Low Risk Cash Management Solutions

As a result, large global corporations, which manage cash sitting in different countries would be able to turn that challenge into a profitable lower-risk opportunity by partnering with RoboSig. Further, RoboSig ALPHA is the company’s higher return track. Its mechanism is very similar to the RoboSig Cash Management Alternative (CMA) track but incorporates a much higher amount of leverage to produce larger returns. Due to the deep liquidity of the G7 FX market and asset management, fund, brokerage, and other regulated fiduciary partners, double digit returns have proven to be equally as consistent for their investors with the RoboSig ALPHA product.

RoboSig collaborates with a number of asset management, fund, and brokerage partners. Using RoboSig technology, a partner would be able to profitably manage corporate cash that sits in most G7 countries. This cash is already in the local currency in various bank accounts such that a client can pay international employees and country specific operating expenses. The goal is to profitably convert cash from one currency to another depending on real-time spot prices to optimize the overall global return There would be no leverage introduced so that the annual returns would be in the low single digits but still be multiples higher than what would otherwise be possible in today's low interest rate environment.

We are in a unique position where the software we create has only one job that it does consistently: make money,” mentions Dieter Marlovics

One of the exciting recent developments is that RoboSig is currently forming a minority-owned subsidiary in the UK dedicated to the RoboSig strategies called RoboSig International, LTD. “The team in London that we are partnering with is world class,” mentions Marlovics. Having an asset manager like this makes it easier for any type of investor to allocate cash onto the RoboSig platform. In addition, RoboSig is continuing to make significant R&D investments to continually improve its product. “The next evolution will be for our AI to tailor its own parameters and “learn” autonomously via inline machine learning. Even higher consistency and Sharpe Ratio is the goal for when our ML strategy is integrated into the real-time decision stream to further improve our consistency and returns,” concludes Marlovics.