Our client, a Tier-1 US bank, commissioned an investigation of the current practices employed across the banking industry regarding the governance and risk management processes for e-Trading algorithms (algos) that incorporate a model component (or feeder).
The obligations and definitions for model risk management set out in the Fed’s SR11-7 have caused a high level of confusion in US institutions active in the algorithmic (algo) space. The definition of a model, in particular, is so broad that in some circumstances it may cover not only quantitative financial models but also algorithmic trading tools and components.
The client, a pre-revenue fin-tech payments and mobile commerce start-up acquired the technology assets from another firm and wished to bring a new offering to market in the mobile commerce and payments space within a 9 month timeframe. The assets acquired, however, were limited by a number of architectural short-comings.
The client engaged GreySpark to perform financial and product capability analysis of a trading technology vendor that services both buyside and sellside financial institutions.
The client, a US-based multi billion-dollar Private Equity Fund, considered investing in companies that specialise in electronic trading systems across cash equities, listed derivatives and fixed income. The client’s assessment of the investment opportunity was incomplete by having limited knowledge of electronic trading across those asset classes.
The client was running an obsolete FX trading platform that could not be updated or extended due to lack of source code. The client wanted to design a new scalable and robust platform from scratch which would support low latency trading. The source code would be fully owned by the client.