Within the domain of capital markets trading, investing, structuring and risk management, next generation technology and emerging digital approaches are beginning to make headway to enhance current industry practices and functions, not least towards achieving more dynamic projections, better foundations for modeling, and greater scalability to handle complex scenarios and expanded risk metrics in a timely manner.
Regulators, internal stakeholders, customers, and investors are demanding more transparency in understanding the trading, investment, risk, and capital models — from trading algorithms and capital models to newly emergent retail credit risk models that incorporate statistical learning approaches. Transparency and governance demands are required not only at an analytical level, but also in development workflows and lifecycle activities associated with quantitative, strategy development/testing, risk models, and data. With these developments, one imperative that we believe to be significant in the coming years is the emergence of what Celent terms “QuantTech” platforms powered by next-generation data science technologies.
In the years to come, the convergence of QuantTech, data science, and its ecosystem of technologies that have emerged in recent years will fundamentally alter how quantitative groups develop, model and collaborate. As part of Celent’s ongoing research into quantitative and analytical solutions with data science capabilities, Beacon Platform briefed Celent about their solution platform through briefing sessions and demos by relevant subject matter experts and senior management from the firm.
This Briefing Note highlights Beacon Platform's solution proposition and provides our perspectives on the opportunities, benefits, implementation considerations and caution points for firms looking to chart their journey to leverage next generation capabilities.
