Quantifi’s data science platform provides clients with the ability to do complex data analysis and flexible reporting using Python, Jupyter Notebooks and other popular data science tools. Integrated with Quantifi’s proven portfolio management solution, users benefit from complex client-driven analysis, strategy back-testing, ad-hoc portfolio what-if analysis – all using mixed data sets from diverse sources.
In this presentation, experts from Quantifi and Intel explain how leveraging Intel’s latest hardware can accelerate the performance of largescale XVA workloads by increasing performance of the CPU and improving the efficiency of I/O.
The IBOR reform represents one of the biggest challenges facing financial services firms. Successful management will require significant change and strategic risk management. Preparing for the transition will require firms to establish a strategy to assess the impact and navigate transition risks. Is your firm ready?
Regulators, internal stakeholders, customers, and investors are demanding more transparency with understanding of front office, risk, and capital models – from trading algos, capital models to counterparty risk models that incorporate statistical learning approaches.
Quantifi’s 6th annual risk conference, at The Harmonie Club, New York, attracted delegates from across the industry for a compelling afternoon of unique insights and discussion on the dynamics driving capital markets. Topics covered included navigating the IBOR transition, concept drift in machine learning and the rise of fixed income ETFs.
Quantifi’s 7th annual risk conference, at Armourers’ Hall, London, attracted delegates from across the industry for a compelling afternoon of unique insights and discussion on the dynamics driving capital markets. Topics covered included navigating the IBOR transition and the rise of fixed income ETFs.
Following the credit crisis of 2008, tranche trading all but disappeared; it is now back with gusto. For example, bespoke tranche trading reached $80 Billion issuance in 2018, and continues to grow rapidly. Although a far cry from pre-crisis level, there are encouraging signs for the market’s revival.
With the increasing demands from customers, greater regulatory requirements and cost efficiency pressures, more and more firms are embracing cloud strategies to address the modern business imperatives of performance, flexibility, scalability and agility.
Forward-looking investment management firms are searching for ways to outperform their peers. The firms that we see succeeding are executing based on a combination of focused business models, agile operational competency, and strong cost discipline, especially around core investment and risk functions.
New technologies including AI, big data, Cloud, microservices, Modern CPUs, In-Memory Computing, Lambda Architectures and blockchain are reshaping how firms operate. Quantifi is at the forefront of these changes and our advanced architecture provides clients with significant value and competitive advantage. New technology brings significant benefits in usability, flexibility, scalability, and performance.
Rohan Douglas, CEO, talks about how Quantifi is leveraging Intel to enhance performance. Performance is critical to our clients being able to accurately measure their risks. For example, calculating the counterparty exposure for a mid-size bank’s trades may involve over 25 trillion trade valuations, each of which requires significant computation.
Quantifi’s 5th annual risk conference, at The Yale Club, New York, attracted delegates from across the industry for a compelling afternoon of unique insights and discussion on the dynamics driving financial markets including AI/machine learning for investment managers, funding costs (KVA, FVA, MVA) for derivatives trading and impact of blockchain on the global financial markets.
Quantifi’s 6th annual risk conference, at Salters’ Hall, London, attracted delegates from across the industry for a compelling afternoon of unique insights and discussion on the dynamics driving capital markets. Topics covered included IM requirements for cleared and bilateral trades, market changes post MiFID and the role of AI/Machine learning in financial services.
FRTB is set to revolutionise current market risk practices, placing emphasis on the coordination of operational, risk and data management processes as well as systems and technology. To best respond to these new demands, banks need to make the right strategic and technology decisions and assess the impact on operations and processes across risk, front office, finance and IT.Co-hosted by Quantifi & Monocle Solutions
Quantifi recently took part in Intel’s Coffee Chat series to discuss their partnership with Intel. In this video, Intel Vice President, Pete Baker discusses risk analysis, analytics and artificial intelligence on Intel architecture in the financial services sector with Sebastian Hahn, AI Lead, Quantifi.
What if you could increase alpha by trading across a range of asset classes, grow AUM while satisfying investor and regulatory demand for transparent and detailed risk reporting, and reduce costs by simplifying data management and operations – all within a next generation system that is open, flexible and simple to implement?
Quantifi breaks down the results from its recent survey on the Fundamental Review of the Trading Book (FRTB). 106 banking practitioners were surveyed to measure opinion on how prepared their firms are for dealing with the impact of FRTB and their approach to addressing implementation challenges.
New challenges in the financial markets driven by changes in market structure, regulations and accounting rules like Basel III, EMIR, Dodd Frank, MiFID II, Solvency II, IFRS 13, IRFS 9 and FRTB have increased demand for higher performance risk and analytics. Problems like XVA can be extremely computationally expensive to solve accurately. This demand for higher performance has put a focus on how to get the most out of the latest generation of hardware.
Schedule a personalised demo today