CompatibL is a leading provider of risk management software, model validation and quantitative consultancy services. The company’s award-winning cloud and on-premises software solution is used by financial institutions worldwide, including four major derivatives dealers, central banks and some of the world’s largest asset managers.
Our quantitative research program produced multiple innovations in models and numerical methods for counterparty credit risk, settlement risk, risk premia in the yield curve, and has been recognized by multiple awards.
Elena Ovsianko: firstname.lastname@example.org
AI technology is progressing quickly and has put real-time risk management of derivatives books within reach. Underpinned by sophisticated models requiring intense computations, the opportunities are centred on real-time portfolio analysis – on trading, exposure monitoring and capital utilization.
Riskfuel is collaborating with Microsoft and Nvidia to develop new low-cost, low-computation AI tools for the job. We would be happy to send you further details, arrange a demo, or to have a short, informal and friendly call to exchange ideas with you.
FIS Adaptiv provides solutions for enterprise-wide risk management solutions, spanning trade capture to operations management. Adaptiv Analytics is a state-of-the-art calculation engine that offers marketleading performance for market risk, counterparty credit risk, and regulatory calculations. AAD-enabled Analytics software is the latest exciting development from FIS Adaptiv. This will add to the suite of performant technologies upon which Analytics is built, which includes vectorization and GPU support, and will enable real-time calculation of exact XVA sensitivities for effective risk reporting, credit limit monitoring, and position management.
Through the depth and breadth of our solutions portfolio, global capabilities and domain expertise, FIS serves more than 20,000 clients in over 130 countries. Headquartered in Jacksonville, Fla., FIS employs more than 55,000 people worldwide and holds leadership positions in enterprise risk management, payment processing, financial software and banking solutions. Providing software, services and outsourcing of the technology that empowers the financial world, FIS is a Fortune 500 company and is a member of Standard & Poor’s 500© Index.
RavenPack is the leading big data analytics provider for financial services. The company’s data solutions, research and technology allow clients to enhance returns, reduce risk, and increase efficiency by systematically incorporating the effects of public information in their models and workflows. RavenPack’s clients include the most successful hedge funds, banks, and asset managers in the world.
Both through regulation and industry practice, there is an increasing number of risk calculations that need to be done on a regular basis. These calculations require the valuation of portfolios on up to hundredths of thousands of scenarios making them computationally very expensive in time and cost.
MoCaX technology, based on Chebyshev Spectral Decomposition methods, is a methodology and software application which massively reduces the computational burden in a risk calculation. This is achieved by pricing the portfolio on very small number of pre-defined collection of points yielding an object capable of approximating a pricing function and its greeks to a very high degree of accuracy. The object can then be evaluated on thousands of risk scenarios in an ultra-efficient and numerically stable manner.
Several benefits are obtained with this technology. Applications include Market Risk VaR, IMA-FRTB, Dynamic Initial Margin for MVA and IMM, Exposure profiles for CVA and IMM, what-if analysis tools, etc.
Yields.io is the first FinTech platform that uses AI for real-time model risk management on an enterprise-wide scale.
Our clients use our solution to speed up model validation tasks, to generate regulatory compliant documentation and to industrialize model monitoring. The platform works with all models that are used within the financial sector such as credit risk models, valuation algorithms, market risk, AML, AI and behavioural models.
Yields.io was founded by Jos Gheerardyn and Sébastien Viguié. The company is expanding quickly and has offices in Brussels and London. Yields.io has an international portfolio of clients with both investment banks as well as regional financial institutions.
Matlogica specializes in software solutions that allow to accelerate Monte-Carlo Simulations using highly parallel vectorized software and automatic adjoint differentiation. At the moment we are developing a breakthrough C++ tool for AAD. Our unique approach allowed us to obtain impressive benchmarks compared to other well known AAD tools. If you are interested in getting the best performance from your existing or new C++ library, we can offer quick proof-of-concept projects to gage the possible benefits our tool can bring to you.
Matlogica brings together a broad range of specialists: from quantitative analysts and computer science engineers to academic researchers. The company was organized around an invention which forms the kernel of the new Adjoint Differentiation Tool.
We specialize in parallel computations in a wide range of areas including XVA, MVA, Monte-Carlo Simulations, Derivative pricing and Risk, Large Portfolio simulations, Model calibrations such as Heston SV and LMM, among others.
Starts: Thursday 3rd June 2021
The objective of the course is to develop fundamental skills of quantitative developer role. The course is of an introductory level and does not require programming experience. The course is designed by practitioners from quantitative finance with experience in model development for derivative pricing and systematic trading. The primary coding languages of the course are Python and C++. As it is essential in finance to work with time series data we introduce database KDB and the language q, which are the leading solutions for storing the timeseries.
The course consists of 5 Modules:
- Python for Finance, C++ fundamentals and use cases from quantitative finance
- Data Structures and Algorithms in C++
- Databases in finance – KDB
- Design of systematic trading platforms
- Throughout the course sample test questions from quant interviews will be provided
Early Bird Discount Structure:
causaLens is pioneering Causal AI, a new category of intelligent machines that understand cause and effect – a major step towards true AI. Its enterprise platform is used to transform leading businesses in Finance, IoT, Energy, Telecommunications and others.
Current machine learning approaches, including AutoML solutions, have severe limitations when applied to real world business problems and fail to unlock the true potential of AI for the enterprise. For instance, in the case of predictions, they severely overfit and do not adapt when the environment changes. causaLens’ Causal AI Platform goes beyond predictions, providing transparent causal insights and suggesting actions that directly improve business KPIs.
causaLens is run by scientists and engineers, the majority holding a PhD in a quantitative field.
The Numerical Algorithms Group (NAG) are experts in numerical algorithms, software engineering and high-performance computing. They have served the finance industry with numerical software and consulting services for over four decades because of their outstanding product quality and technical support. Specifically, relevant to the finance industry, NAG pioneer in the provision of the NAG Library – numerical, machine learning and statistical components ideal for building Quant Libraries, Risk Applications and the like.
NAG also provides best-in-class C++ operator-overloading AD tools for CPU and GPU called dco (derivative computation through overloading) and dco/map (dco meta adjoint programming). The NAG Library and AD tools are used by many of the largest Investment Banks where they are embedded in Quant Libraries and XVA applications. As a not-for-profit company, NAG reinvests surpluses into the research and development of its products, services, staff and its collaborations. www.nag.com
Starts: Tuesday 20th April 2021
The MLI is a comprehensive six-month part-time course, with weekly live lectures in London or globally online. The MLI is comprised of 2 levels, 6 modules, 25 lecture weeks, lab assignments, a practical final project and a final sit down examination using our global network of examination centres.
This course has been designed to empower individuals who work in or are seeking a career in machine learning in finance. Throughout our unique MLI programme, candidates work with hands-on assignments designed to illustrate the algorithms studied and to experience first-hand the practical challenges involved in the design and successful implementation of machine learning models. The MLI is a career-enhancing professional qualification, that can be taken worldwide.
Early Bird Discount Structure: