Recorded Webcasts
The proliferation of semi-liquid fund structures has grown substantially over the past decade, as GPs have sought new ways to offer private markets to the wealth management channel.
Adoption has simultaneously increased from investors seeking exposure to private markets while maintaining operational and tax efficiency.
Where is the interest? Where are funds being raised and in which asset classes? Is there more innovation on the horizon?
This discussion sought to answer these questions, focusing on the data and trends found in popular fund vehicles such as interval funds, tender offer funds, business development companies, and non-traded REITs.
This webinar featured members of the FDP Curriculum, Candidate & Member Relations and Operations Teams. The following topics were discussed: Curriculum materials, Learning Objectives and Practice Question review. We went over the exam structure and format, and available resources. Preparation for exam day and items permitted during the exam were covered.
The recent advancement of deep learning and large language models has had a profound influence on many fields, including finance. Speakers Nino Antulov-Fantulin and Petter Kolm provided an overview of recent ML advancements like large language models, transformers, physics-informed neural networks, graph neural networks, and their impact on decision-making, data-driven analysis, and time series forecasting in finance.
The presentation paid special attention to large language models for finance. LLMs like GPT-3 are trained through a two-step process: pre-training and fine-tuning. In this pre-training, the model is exposed to a massive dataset of texts and is trained to the next word in a sentence or filling in gaps in sentences. In essence, the model learns to understand the grammar, context, and various language patterns. After pre-training, the model is fine-tuned on specific tasks or datasets to specialize its capabilities.
In this fast-paced, ever-evolving tech landscape, AI is not just an option; it's a necessity. As a startup, understanding AI can become your game-changing strategy. This insightful webinar is specially designed to address the pressing questions startups often have about AI:
• What exactly is AI?
• How can it be leveraged within a budding business?
• What are its potential pitfalls, and how can they be avoided?
Dr. Kathryn Wilkens moderated as Dr. Stylianos Kampakis delved deep into these topics, drawing on vast experience and industry foresight. They provided actionable advice on integrating AI into your operations, sharing valuable case studies and success stories.
Map out your learning journey to obtain the FDP Charter. The FDP team answered questions about the FDP program, where to obtain your curriculum, prep providers, preparation for exam day and focused attention on our testing options.
This is a great opportunity to clearly see the steps required to have a successful exam experience.
Artificial intelligence and machine learning (AI/ML), including generative techniques, are revolutionizing the financial services sector. While they present incredible opportunities, they also come with inherent risks. Aaron Johnson, Federal Housing Finance Agency Senior Examiner guided financial professionals through essential risk management principles tailored for AI/ML applications. Dr. Kathryn Wilkens moderated as we touched upon pertinent regulatory guidelines from both the US and Europe.
Learn more about the FDP Community along with the Charter curriculum and a roadmap to prepare for the upcoming FDP exam. This session provided an outline of the curriculum, background requirements, reading materials and study tools to help you prepare.
The Financial Data Professional Institute (FDPI) has designed a self-study program to provide financial professionals with an efficient path to learn the essential aspects of financial data science. The Financial Data Professional (FDP) is a global designation for investment professionals with data science skills.
As the demand for environmental, social, and governance (ESG) goals continues to increase, asset managers are adapting their investment procedures. The shift is driven by both consumer expectations and strict governmental regulations.
To make successful ESG investment decisions, it is necessary to identify, extract, and combine granular data accurately. This requires access to high-quality and reliable data that is both quantitative and qualitative. Prioritizing data integrity is crucial for firms to move quickly, remain compliant, and demonstrate their commitment to responsible investment initiatives.
In this webinar, Zi Abraham of Verrazano Consulting Solutions LLC and Dr. Hossein Kazemi of the FDP Institute discussed the significance of ESG data, data providers, and potential data challenges. Together we explored if AI can help bridge data gaps, overcome obstacles, and scale ESG data integration.