NLP in risk management: leveraging large language models
View AgendaKey reasons to attend
- Discover practical applications of natural language processing (NLP) in risk management
- Explore controls and risk mitigation strategies for large language models (LLMs)
- Delve into current and upcoming artificial intelligence (AI) regulations
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About the course
NLP is revolutionising the financial sector, particularly with the emergence of groundbreaking LLMs like ChatGPT and DeepSeek.
This course discusses both traditional NLP methods and the latest language models. Participants will explore how to validate an LLM, select from various providers and libraries and learn techniques for fine-tuning these models to suit their organisation’s specific needs.
Through live demonstrations, attendees will examine successful risk management use cases, including text generation, information retrieval and extraction. Participants will also gain invaluable insights into effectively detecting, preventing and mitigating risks associated with these technologies.
This training also addresses key challenges in NLP implementation, such as ‘hallucinations’, data privacy concerns and legal risks, ensuring a safe and ethical deployment.
No prior technical knowledge is required to attend this course.
Pricing options:
- Early-bird rate: save up to $800 per person by booking in advance
- 3-for-2 rate: save over $2,000 by booking a group of three attendees
- Subscriber reward: save 30% off the standard rate if you are a Risk.net subscriber*
- Season tickets: save up to 60% - request price breakdown
*T&C apply, see registration page.
Learning objectives
- Identify key libraries and providers for LLMs
- Learn how to validate LLMs and identify inaccuracies
- Navigate bias, fairness and explainability in AI
- Examine strategies for customising and improving LLM outputs
- Understand the principles of prompt engineering
Who should attend
Relevant departments may include, but are not limited to:
- Risk management
- Risk technology
- Compliance
- Strategy
- Management
- IT and data
This course is best suited for practitioners seeking insights into the risks and opportunities of NLP technology, with a focus on large language models.
Tutors
Grigoris Karakoulas
President
InfoAgora Inc
Grigoris has over 26 years of experience in predictive modelling and risk management. He is the president and founder of InfoAgora that provides risk management consulting and more to financial services organisations. He is an adjunct professor in the department of computer science at the University of Toronto.
Prior to founding InfoAgora, Grigoris was working at CIBC as vice president of customer behavior analytics, responsible for customer decisioning and credit risk measurement solutions for adjudicating new customers and proactively managing existing ones. He has been a postdoctoral fellow in the Institute of Information Technology at the National Research Council. He is on the PRIMA subject matter boards for stress-testing and enterprise risk management and has published more than 40 papers in journals and conference proceedings. He holds a PhD in computer science.
Jose Blasco
Founder
Traddictiv
Jose Blasco is a distinguished expert at the intersection of artificial intelligence (AI), financial trading and risk management, renowned for pioneering the use of advanced technologies to navigate the complexities of global markets. As the visionary founder of Traddictiv PTE. LTD., he specialises in creating cutting-edge trading technologies that leverage machine learning and AI, significantly enhancing strategic market analysis and decision-making processes.
With a solid foundation in quantitative finance, evidenced by his Certificate in Quantitative Finance (CQF) and a broad spectrum of experience spanning financial trading and quantitative research, Jose’s work embodies the fusion of technical expertise with practical financial acumen. An acclaimed educator and communicator, he has been recognised with prestigious awards for his ability to demystify complex financial and technological concepts for a global audience, fostering a deeper understanding and application of AI in finance.
Jose’s multifaceted career is marked by a commitment to innovation, excellence in teaching, and a passion for bridging theoretical knowledge with real-world application. His multilingual skills and international teaching experiences further enrich his ability to connect with and inspire professionals across the globe, making him a leading authority in the evolving dialogue on AI and its transformative potential in the financial industry.
Jesús Calderón
Managing director
Maclear Data Solutions
Jesús Calderón advises Canadian and international clients in the financial services and energy industries on the implementation of data-driven solutions for risk management in banking, insurance, capital markets, and energy trading, as well as anti-money laundering and regulatory activities. Jesús has over twelve years of experience in risk management, internal audit, and fraud investigations, where he has specialized in the application of data science and machine learning methods to optimize risk control activities and examinations.
Stanislav Shcheredin
Director
Deloitte
Stan is a Director at Deloitte with c. 16 years of experience in Big4 Advisory & Assurance. In his career Stan developed quantitative analytics and AI/Machine Learning propositions for banking and large corporate clients. He holds a PhD in theoretical physics where he lead cross discipline research using machine learning algorithms that were deployed on High Performance Computing.
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