This session will address challenges in financial services, such as regulatory pressure, customer expectations, and competition, and highlight trends like Explainable AI (XAI) and responsible AI. It will demonstrate how EdgeVerve’s AI First Platform is designed to tackle these challenges, empowering financial institutions to achieve their transformation goals through
- AI-powered operational efficiency and automation.
- Enhancing customer experience and fraud detection.
- Data-driven risk and innovation decisions
- Customer success stories showcasing the platform’s impact.
Join to understand how the platform’s role as a strategic partner for financial institutions in an AI-driven future.
• Overviewing ethical concerns of implementing LLMs, GenAI, models, transparency, and responsibility
• To what extent is AI considered unethical?
• Exploring the significance of AI safety and tackling risks of hallucinations in ethical audits
• Who has the answer to efficiently showcase emissions, ethics and ESGs reports supported by AI?
• Discussing potential techniques to enhance ethical data analysis and reporting using AI
In a landscape where the expectations for Generative AI are rapidly evolving, this session will delve into the critical role Graph technology plays in advancing Retrieval-Augmented Generation (RAG). As recognized by Gartner and other leading analysts, Graphs are now pivotal in enhancing the accuracy and reliability of Generative AI.
Attendees will learn how the integration of Graph technology with RAG not only addresses the inherent limitations of traditional models but also establishes a solid foundation for developing enterprise-grade Generative AI solutions that are precise, trustworthy, and capable of meeting the demands of today’s data-driven world in highly regulated industries.
To maximise the benefits of AI, business leaders must ensure investments are well-placed to drive value and competitive differentiation. Given its budgetary, security, and ethical implications, AI has rapidly become a board-level priority. It’s essential to reposition AI from being solely an IT responsibility to a collaborative effort across the entire organisation.
This session will explore the successful business outcomes that a unified strategy around AI adoption can deliver for organisations, particularly how to accelerate their AI journeys from proof of concept to production while also reducing risk.
• Join SAS and Nationwide Building Society in exploring transformative potential of Generative Adversarial Networks (GANs) and synthetic data in revolutionising risk analytics.
• Collaborating uses GANs to enhance personal loan model accuracy by augmenting default cases with synthetic data.
• How do these technologies boost model performance through a case study comparing outcomes with and without synthetic data; highlighting realistic improvements in risk analytics; and helping to discover the future of risk with generative AI.
• Evaluating challenges in enhancing APIs and ChatGPT in finance
• Discussing measures to manage data risks to protect customers?
• Investigating compensation claims and the scope to improve CX platforms
• Investigating opportunities and encouraging women working in AI
• How can we improve an imbalance in diversity and inclusion within Finance?
• Building from the past; how can we learn from others to present greater opportunities to women in AI?
• Shaping innovation and culture in AI for a better future
