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Insights and key takeaways from FIMA Connect UK 2024: Pioneering efficient AI integration

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FIMA Connect has always been a cornerstone event for finance professionals looking to integrate cutting-edge technology and strategies. During this year’s edition, the spotlight was on effectively implementing AI and leveraging Large Language Models (LLMs) to transform business and their operations.

In this blog, you’ll discover key and practical takeaways from the conference, emphasizing the crucial pillars of data governance, lineage, and quality for successful AI deployments. It’s great to see AI has moved from being a curious, anxious mode to ‘show me’ the value and what the route is to live!

Key takeaways

  • Building a strong foundation: Ensure safe and secure AI by focusing on data governance, clear data lineage, and data quality controls.
  • Data is king. Clean, secure, and well-governed data is essential for optimal AI performance and regulatory compliance.
  • Security in Products with AI: Implement robust security protocols to protect sensitive data when outsourcing data processing.
  • Invest in your people. Develop a skilled workforce through continuous learning programs to effectively leverage AI and LLMs.
  • AI for good: Be mindful of the environmental impact of AI models and choose models that promote responsible AI use.

Integrating the right tech stack for AI

A major focus at FIMA Connect was the importance of assembling a tech stack that supports advanced AI capabilities responsibly. As organizations deepen their commitment to safe and secure AI, they are concentrating on deploying systems that adhere to compliance, regulation, and organizational values. This requires robust data governance, a clear data lineage, and stringent data quality controls as foundational elements to ensure AI operates within ethical bounds and delivers reliable results.

Leveraging AI and LLMs for increased efficiency and alpha

Financial institutions are increasingly harnessing AI and LLMs to enhance productivity and operational efficiency. The key to success lies in the readiness and quality of the data. As discussed at FIMA Connect, ensuring that data is clean, well-governed, and secure not only enhances the performance of AI applications but also ensures compliance with consumer protection regulations. The shift from mere curiosity about AI to measuring its tangible value was a critical topic, emphasizing the need to have a clear framework for evaluating AI’s impact on business outcomes. Opening new channels and use cases to consume data in a natural and conversational way, leveraging large AI models, were of particular interest.

Ensuring security in products with AI 

With many organizations buying products that have AI in them, data processing and managing the security of this data have become crucial. FIMA Connect stressed the importance of robust security protocols to protect proprietary information. Effective strategies include establishing clear contracts, conducting regular security audits, and adopting state-of-the-art encryption methods to safeguard data.

Developing a skilled data and analytics workforce

Another focal point of the conference was the development of a skilled workforce capable of leveraging AI and LLM technologies effectively. Continuous learning and development programs are essential in keeping the workforce adept and well-prepared for rapid technological advancements. Many of the enterprises have started an AI Centre of Excellence to involve and work with people in building capabilities and defining specific use cases and experiments.

Responsible AI usage and carbon footprint awareness

A new but increasingly important area of discussion at FIMA Connect was the environmental impact of AI technologies. The conference highlighted the need for awareness of the carbon footprint associated with deploying AI models and the importance of choosing models wisely to demonstrate responsible usage. Organizations are encouraged to consider the environmental costs of their AI deployments and seek more sustainable practices in model applications.


FIMA Connect provided profound insights into how financial institutions can use AI responsibly and effectively, emphasizing the importance of data integrity, security, and ethical practices. The conference also put a spotlight on the environmental impact of AI implementations, urging a sustainable approach. These discussions offer a roadmap for organizations looking to lead in the competitive finance sector by using AI technologies responsibly and efficiently. Incorporating these insights into strategic planning ensures that organizations are prepared to handle modern finance challenges while positioning themselves as leaders in ethical and effective AI use.

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Prasad Prabhakaran is a product manager with 23 years of expertise in data and AI, currently leading the AI practice at esynergy. An ex-Microsoft employee, he has also successfully bootstrapped and built his AI startup. Prasad specialises in developing data- and AI-based products. His work focuses on achieving problem-solution fit, product-market fit, and driving user and community engagement. He effectively aligns teams, prioritises development, and delivers solutions that drive business value.