Julia Bardmesser

David Steffa of Snowflake and Jessica S. of Dropbox sharing their perspectives on a San Francisco #Treasury Symposium #sfts panel about how to deal with the current #rate environment. There are things that are outside of your control (e.g., #Fed rate cuts/hikes) but you can focus on things that are within your control (e.g., solid #cashflowforecasting). And, like also heard on other panels today, #ESG investing came up as a passion project for many, but not all, Treasurers.

120

6 Comments

𝗤𝘂𝗮𝗻𝘁𝘂𝗺: 𝗳𝗿𝗼𝗺 𝗳𝗿𝗶𝗻𝗴𝗲 𝘁𝗼 𝗳𝗿𝗼𝗻𝘁𝗹𝗶𝗻𝗲. Bloomberg Originals has dedicated an entire episode to this groundbreaking field, hosted by the brilliant Hannah Fry. Hannah masterfully breaks down complex concepts for a general audience, making quantum accessible without losing its essence. While purists will note some simplifications, the episode succeeds in igniting curiosity and understanding. "𝘛𝘩𝘦 𝘲𝘶𝘢𝘯𝘵𝘶𝘮 𝘧𝘶𝘵𝘶𝘳𝘦 𝘪𝘴 𝘢𝘣𝘰𝘶𝘵 𝘣𝘶𝘪𝘭𝘥𝘪𝘯𝘨 𝘢 𝘴𝘤𝘪𝘦𝘯𝘵𝘪𝘧𝘪𝘤 𝘵𝘰𝘰𝘭 𝘵𝘩𝘢𝘵 𝘢𝘭𝘭𝘰𝘸𝘴 𝘶𝘴 𝘵𝘰 𝘴𝘦𝘦 𝘢𝘯𝘥 𝘶𝘯𝘥𝘦𝘳𝘴𝘵𝘢𝘯𝘥 𝘵𝘩𝘦 𝘶𝘯𝘪𝘷𝘦𝘳𝘴𝘦 𝘥𝘰𝘸𝘯 𝘢𝘵 𝘵𝘩𝘦 𝘭𝘦𝘷𝘦𝘭 𝘰𝘧 𝘢𝘵𝘰𝘮𝘴 𝘪𝘯 𝘢 𝘸𝘢𝘺 𝘵𝘩𝘢𝘵 𝘸𝘦 𝘩𝘢𝘷𝘦 𝘫𝘶𝘴𝘵 𝘯𝘦𝘷𝘦𝘳 𝘩𝘢𝘥 𝘢𝘤𝘤𝘦𝘴𝘴 𝘵𝘰 𝘣𝘦𝘧𝘰𝘳𝘦.... 𝘵𝘩𝘪𝘴 𝘪𝘴 𝘴𝘰𝘮𝘦𝘵𝘩𝘪𝘯𝘨 𝘢𝘭𝘭 𝘰𝘧 𝘩𝘶𝘮𝘢𝘯𝘪𝘵𝘺 𝘸𝘪𝘭𝘭 𝘴𝘵𝘢𝘯𝘥 𝘵𝘰 𝘣𝘦𝘯𝘦𝘧𝘪𝘵 𝘧𝘳𝘰𝘮." Honoured to have contributed to this episode alongside Dario Gil, Andrew Shields, Alexander Ling, Olivia Lanes, PhD. Quantum tech is no longer a future concept - it's our present reality, shaping industries and pushing the boundaries of what's possible. Ready to dive into the quantum revolution? Watch the full episode here: 📺 https://lnkd.in/e_8uBk7M #QuantumComputing #FutureTech #Innovation #BloombergOriginals.

60

1 Comment

This could be a game changer toward democratising the creation and training of LLMs, Prime intellect an AI startup creates first distributed LLM across three continents. More details in comments. #LLMs #GenAI #AI

10

4 Comments

Excited to share insights in this CU Management article on the transformative power of AI in the credit union industry. From enhancing member experiences to optimizing operations, AI is a game-changer. Proud to be part of this conversation and to see how AI is shaping the future of financial services. #AI #creditunions #memberservice #GenZ #financialservices #Innovation #CUmanagement

46

1 Comment

You see the tremendous potential and want to implement Gen AI at your organization - so where do you begin? This article helps you get organized. The list is short, but the journey is long - start now! #LLMs #GenAI #AIGovernance #ResponsibleAI #ValidMind

17

3 Comments

"Our discussion with Citigroup's Murli Buluswar underscores the critical importance of a robust data foundation, a proactive and curious data culture, and strategic alignment of AI and analytics initiatives." Check out this blog to learn more about a recent discussion with our CEO Justin Borgman and Murli Buluswar, Head of US Consumer Analytics at Citi about how to build a strong data foundation: https://okt.to/3DezpA #datafoundation #AI #datalakehouse

13

🌟 New from #NVIDIAResearch: Weight-Decomposed Low-Rank Adaptation (DoRA). A groundbreaking advancement in fine-tuning technology that's set to revolutionize how we optimize pretrained models without increasing inference costs. 👀 https://dy.si/HXvUD9

8

AI is rapidly transforming #banking, and the dynamic landscape of #GenAi demands a strategic approach to operating models. Banks & other financial institutions should balance speed of deployment & innovation while managing risks. This McKinsey & Company article outlines strategies that can help financial services companies to align their GenAI initiatives with strategic goals to maximize outcomes. Scaling GenAI solutions isn’t straightforward, and banks need to have the right #operatingmodels in place to fully capitalize on this emerging technology. Read the article here: https://lnkd.in/eyQiGx67

26

Join Gerard Francis at Snowflake Data Cloud Summit to learn about the newly launched Containerized Data solution from Fusion by J.P. Morgan. Discover how Fusion leverages standardized data containers and Snowflake's AI capabilities, including Cortex, to deliver rapid insights to clients. #datamanagement #AI https://lnkd.in/eipHftk4

32

"#ACE combines economic principles, mathematical concepts, and advanced computer simulations to create tailored #agent-based models for economic analysis' via Ilan Gleiser

2

While still a small segment of the ETF market, actively managed ETFs are gaining momentum. Active ETFs now comprise almost 9% of ETF assets under management, a significant increase from 2% in 2019, as per Morningstar data. Investors and financial advisors favor ETFs for their tax advantages, intraday trading capability, and transparency into holdings. Notably, the attraction to ETFs lies in their cost efficiency, making them a compelling choice for many. #ETFs #Investing #Finance #ActivelyManagedETFs #FinancialAdvisors

1

I came across this study from McKinsey that states that AI adoption is surging to a record high, and Gen AI is performing well, but data barriers and risk need to be addressed (maybe not such a big surprise). What I like in this survey is the message that AI and Gen AI have begun to create real business value and don't only exist as garage projects in an IT organisation; I notice that Risk, Legal, and Compliance reports increased revenue and that HR reports the most significant cost decrease. I'm realistic, but this is a good way to start the value conversation. That is a strong signal that business adoption is moving in the right direction. Unsurprisingly, the industry technology is most likely to invest in AI. I think financial services are forced to adopt AI to be cost-effective and comply with regulations. Interestingly, energy and materials are more prominent than media. Given the insights from the McKinsey study, I'm keen to explore the AI landscape in the Nordics. Localised research could shed light on any potential lagging of AI adoption in our region.

8

What if private equity firms could leverage technology leadership to increase portfolio value? Our latest video explains how. Interested in learning more about Fortium's expertise and impact in the PE landscape? Visit our Private Equity page: https://gag.gl/cw8yx0 #privateequity #leadership #technology

3

Last week, I spoke with COCC about actionable strategies for C-Suite executives in the #banking and #financial services industry to navigate #AI and emerging #tech. We focused on practical steps for integrating AI to enhance decision-making, optimize processes, and more. Thanks to Richard Leone and Jillian Flaherty for having me. #speaker #keynote #keynotespeaker #financialservices #technology #fintech #artificialintelligence #csuite

22

2 Comments

Combining the muscle memory of past cycles in #markets with new ideas and ways of thinking is crucial to lasting success. Chris Pizzotti, global head of FX voice trading at State Street Global Markets, joins #STTStreetSignals to talk about his experiences in #trading and answer the most pressing questions in #macro markets today. Is #volatility back for good or will it subside as quickly as it rose? How aggressive will the #FederalReserve and #BOJ be in signaling policy intentions? And what does it mean for the #USD, #JPY and #EM FX markets? http://ms.spr.ly/6049mZxWx

2

Building a generative AI ecosystem in credit risk of financial institutions To capture the full potential of generative AI in credit risk, financial institutions must move beyond today’s adhoc approach and develop a common set of practices to prioritize, develop, deploy, maintain, and reuse generative AI applications. Eight such practices are essential: 1. An AI road map. This should align with the organization’s broader business strategy, explain the required capabilities and solutions, and provide a timeline for development, launch, and deployment at scale. 2. Aligned processes for building generative AI tools. These should support rapid but safe end-to-end experimentation, comprehensive validation, and the deployment of solutions. 3. A secure, generative AI-ready technology stack that supports hybrid-cloud environments, so companies can access the computing power they need to train models and then run them at scale. Such a stack should be able to manage unstructured data, train and execute models, and pre- and postprocess data. 4. Integration with enterprise grade foundation models and tools. These are large deep-learning neural networks, such as large language models that underpin advanced generative AI systems, along with software toolkits that support their customization and deployment. Generative AI applications use such models directly or build on them to develop proprietary solutions. 5. Robust automated supporting tools. These include machine-learning operations (MLOps) and appropriate data infrastructure and processing pipelines to support the development, release, and maintenance of use cases. 6. A governance and talent model that can deploy cross-functional expertise to support generative AI development. The people providing this expertise might include software developers, NLP specialists, teams to run reinforcement learning based on human feedback (RLHF), cloud computing specialists, AI product leaders, and legal and regulatory experts. 7. A modular solution architecture. This allows parallel development and customizable connections across different layers, such as the UX layer and the business logic layer. 8. AI services and solutions. The items in the library can be plugged into a range of business scenarios and applications across the credit value chain. From McKinsey Insights: Embracing generative AI in credit risk https://lnkd.in/dE7th7rK

5

Some more thoughts from the IBM event in NY this past week. It was clear that the efforts to bring 160,000 consultants up to speed to evolve IBM's $2B book of business is a high priority. It is being executed broadly to take advantage of an expanding TAM as AI's impact is felt across industries around the world. IBM is already seeing that costs are top of mind among its customers and prospects, as Shawn Rogers and I found in our recent primary research conducted for BARC(https://lnkd.in/gy_zS9TZ). There was much discussion of IBM's Granite models (https://lnkd.in/gszuu7AF). It was an eye-opener for me personally to see how much benchmarking and effort have gone into creating deliverables that are not falling prey to what seems to be a common belief that more is always better - demonstrating that smaller, more targeted models can outperform at a lower cost. Eileen Lowry talked about the compelling new offerings in IBM Consulting Advantage, a platform that will enhance productivity for developers and users alike. A strong focus on usability and delivery will serve IBM well, leveraging the reliance its customers have leaned into for decades on the company's trustworthiness. Rob Thomas and Dario Gil highlighted trends to come, such as multi-agent orchestration, speculative decoding, more and more open source, and the impact of using more than the 1% of enterprise data that is typically represented in foundation models. Data at the heart of it all was a recurring theme, and I could not be happier to hear this ringing affirmation. Although Arvind Krishna made it clear he sees Quantum as one of IBM's 3 largest growth areas by percentage over the next few years, he also asserted, in response to a provocative question from Sanjeev Mohan, that those who know IBM "do not have the impression anymore" that IBM is a legacy vendor. It's a tribute to his leadership that heads nodded around the room when he said so. IBM is adding clients in the thousands year over year, he said. There is so much more I could talk about but I will close with one of my favorite pieces of phrasemaking: the reference to IBM's zTPS as "the OG Platform." IBM continues to embrace its mainframe legacy, as it should. The z platform embodies the distinction between "technical debt" and "technology asset."

83

1 Comment

If you’re not using LLMs or AI capabilities at your bank, it’s going to impact the customer experience. Want to re-architect banking around your customers? Then there needs to be top-down dedication and commitment to adopting these new technologies. Delaying AI adoption can directly impact your company’s bottom and top lines. Not using these technologies can lead to: → Problems delivering differentiated experiences for your customers → Lagging behind competitors that adopt new technologies → A negative impact on your balance sheets and income Want to know more about AI developments at banks? Feel free to DM me or tune in to episode 8 of the ‘Banking Reinvented’ podcast.

44