Generative AI (For Finance)
Hello! We’re back again with another edition of Fin AI Briefings. The earlier two iterations focused on Enterprise AI and AI to combat AI-driven fraud. This time, we are focusing on Generative AI in the context of finance.
Generative AI is a term that was popularized by the arrival of conversational AI platforms such as CHATGPT. It prompted organizations to think about the use cases of this novel technology – the use cases that extend beyond elaborate chatbots.
Finance as a niche creates and thrives on data. Generative AI, too, relies on the quantity and quality of data. When you put two and two together, it’s a perfect match. This is the reason why CFOs and decision-makers across financial institutions are scrambling to understand how Generative AI will impact the finance sector – in the short and the long run.
Gartner, on the spectrum of the hype cycle of emerging technologies, placed Generative AI right between the ‘Peak of Inflated Expectations’ and ‘Trough of Disillusionment.’
The technology that was the talk of the town. How could it plateau? Or is it even plateauing?
Every new technology undergoes this shift. Heightened expectations get people excited, and when they’re met with slow advancements, perception changes. The fact is that Generative AI is indeed a powerful technology, especially for the financial sector.
Finance insights engines, autonomous agents, risk assessment, fraud detection, predictive analytics, and cash flow forecasting are some of the cases in which Generative AI is and can be used in finance. Let’s catch up on what experts and thought leaders have to say about it.
For Financial Institutions, Generative AI Integration Starts Now. [Wolters Kluwer]
Gen AI offers opportunities for financial institutions in risk and compliance. Automating regulatory analysis, decision-making, and fraud detection are some of the key use cases. Integration, however, requires ‘AI stewards’ across business functions, along with compliance with regulations such as the AI Act in Europe.
Societe Generale Shares its Strategy for Integrating Generative AI Into the Financial Sector [Societe Generale]
At the AI For Finance 2024 event in Paris, Societe Generale outlined its strategy for integrating Gen AI to drive financial sector transformation. The focus is on processing unstructured data to enhance client experience and improve risk management while managing associated risks and costs – with over 300 AI use cases in production.
Main GenAI Benefit, So Far, is Time Saved, Finance Execs Say [CFO Dive]
So far, Gen AI’s primary benefit has been time-saving, freeing employees from manual tasks to focus more on strategic work. Quantifying its ROI remains a challenge, but executives expect clearer metrics in the future. The tech’s rapid evolution further creates uncertainty about its long-term impact.
Navigating the Ethical Dilemma of Generative AI in Finance [Prashant Chaturvedi]
For the finance sector, Gen AI, with all the potential and opportunities, brings ethical challenges, such as potential job displacement, dependency on algorithms, bias, regulatory gaps, and data privacy risks. Innovation must be balanced with responsibility to avoid creating industry control solely by algorithms.
What’s the Difference Between Generative AI and Predictive AI? [Arya AI]
Both technologies have the potential to transform the finance sector but differ in what they can do. While generative AI suits innovative tasks, predictive AI excels in operational efficiency. Generative AI is focused on creating synthetic data, personalizing experiences, and supporting fraud detection, report generation, and engagement. On the other hand, predictive AI helps with historical data analysis, risk assessment, credit scoring, and market trend forecasting.
Generative AI in Fintech Market Analysis 2019-2023, and Forecast 2024-2029 by Component, Deployment, Application, and Region with In-Depth Competitive Analysis [Fintech Futures]
Valued at USD 1.13 billion in 2023, the market for Gen AI is expected to reach USD 7.28 billion by 2029. Key drivers include the increasing volume of financial data necessitating advanced analytics, the demand for personalized customer experiences, and the need for enhanced compliance and risk management. Regionally, North America led the market in 2023 and is anticipated to maintain its dominance.
The Future of the CFO: Generative AI as a Finance Growth Catalyst [Workday]
Erik Brynjolfsson of Stanford highlights that Gen AI is the most significant technological advancement in three decades. Michael Schrage from MIT emphasizes the importance of treating data as a valuable asset. Generative AI can unlock organizational knowledge, as evidenced by a call center company that achieved a 14% productivity increase by implementing an AI-based conversational assistant.
The Build vs. Buy Debate: GenAI and the Future of Software Development [Dev Interrupted]
Delve into the discussion focused on the considerations enterprises must evaluate when deciding to build or purchase Generative AI solutions. It outlines the pros and cons of each approach, including factors like cost, customization, time-to-market, and resource allocation.
Is Generative AI Infrastructure a Good Investment? [Shriftman]
Generative AI infrastructure is changing how we create, compute, and innovate, but investment opportunities are complex due to inflated multiples (~145x) and competition from tech giants offering free tools to drive cloud adoption. Value lies in data, compute, and talent, with niche players and open-source platforms carving opportunities through partnerships and premium models.
A Comprehensive Guide to Building a Custom Generative AI Enterprise App [Madhukar Kumar]
To build a custom Generative AI enterprise app, securely run LLMs within your network. Organize your data with hybrid vector databases for efficient searches and context retrieval. Finally, integrate a "Search and Prompt" system to connect user queries with curated data, enabling the AI to generate tailored and secure responses. This approach ensures privacy, scalability, and relevance in enterprise AI applications.
Future of Finance: AI and GenAI's Transformation [Christophe Atten]
Explore how Artificial Intelligence, particularly Generative AI, is transforming the finance industry. It highlights applications in areas like risk assessment, customer service, and financial forecasting, and discusses the implications for financial institutions and professionals.
This time, we had the privilege of inviting Ashish Rai, the CEO of Aurionpro, to shed light on the potential of Generative AI in finance. Drawing from his extensive experience in driving innovation for the FinTech space, Mr. Rai shares his perspective on this groundbreaking technology.
👉🏼Podcast: What an AI-powered finance function of the future looks like [McKinsey]
👉🏼 Article: What is an Automated Underwriting System? [Arya AI]
👉🏼 Podcast: What AI can and can’t do in financial services [11:FS]
👉🏼 Article: The Role of AI in Automating Loan Origination [Arya AI]
👉🏼 Report: An Analysis of Generative Artificial Intelligence and International Trade [WEF]
👉🏼 Generative AI: My Experience [Alex Geller]
👉🏼 Transforming Finance: Exploring the Potential of Generative AI in Finance [Apoorv Gehlot]
👉🏼 Podcast: AI in Financial Services [Daniel Faggella]
👉🏼 A Deep Dive on AI Inference Startups [Eastwind]
We hope you enjoyed reading this edition of Fin AI Briefings. Let us know in the comments if you did! Click on the Subscribe button for the new issue.