The Myths About Finance AI Agents
AI in finance is growing fast, but there are still many myths about it. Here, we’ll break down five common myths in simple terms.
How not to handle the AI security?
Approaching AI security in finance shouldn't be about fear—it should be about empowerment. Secure AI allows companies to innovate confidently, knowing that sensitive information is protected. Security measures create a safe environment where AI can perform...
The Role of AI agents in Enhancing Collaboration between Controllers and FP&A
In today’s dynamic business environment, maintaining financial health while preparing for growth requires more than just balancing the books. Controllers and Financial Planning & Analysis (FP&A) teams, both essential pillars of financial management, often find...
What we learnt from deploying ChatFin AI in finance teams
At ChatFin, we've had the unique opportunity to collaborate with some amazingly forward-thinking finance teams across various industries. These teams, led by leaders who not only embrace change but actively seek it, believed in the transformative power of AI and...
The Answer Is More Straightforward Than You Think: Finance AI—Build vs. Buy?
When it comes to implementing generative AI applications in the finance sector, the debate between building in-house solutions versus purchasing from vendors can seem complex. However, the decision often leans convincingly towards buying. Here's why this choice is not...
What is the difference? ChatFin Vs ChatGPT
ChatFIN is a purpose-driven language model. It is designed specifically for accounting and finance. ChatFIN not only understands finance and accounting contexts but also has the ability to operate data.
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The call for faster,accurate, smaller and affordable models which can serve the needs of enterprises.
Myths of A.I in corporate finance
In finance, we always thought A.I is a black box and its hard to build trust and consensus on the results produced.
9 Critical Pitfalls to Avoid on the AI Journey in Finance
Traditionally, finance professionals have used Excel for modeling, but that Excel tends to produce inaccurate results because it overgeneralizes the relationship between several data elements.
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