Use case.

Financial analyst assistant.

Streamline financial analysis by using an AI-powered assistant to instantly correlate historical data from Fortune 500 profiles, uncovering insights that may have taken hours to find manually. This tool provides faster and more accurate financial assistance by delving into financial archives.

Can you provide an analysis of Apple's revenue growth over the last five years and its implications for the tech industry?

Copilothelps to specify your intents.

Model used

Filter on Filters

Apple's revenue has grown approximately 7.3% annually over the last five years, driven mainly by iPhone and Services sales. This growth sets a benchmark in the tech industry and indicates healthy demand in consumer electronics and digital services, offering opportunities for other industry players.

LLM:

Filters:

Streamlined financial analysis

Cuts manual financial research time significantly

Enhance decision-making through real-time analysis

Reduces risk of human error by leveraging data-driven algorithms

What you previously had to do.

Manually compile and analyze financial data from multiple sources, spending hours sifting through financial statements, balance sheets, and market reports.
Struggle with identifying trends and insights across vast datasets, relying on cumbersome spreadsheets and potentially overlooking key investment opportunities.
Struggle with identifying trends and insights across vast datasets, relying on cumbersome spreadsheets and potentially overlooking key investment opportunities.

What this task now looks like.

Access an integrated platform that swiftly compiles and correlates financial data from Fortune 500 profiles, enabling real-time insights that can be retrieved instantly.
Utilize advanced algorithms that automatically analyze and identify market patterns, trends, and investment opportunities, transforming raw data into actionable intelligence.
Utilize advanced algorithms that automatically analyze and identify market patterns, trends, and investment opportunities, transforming raw data into actionable intelligence.

You can choose from various LLMs.

For this use case, we recommend Azure GPT-4.

OpenAI

You can integrate the famous ChatGPT-model from OpenAI as an API.

Microsoft Azure

Host OpenAI's ChatGPT-model on Microsoft Azure. Can be hosted in Europe with added security.

HuggingFace

HuggingFace is an AI ecosystem of open-source LLMs, which can be self-hosted on demand.

Mistral

Fast, open-source and secure language models. Facilitated specialisation of models on business use-cases, leveraging private data and usage feedback.

Train from different data sources.

Data examples.

You can train your Generative AI assistant from different data sources. Here are some examples.

This might also be relevant for you.

Further resources

We have collected a list of resources that might be helpful for you to learn more about this use case.

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Pioneering Innovation: How GenAI is disrupting Finance & Banking - with free ebook download

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Pioneering Innovation: How GenAI is disrupting Finance & Banking - with free ebook download

An actionable guide to the diverse elements of Generative AI in Finance and Banking that are changing the landscape of productivity, customer experience, and the way the industry operates.