Sprint Zero - Strategies for Generative AI in Finance
Hi,

We are currently evaluating use-cases for the application of generative AI in Financial Services companies.

Several companies have already begun testing generative AI products:


In our opinion, Artificial Intelligence has the potential to provide benefits in terms of speed/efficiency, objectivity, and scalability that positively create cost savings and/or increase revenue if the risks of it's application are well managed.

Speed and Efficiency:  AI tools can process and analyze vast amounts of data quickly and providing faster responses. Data quality will be an issue. If provided quantitative data, will the model use correct values along the way?

Objectivity: Despite a data bias, AI has the potential to provide more objective summaries and recommendations compared to human advisors. However, AI might struggle to understand complex relevant context.

Scalability: AI tools can perform their work 24/7/365 and can handle a large number of queries concurrently without compromising quality and speed. Yet this might lead to unrealistic customer expectations and misaligned time horizons in decision making.

But these are just our thoughts. We would love to hear yours

We only ask for a few minutes of your time to complete this survey.

With best regards and many thanks!


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Are you currently using generative AI in your operations?
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Which aspects of your business might benefit the most from using generative AI ?
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In your expert opinion, what are the largest compliance and liability problems generative AI will face getting deployed in Financial Services? And how could these be solved?
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Do you believe that Autonomous Agents (AI that reasons continuously and independently) will be able to perform some of the tasks below on the same level as a human being?
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Would you be open for a free explorative call to gain a deeper understanding of risks and benefits of generative AI in your business?
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