Generative AI writing the future of finance

The financial services industry is abuzz with Gen AI's potential to revolutionize operations and client experience.

Boon-Hiong Chan, Deutsche Bank’s APAC Head of Market and Technology Advocacy explains why Generative AI (Gen AI) is more than just a passing fad with its ability to generate new information by learning from existing datasets.

You can also read the full transcript of the video here:

Gen AI, the new kid on the block, has got several interesting applications in banking and finance. Artificial Intelligence (AI) has revolutionized industries across the globe, with the finance sector being no exception.

From algorithmic trading, fraud detection, risk management to investment advisory, the use of AI is well established and successful.

What is different about the AI revolution today?

The AI excitement of today is actually a language revolution that democratizes high tech for ordinary people. Boon-Hiong Chan

This means that Text-based data management capabilities via large language models will allow imprecise natural language requests to be translated into precise instructions for machines to execute.

This creates a sophisticated natural language layer as a human-computer interface that puts high tech AI capabilities at the fingertips of ordinary people, to create extraordinary results.

How is Gen AI being used in financial services?

Gen AI use cases in the industry include, helping summarise documents, multiple documents, that are multilingual and to draw inferences based on chain of reasoning.

As a chat to agent when natural language is combined with statistical and other AI engine, it allows users and clients to access complex seas of data intuitively.

This solves the historical question of “I don’t know what I don’t know”. Now, AI can look for data patterns for you.

Other use cases include probabilistic scenario analysis like settlement failure, unstructured text volume analysis like in client services and emails, and investment analysis. The innovation here is that users will be directing AI to achieve business goals using their natural language.

What does the future look like?

AI adoption would first increase productivity and scale human knowledge. It is not necessarily about removing people but about how meaningful impact can be achieved within normal working hours.

AI can also enhance economic inclusion of mature workers, for example, to be redeployed to train and govern models, to be tomorrow's virtual expert assistant to democratized knowledge to benefit new professionals.

A future with AI is an empowered tomorrow where pace of change is faster and more targeted.