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What is the current state of AI adoption within Financial Services and on the buyside?

💥RPA, ML techniques and NLP test understanding are the top 3 use- cases of the AI adoption within the financial services industry, according to Stanford University

💥According to Massachusetts Institute of Technology 56% of Financial Services organisations have used AI for Fraud Detection and a further 41% for finance processes and analyses.

How can AI help your Fund in active portfolio management?🔽

One of the use cases is the fusion between AI and Big Data, allowing it to run a search on the internet. The result is a highly intricate model that can predict future market movements better.

Clustering models allow you to categorize

records into a certain number of clusters. This can help you identify natural groups in your data. Clustering models focus on identifying groups of similar records and labelling the records according to the group to which they belong.

These models take your data (for example, a list of stocks) and create a scatter plot based on absolute values of the portfolio’s relative risk, which can then be arranged hierarchically.

And this is just one example of how fintech innovations can help you improve your Fund’s performance.

Take digital transformation in your Fund to another level. Get in touch with us today on

We will help you look for trading software to improve your Fund’s processes. Put this into your development plan for 2023 now.

Infographic below provided by Raconteur

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