Incorporating artificial intelligence (AI) into back and middle office operations can focus data optimisation strategies with the potential to increase productivity, a white paper from Northern Trust and The Economist Intelligence Unit has found.
In the paper, it was noted that AI could drive revenue, improve security, and manage risk for asset managers and asset owners.
The white paper also outlined the ways in which AI is in use today. It was revealed that this ranges from the ability to predict movement to rob advisor systems that use AI to support investors in determining their asset allocation.
Companies are also using AI to both analyse structured data and extract information from unstructured and alternative data.
This can be done through image reconciliation and natural language understanding capabilities, in order to enhance business results.
According to the paper, while AI’s uses are far-reaching, it is important that an organisation establishes a clear data strategy to determine where and how AI will have the most beneficial impact.
The key is to focus first on the needs of the business and adopt a strategy that is in line with the company’s goals, the paper advised.
Penelope Biggs, CSO for corporate and institutional services at Northern Trust, said: “Certainly we see the significant ways AI can help financial services providers optimise the data they access on a daily basis.”
“It is important to think strategically about how incorporating AI and automation into business processes can benefit the end user, whether that is by reducing risk, increasing operational efficiency or enhancing overall performance.”
Biggs added: “At Northern Trust, we have a strategic plan that focuses on delivering a data-centric technology architecture aligned to our clients’ future business needs.”
“The significant investment we are making in our future-state asset servicing platform will ultimately deliver an end-to-end technology solution to our asset owner and asset manager clients globally. Incorporating the use of AI and machine learning is a key component of our strategy to optimise results and drive operational alpha.”
