In the fast-paced and ever-evolving world of asset management, maximising returns and future-proofing the back and middle office is crucial for all investment firms’ success.
With advancements in data analytics and global automation, financial institutions have a unique opportunity to streamline efficiency, drive innovation, and stay ahead of the curve.
So what are some of the key strategies and innovative solutions that can help investment organisations achieve these goals.
Maximising returns: harnessing the power of data analytics
Data analytics has become an indispensable tool for maximising returns. By adopting a data-driven approach, organisations can gain valuable insights to inform their decision-making processes. The key is to integrate data analytics into every aspect of a business; from development to operations.
One effective strategy is to build data analytics directly into applications and solutions. By embedding analytics capabilities, organisations can streamline processes, identify inefficiencies, and make informed decisions that have a maximum impact. This data-driven approach ensures that solutions are tailored to meet the specific needs of the organisation and its clients. It’s the approach our product development team takes, building out our connected ecosystem within the Fund Information Hub. Data analytics and the ability to draw and extract insights are front and centre to help our clients optimise their fund data management and reporting processes.
Future-proofing: navigating complexity and regulatory demands
While it's impossible to future-proof entirely, organisations can take proactive steps to navigate complexity and regulatory demands effectively. Asset management, for example, requires continuous product innovation to adapt to evolving market dynamics. Future-proofing in this context involves being responsive to portfolio strategy and continuously exploring new avenues for growth.
Furthermore, regulatory requirements pose a significant challenge for the middle office. As regulations become more stringent, the complexity of ensuring compliance and safeguarding assets increases. Organisations must anticipate the data requirements that will be necessary downstream and incorporate them into their product manufacturing process. This proactive approach minimises the impact of regulatory changes and ensures seamless operations across various functions, such as regulatory reporting, marketing, and distribution.
Data analytics and workflow automation: a powerful combination
Data analytics and workflow automation go hand-in-hand when it comes to maximising efficiency and scalability. Implementing automation technologies can significantly improve throughput, enhance scalability, and reduce reliance on manual processes. However, it is crucial to start small and pick up wins gradually before scaling automation initiatives across the organisation.
A data science approach is essential for leveraging automation effectively. This involves identifying the parts of the value chain that generate valuable data, implementing robust data management practices, and working closely with product teams to extract meaningful insights. By feeding these insights back into the product life cycle, organisations can continuously improve their offerings and stay ahead in a competitive landscape.
Exploring new solutions: machine learning, generative AI, and natural language processing
The rapid evolution of new technologies presents exciting opportunities for the financial industry. Machine learning, generative AI, and natural language processing have the potential to revolutionise data analysis, customer interactions, and decision-making processes.
These advanced solutions enable organisations to interact with data in a more human-like manner, uncover hidden patterns, and make data-driven decisions with greater confidence. The marketplace for these technologies is expanding rapidly, with communities coming together to build open-source solutions and platforms for collaboration. For example, platforms like Hugging Face are fostering an open culture of innovation and knowledge sharing, making new models accessible and facilitating collaboration to expose biases, problem solve and evolve models.
Tokenisation: opportunities and challenges
While the tokenisation of data presents intriguing possibilities, its widespread adoption in the current financial and regulatory framework still faces challenges. Security concerns, inefficiencies, and the high energy footprint associated with certain platforms like Ethereum present hurdles that need to be addressed. As interesting as the technology is, widespread adoption and integration needs to be matched with a considered and compelling need, whilst offering a sustainable and secure solution.
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Paul Ronan, Chief Technology Officer, FE fundinfo
For more on this topic, watch Paul take part in a recorded panel session as part of FundForum 2023
