Machine learning models for the future
As machine learning in financial services matures and data scientists adopt a more strategic role, new research from Refinitiv reveals how firms are doubling down on their investments to gain an edge.
COVID-19 has only made data-driven strategies and investment in artificial intelligence (AI) and machine learning (ML) more critical.
As previous challenges related to talent, technology and funding have diminished, firms have built a strong foundation to implement machine learning at scale. The growth of the data science community – both in size and influence – is a key driving force behind these developments.
However, data quality and accessibility issues continue to disrupt machine learning strategies, and only businesses that can harness quality data and data science expertise to deploy their models at speed will gain a competitive edge.
Access the full report to find out:
- The latest machine learning trends and use cases in financial services
- How COVID-19 has impacted machine learning models and investment
- Key barriers to machine learning adoption
- How the role of financial data scientists is evolving
- The tech advances that prove machine learning is more reality than “hype”
72%of financial services firms consider machine learning a core part of their strategy
40%of firms expect an increase in machine learning investment because of COVID-19
260%growth in the number of data science teams per firm between 2018 and 2020