The latest data science trends in banking and fintech
The latest trends in data science suggest that a new viewpoint is taking shape. Data is no longer a science reserved for a select group of specialists but has instead become an invaluable opportunity for every industry, especially banking and fintech.
AI automation and cloud computing for more efficient data analytics
Increased availability of Environmental, Social and Governance (ESG) data
Use of alternative data aiding business decisions
Measuring ROI for machine learning and data science projects
Customer personalisation driven by data
Stricter time stamping regulations
In this article, we explore a key emerging trend in time stamping:
Traceable timing solutions
With time stamping regulations in financial services getting stricter, and data scientists, developers and technologists looking to maintain integrity of assets, server clock synchronisation look to improve the accuracy of time sources.
Richard Hoptroff, CTO and Founder of Hoptroff, said: “Network derived and precise traceable timing solutions are an innovative aide which can be used to bolster data infrastructure of banks, financial services and fintech. They are a growing alternative to traditional, satellite dependant means of achieving time. Network derived time can be used to optimise trade lifecycle management, improve transaction reporting and inform strategic decisions. This enables the verification of transactions to become more efficient and reliable and also opens up the possibility to identify significant cost savings.
Ready to learn more?
Hoptroff Traceable Time as a Service (TTaaS®) is a range of network and software-based timing solutions that are simple, resilient, and cost-effective.
Whether you need the security of verifiable time for compliance, protection from risk and fraud, or want transparency and efficiency, our obsession with accuracy will transform your business.
