Undoubtedly, data has become one of an organization’s most valuable assets. A disciplined, three-step approach can help organizations understand and obtain the most value from their data and begin monetizing it.
Paul Gibson shares his key takeaways from the 2017 FIMA Europe conference in London, including why CDOs must align data and analytics and how GDPR gives you an opportunity to improve you data infrastructure.
As the investment management industry faces growing budgetary constraints and new complex regulatory mandates, relying on internal and external data is now pivotal to maintain or gain a competitive advantage in the market.
At a time when businesses across every industry are debating how to transform their data into actionable assets, analyzing design patterns through visualizations offers a clearer picture of your data and helps to handle the increasing complexity of your business today.
As regulatory bodies have unleashed a flurry of new rules to enhance greater trade and transaction reporting transparency and mitigate systemic risk, the industry has sought to improve reporting efficiency with data standards. But with each regulation bringing new complexities (and more requirements right around the corner), the goal of industry-wide harmonization may just be impractical.
As the global financial industry faces lower margins, increasing competition and more regulation, one remedy that can help institutions effectively navigate these challenges is a successful data management program. Yet for many, that in and of itself is a daunting task.
Technological advancements, such as electronic trading in the financial services industry, have delivered cost benefits to many industries while also increasing competition. However, within the shipping industry such a large-scale transformation has yet to unfold, although it’s evolving.
In every industry and across all departments, organizations are realizing the potential of analytics programs to raise productivity, improve decision-making and gain a competitive advantage. Yet, managing and executing an analytics program isn’t easy.
Organizations are increasingly relying on analytics and advanced data visualization techniques to deliver incremental business value. However, when data quality hampers their efforts, the credibility of their entire analytics strategy becomes questionable.