A discussion of trends in innovation management within financial institutions, and the key processes, technology and cultural shifts driving innovation. Diederick Van Thiel. Payson Johnton. Thomas Pintelon. Farah Miller. Blog article. News in your inbox For Finextra's free daily newsletter, breaking news and flashes and weekly job board. Sign Up. Innovation in Financial Services. External what does this mean?
This content is provided by an external author without editing by Finextra. It expresses the views and opinions of the author. Data Analytics in Wealth Management 18 July Following are some areas of focus at many firms as the discussion continues: Planning for how analytics is to be integrated into current workflows, understanding the projected end results, involving key influencers e.
The aim of data and analytics starts with the creation of an integrated target-state vision across data management and governance, analytical tools, technology deployment, and business adoption. Process automation. Wealth Management firms are now using NLP and similar methods to analyze text and voice data to enhance the efficiency of processes and core functions. RPA for example, can contribute to more effective compliance practices.
Functions such as monitoring and testing are suitable automation candidates. Risk management. As organizations expand their digital footprint, their risk profiles change and create more points of vulnerability to threats of cyberattacks. Robotic process automation RPA is also able to handle significantly more transactions than humans and can be leveraged for compliance and internal audit checks and balances. Improving productivity. Asset managers are using analytics, specifically predictive algorithms to identify actionable client insights and, help enhance sales and marketing efforts.
These algorithms have proven to have greater accuracy in sales results for those using these analytical tools. Augmenting research process. Natural language processing NLP can help asset managers and research analysts process vast amounts of data more quickly than ever, through the consumption, analysis and access to changes in public filings and social sentiments.
The use of machines for this purpose complements the human process as the technology can help users focus on relevant information in much the same way that Netflix or Amazon deliver personalized recommendations to users allowing asset managers to spend more of their time on high-value decisions for their client, potentially in real-time. Why does the above matter? Report abuse. Join the discussion. A data-centric approach to IBOR provides you with a single source of truth to support better decision making.
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