If Warren Zevon were alive today and writing about the state of many companies, he might say “send workflow, data and analytics, the s*** has hit the fan.”
While the theme of “Lawyers, Guns and Money” is not a direct parallel with the sea changes happening due to new technologies and Big Data analytics, the resulting impact of hitting the fan may be for companies that are slow to adopt to new innovations.
Leading companies are looking carefully at workflow processes, creating automated validation checks and repair processes to ensure accuracy. They are looking at how data is stored and accessed across the entire organization, and they are looking at how they can improve the value of that data through advanced analytics.
In the financial services industry, there are many examples that are being broadly adopted, such as reference data management automation, and also Big Data analytics to support marketing segmentation. New innovations include automating collateral management, improving data governance, streamlining fixed income attribution, and new models for asset allocation, among others. Firms are looking at how they can mix data stored across silos with unstructured data to provide true Business Intelligence with predictive analytics in order to provide new insights on their clients, investment strategies and overall business efficiency.
For companies not thinking about these new innovations, they may claim to be an “innocent bystander…down on [their] luck.” Fortunately, it’s not too late to start.
While the theme of “Lawyers, Guns and Money” is not a direct parallel with the sea changes happening due to new technologies and Big Data analytics, the resulting impact of hitting the fan may be for companies that are slow to adopt to new innovations.
Leading companies are looking carefully at workflow processes, creating automated validation checks and repair processes to ensure accuracy. They are looking at how data is stored and accessed across the entire organization, and they are looking at how they can improve the value of that data through advanced analytics.
In the financial services industry, there are many examples that are being broadly adopted, such as reference data management automation, and also Big Data analytics to support marketing segmentation. New innovations include automating collateral management, improving data governance, streamlining fixed income attribution, and new models for asset allocation, among others. Firms are looking at how they can mix data stored across silos with unstructured data to provide true Business Intelligence with predictive analytics in order to provide new insights on their clients, investment strategies and overall business efficiency.
For companies not thinking about these new innovations, they may claim to be an “innocent bystander…down on [their] luck.” Fortunately, it’s not too late to start.
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