7 Financial Services Initiatives Where Self Service Data Prep is Vital Backgorund

7 Financial Services Initiatives Where Self-Service Data Prep is Vital

July 17, 2017
· 2 min read

The ability to effectively and efficiently manage the vast and disparate range of corporate, customer and business information is rapidly emerging as a critical objective for financial services companies —regardless of their respective market and geographic focuses.

While data management has always been a critical component of financial services companies’ initiatives to better understand their customers, manage risks, and comply with regulations, today new market, customer, regulatory, and shareholder demands require a different breed of technologies.

For example, the sheer growth of transaction volumes in recent years, tighter regulations around federal reserve stress testing and politically exposed persons, and omni-channel customer experience models are pressuring these financial services companies to look for new data management capabilities that can speed both their strategic, revenue-focused and tactical, control-focused initiatives.

In the past, many of these initiatives were done manually utilizing Excel or legacy data management solutions. Today, we are seeing the same Fortune 100 financial services companies use artificial intelligence (AI) to detect fraud, leverage machine learning techniques to improve the quality and accuracy of their at-risk accounts and transactions, or self-service data prep (SSDP) tools to empower business subject matter experts to deal with regulations.

Information, as Chief Data Officers (CDOs) and Chief Risk Officers (CROs) know it, can herald the growth of a financial institution’s brand and performance if properly managed, or choke the life out of it and damage the company’s reputation if its value as a strategic corporate asset is underappreciated or ignored.

Today’s CROs and CDOs know that turning raw data – from transactions, trades and weblogs – into information that can be acted upon does not require employing a lengthy process or hiring an extensive set of resources. Instead, these processes can become more automated, predictive, and prescriptive.

These companies and their CDOs and CROs are information forward-thinkers. They are information inspired. They know that only when data is complete, semantically and syntactically clean, contextual to the business need and consumable in the way business consumers and subject matter experts desire it, does it become information.

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About the author

Value-Driven AI

DataRobot is the leader in Value-Driven AI – a unique and collaborative approach to AI that combines our open AI platform, deep AI expertise and broad use-case implementation to improve how customers run, grow and optimize their business. The DataRobot AI Platform is the only complete AI lifecycle platform that interoperates with your existing investments in data, applications and business processes, and can be deployed on-prem or in any cloud environment. DataRobot and our partners have a decade of world-class AI expertise collaborating with AI teams (data scientists, business and IT), removing common blockers and developing best practices to successfully navigate projects that result in faster time to value, increased revenue and reduced costs. DataRobot customers include 40% of the Fortune 50, 8 of top 10 US banks, 7 of the top 10 pharmaceutical companies, 7 of the top 10 telcos, 5 of top 10 global manufacturers.

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