Advanced Analytics Is Crucial For Finance
Opportunity Watch: Advanced Analytics In FinanceBig data is transforming industries. From education to tech, retail, and healthcare, sophisticated analytics are helping organizations make intelligent decisions to maximize key goals.
“From Facebook to Netflix, companies are tracking and analyzing our searches, our purchases, and just about every other online activity that will give them more insight into what we are and who we want,” wrote Jim Fruchterman for Harvard Business Review. “The more we use technology in our education and health systems, the more data we collect about how people learn and what keeps us healthy or what makes us sick.”
For financial firms that face challenges of increased governance, risk, strict compliance guidelines, and worldwide economic instability, the need for data-driven decisions is even more crucial.
“To navigate the complexity and manage capital more effectively, it’s essential to develop advanced analytic forecasting capabilities and financial management techniques,” according to a Deloitte case study.
The following three areas are leading the charge:
1. Decision Support Partnerships
Data drives more than just reporting — financial firms need quantitative strategies to drive overall business. Big data transforms finance teams from researchers and analysts to key influencers.
“Companies with strong FPA[Financial Planning & Analytics]-business partnerships have more cost discipline and deliver a 5.9% average annual total shareholder return premium,” wrote Michael Griffin, Jian Chen, and Anna Kipchuck for the Wall Street Journal.
Opportunities include synthesizing diverse data systems, extrapolating trends, improving efficiency, and recommending changes to the overall business.
“Unsurprisingly, finance teams with these capabilities are more likely to be viewed as strong business partners, which means they’re more likely to be involved early in key conversations and decisions rather than during the approval or funding stage,” wrote Griffin, Chen, and Kipchuck.
2. Compliance Cost Reduction
Last year, the financial services industry witnessed hundreds of new regulations. These changes will have a heavy influence on the sector’s data strategy. Beyond long-standing Sarbanes-Oxley regulations, new regulations from Basel III, the Dodd-Frank Act and other legislation create new complexities — with data as a mission-critical remedy.
Boston-based State Street Corp., for instance, is experimenting with semantic databases — information storage solutions with flexible data structures that prioritize meaning in relationships.
“State Street began experimenting with semantic databases last year and has moved from proof-of-concept demonstrations to pilot programs using the semantic data model,” wrote Kathy Burger for Bank Tech.
According to State Street’s chief scientist David Saul, semantic data is a powerful compliance tool for the Legal Entity Identification (LEI) standard mandated by the Dodd-Frank Act.
“State Street has been working on taking a semantic approach to LEI data, and Saul says its ability to link different kinds of data and creative equivalency could prove invaluable to banks in their efforts to comply with this new standard” wrote Burger.
With automation of LEI data — an otherwise manual process — comes cost savings opportunities through improved efficiency.
3. Rigorous Predictive Models
Volumes of data are growing exponentially for the finance sector. These data points are invaluable for profit and efficiency maximization.
“Banks and investment firms assess massive amounts of data to stay ahead of the competition,” wrote J.J. McCorvey for Inc. “In 2011, for example, trading volume grew to 4.55 billion contracts, up 17% from 2010, while the American Bankers’ Accociation reports that there are 10,000 credit card transactions every second around the world.”
Predictive models are invaluable for sifting through massive consumer insight volumes. Best practices rely on the capabilities and priorities of individual organizations.
“Harnessing the ultimate power of an information-driven culture will depend on how organizations approach the opportunities offered by data and analytics,” wrote Jeanne E. Johnson for a KPMG report.
Cut costs, influence business decisions, and grow profits — all three provide opportunities for advanced analytics as a guiding force. As reporting standards grow more complex and competition for consumers becomes more rigorous, the need for data will become exponentially higher.
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