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SmartData Collective > Big Data > Data Mining > SAS Vertical Strategy
Business IntelligenceData MiningDecision Management

SAS Vertical Strategy

JamesTaylor
JamesTaylor
3 Min Read
SAS Vertical Strategy
Illustration generated with Qwen Image.
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Focus of the presentation from Russ Cobb was Banking, Insurance, Retail and Government.

Banking first. Lots of releases this year primarily around Enterprise Risk Management, Governance Risk Compliance, Customer intelligence, fraud and financial crime solutions. Key customer issues for SAS in banking:

  • Customer Growth
    How do you identify, grow and manage your most profitable customers. Big focus for banks, especially retail banks, particularly in the new risk environment post-meltdown.
  • Enterprise Risk
    What will Basel III mean, how do you tie product-risk to customer-centric growth so you don’t offer credit that fails risk
  • Governance and Compliance
  • Fraud
    Big focus for SAS across the board, especially in financial services. Often a great start point as it generates a return that can then be reapplied to new areas
  • Efficiency

Insurance next. Roadmap includes an extensible insurance data model and Solvency II support in Risk Management for Insurance. Many of the same basic products as for banking, just tailored for insurance. Check out my recent webinar on top issues in insurance for my thoughts on this. Key issues for customers:

  • Premium Revenue
    Particularly in an era of very transparent pricing in P&C.
  • Regulatory uncertainty
    Around the new Dodd Frank Act’s new Federal organization.
  • Product pricing
    The right risk at the right price
  • Claims Expense Reduction
    A big focus – check out the claims white paper to see how you can move from “claims recovery” to up-front claims assessment.

Retail highlights include focus on optimization across price, promotion, markdown and size. Retail forecasting also a focus area. Key customer issues:

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Quality and Governance are Beyond the Data
  • Customer Insight
  • Merchandise Analytics
  • Optimization
  • Forecasting across the enterprise
  • Loss prevention

Final area of focus is Government. Key issues:

  • Fraud
    In tax and other areas
  • Healthcare
    Especially in reducing fraud
  • Intelligence
  • Workforce planning and forecasting
  • Criminal Justice
    In state and local, integrating data from multiple sources particularly like the North Carolina example discussed in the panel I moderated last year.
  • Unified citizen outcomes
    Again, state and local.
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