DATA ANALYTICS

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DATA ANALYTICS

• OFFSHORE SUPPORT TO
• FORD CREDIT
• BY
• FUTURE FOCUS INFOTECH PVT LTD

2
Analytics supports Risk Managements mission to
partner with the business locations in order to
identify, measure, and communicate risks and
opportunities associated with the credit life
cycle to add value to business decisions using
the best information, tools, and analysis to
achieve continuous and predictable profitability
and growth.
Product Development
Pricing
Loss Recovery
Credit Underwriting
Collections
Approval Process
Servicing
3
Business Partners
SUPPORT PROCESS
Manager Global Risk Management
Remote Execution
Query
Analysis
Scripting SAS 8.2
Internal Customers
Data warehouse
SAS Output
Formatted Report
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• KEY STEPS IN SUPPORT PROCESS
• Receipt of Request by email.
• Analysis of the requirements and finalization of
  the Extraction strategy.
• 3. Development of scripts using SAS 8.2.
• 4. Remote Execution on Oracle DW databases.
• 5. Presentation of SAS outputs - Excel format
  thru email / Web

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• Salient Points
• Technology
• Backend Oracle DW in IBM Mainframe
• Client Analytics tool - SAS 8.2 on Windows
• Presentation tools MS-Excel / Web
• Coverage
• Retail/ Lease Credits, Purchase/Non Purchase
  Segments
• Customer Rating
• Analysis by parameters like POP, Projected POP,
  FICO scores
• Development
• Task-specific processes
• Faster with REUSABLE Structures

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• Project Methodology
• Familiarization (1Month) Study of source
  Database and Fields.
• Study of mapping rules.
• Study of Business rules to be
  applied.
• Production (Ongoing) SAS scripting to
  generate outputs in the
• 
  desired formats.
• Presentation options -
• 
  MS-EXCEL
• ODS for voluminous outputs
  Web Hosting

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• OVERVIEW OF JOBS UNDERTAKEN
• Special Queries and Statistics.
• Regular Reports Periodic Analysis.
• Enhancements Value additions.

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Special Reports Statistics

• Average Credit Loss reports Variation of Loss
  with a number of Variables.
• Extended term Purchase Analysis Contracts,
  Violations Performance.
• Evolution of variability Analysis - Summary
  Details.
• Tier Performance Reports.
• - Summary (Pivot)
• - Defaults
• Projected Performance Reports.

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Special Reports (Contd.)

• Basis Point Change Impact Studies
• ORDB data request criteria Study of Percentage
  advanced
• Commercial Accounts Performance
• Vintage Analysis
• Volumes
• Defaults
• Pivot Charts
• Exceptions vs. defaults
• Average Customer Payment Statistics

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• Regular Reports Periodic Analysis
• Purchase Quality Reports.
• - Summaries.
• - USA/CAN.
• - Region / Branch wise.
• - Exception Details.
• - Region wise.
• - Branch Policy Limits.
• - Dealer Authority Levels.
• - Executive Summary.
• - Region wise Performance.
• - Branch wise Performance.
• Projected Performance Reports. (1999 2002).
• - Region wise. (RTL-N, RTL-U, RTL-C, RCL)
• - Dealer state wise. (RTL-N, RTL-U, RTL-C,
  RCL)
• - Period wise. (Can) (RTL-N, RTL-U,
  RTL-C,RCL).

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Enhancements Value Additions

• Data aggregation through pivoting and automatic
  generation of charts.
• Development of standardized Macros for most of
  the regular jobs .
• Web enabling of Reports on the web server.
• Loan origination statistics for Dynamic
  generation of web outputs.
• - Extraction of Exception database and
  Transformation.
• - Web Interface Design.
• - Output Generation.
• Monitoring of query profiles and standardizing
  of scripts.
• Statistical Analysis using SAS desktop by
  importing the excel outputs.

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ADVANTAGES

• Time Advantage - Leverage the time zone
  difference to obtain overnight business
  solutions.
• Expensive Analyst Resources freed from routine
  responsibilities, can focus on strategic business
  solutions.
• Faster turn around of request from business
  partners will increase customer satisfaction.
• Increased Analytical support for International
  locations that are typically resource
  constrained.
• Low cost analytical unit.
• Wider proactive analytical coverage

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FUTURE COVERAGE

• Credit Analysis requirements of other
  international clients
• Data analysis / Data mining on different data
  sources - Warranty, Customer and Supplier
  databases etc.
•