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Data Management and Business Intelligence

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Building, maintaining, and leveraging data is a key competency of Utile. Our expertise ranges through ETL processes, data warehousing, data mart creation for specific business units, generating custom views, and creating summary reports/dashboards/monitoring tools. In other words, Utile helps move data up the “valued chain” efficiently in order to generate “information” (as an intermediate by-product) and ultimately “intelligence/insights” that drive business goals. Utile’s capabilities in this field can be classified under:
  • Database Design and Support
  • Business Intelligence
Database Design and Support
Optimal database design makes all the difference in using and analyzing data. Utile utilizes proven technologies to design databases that provide businesses with maximum data usability. Our solutions integrate with a variety of leading tools, platforms and analytical features supported by popular database servers. Utile’s capabilities in this field include:
  • Data requirements analysis and cleansing.
  • Logical and physical design using efficient data flows, structures and relationships.
  • Create tables, views, cluster/non-cluster indexing, constraints and SQL code.
  • Develop data marts for custom applications.
  • Schedule back-ups.
  • Perform data assessment and encryption.
Business Intelligence
Utile has extensive experience in summarizing business data into customized reports, metrics dashboards, exception reports, and alerts customized across devices (e.g. mobile and PC). Automated reports (i.e., the foundation of Business Intelligence - BI) can be built by processing real-time data from multiple sources. Utile has supported clients in the delivery of:

  • Product portfolio (key metrics and benchmark tracking) reports.
  • Customer acquisition summary reports.
  • Transactional summary reports for products and marketing channels.
  • Demographic reports.
  • Financial summary reports etc.
In addition to automated BI reporting across key platforms and tools such Cognos, Business Objects, and Tableaux, Utile has assisted clients in:

  • Designing interfaces for external databases
  • Developing VBA/Macro based spreadsheet engines to perform redundant tasks
Data Mining/Statistical Modeling Support
Data mining and advanced statistical modeling have revolutionized the way we leverage data for business decision making. Utile’s statisticians leverage data via SAS and SPSS suites (i.e., SAS Enterprise Guide, Miner, SAS/JMP, PASW Statistics, and SPSS Clementine), in conjunction with other business intelligence tools and data warehousing platforms (e.g.., Cognos, Business Objects, SQL Server etc.) to design, build, score, maintain, update, and deploy statistical models and tools. Using advance data mining techniques such as decision tree based techniques (i.e., CHAID, TreeNet), logistic regression, clustering, factor analysis, and neural network based techniques, Utile has provided quantifiable benefits to clients in the financial services space via:

  • Better customer segmentation to drive optimal marketing/targeting strategies.
  • Predicting customer attrition and developing pro-active retention strategies.
  • Developing marketing response and net-lift models to improve Marketing spend ROI.
  • Advancing risk management models to improve underwriting practices and fraud mitigation
Utile has a consultative approach to model development wherein business goals are kept in the forefront, while putting together the technical requirements. In other words, we match our technical prowess with our “business goal centric” hat, and optimize against time and budget constraints.
Model validation and audit protocols are shared and agreed upon upfront with the client to ensure “top-of-line” quality and to minimize iterations. In addition, Utile takes complete ownership of the scoring, updating, maintenance, and deployment of all models – a hassle-free, “one-stop shop” for all aspects of statistical model management.

Segmentation Models
Utile helps businesses segment their customer/prospect bases into specialized clusters that are distinct in their needs, demographics and behavior. Such models help plan specialized offers for different segments. They support product development in identifying customers with distinct product and service needs and channel managers to understand the optimal combinations to communicate with them. From a business profitability standpoint, these models help define the hierarchy around which customers to “acquire”, “grow actively”, “maintain”, or not focus on.

Attrition Models
Customer retention is a critically important business goal in today’s competitive arena. Utile helps predict which customers are most likely to churn from a product/service or entirely from the firm.
In addition to predicting churn, Utile has conducted advanced factor analysis to help clients understand the drivers and triggers for churn, and to develop counter strategies. This has helped retain the most profitable customers – the “holy grail” in any consumer/subscription based business model.

Response and Net-Lift Models
Utile builds effective predictive models to identify those customers who have the highest chance of responding to a particular marketing activity – be it a cross-selling effort, changing channel behavior (such as shifting customers to a low-cost channel), educational outreach that drives new customer acquisition etc. This helps optimize Marketing spend and get the “Right Offer to the Right Customer/Prospect at the Right Time”. In addition to predicting gross response, Utile has delivered true “Net-lift” focused solutions using decision trees.
Utile designs these models with great precision by testing numerous demographic, environmental and behavioral factors that impact consumer responses to any marketing stimuli and bring significant changes in product buying behavior.

Risk Management Models
Utile helps financial enterprises adopt an analytics-driven risk management approach across the account lifecycle – i.e., from acquisition to managing collections. It has provided analytics support to financial services clients to:

  • Manage and predict allowance for loan losses.
  • Enhance fraud mitigation strategies.

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