Vantage West addressing the growing data concerns

Vantage West is the second largest credit union in the southern part of Arizona with more than $1.7 billion in assets. The credit union has a wide range of financial offerings from business loans to accounts to local consumers and businesses in Arizona. The credit union is 60 years old and started off in a one-room barrack at Davis-Monthan Air Force with the mission to help Tucson’s airmen and their families. The company had gone through many changes, acquisitions, and even changes the name from DMAFB to Vantage West in 2006. Currently, the credit union has 16 branches and close to 30 ATM outlets spread across different regions in Southern Arizona. The most profitable department for Vantage West Credit Union has been the Consumer Lending department and it contributes to 75% of the overall revenue. The department handles all direct and indirect auto loans, credit cards, accounts, mortgage loans, Home equity loans, and business credit cards. From this list the of products the one that has been the backbone of the credit union is the Auto Loans.

In attempts to further strengthen the Auto Loans portfolio, Vantage West Credit Union had implemented several strategies and promotions to attract the consumers. Most of the decisions resulted from analysis of baby data and gut. However, the credit union wants to further enhance their existing line of financial services and make them more customer-centric to attract more members to join the credit union. The CEO Bob Ramirez believes that to achieve this goal, improved decisions backed by data analysis that relate to auto loans and consumers to a number of loans issued over time and location are required. Many consultants who have assisted the credit union during its core system implementation phase have suggested the need for a data warehouse for the Auto loans service to further improve the loan portfolio.

The key metrics that the credit union wants to evaluate are related to Customers and Auto loans over time and location.

CUSTOMERS

·       Which age group of customers has been most profitable?

·       Which salary range customers are likely to take auto loans from VWCU?

·       Where do most of the auto loan customers have their accounts opened?

·       What are the revenue generation trends for the different type of customers over a period?

·       Who is the sales representative that handled most customers in a branch?

AUTO LOANS

·       Which auto loans are most profitable?

·       What is the most profitable time of the year for auto loans?

·       What is the range of auto loans issued at each branch?

·       What are the auto loan trends issued in different branches and different time of the year?

·       Who is the sales representative who sold most auto loans in a branch?

It is very important for the CEO to be able to able to track these metrics as it will help him identify the profitable branches, customers, and auto loan products. This will help implement strategies that further improve existing loan products and also help capture untapped customer auto loan needs. 

After consulting with data experts from MIS department at Eller College of Management, CEO Bob Ramirez decided to build a Datawarehouse starting with dimensional modeling. The MIS department later consulted with the business users at Vantage west and identified 4-dimension tables namely: Customers, Branches, Auto Loan Products, and Date. Each of these dimensions is then connected to a Fact table that contains the quantitative values that help answer the key metrics to be evaluated. The dimensional model gave Vantage West a key advantage of storing the data in a fashion that it is easier to retrieve the information, better understanding, and extensibility. The MIS team followed the 4-step process and came up with the below rough draft of the dimensional model design. 

Vantage West Credit Union is very pleased with the work done thus far and is excited about looking and analyzing the customer data. The credit union is also exploring various reporting tools that could leverage the extensive data warehouse it had built. Great times ahead for the credit union.