ING Vysya’s SAP BO architecture up close: A case study

Indian BFSI player ING Vysya Bank relies on SAP BO architecture to combat report inaccuracy. Here’s a dissection of how ING Vysya’s BI implementation went.

ING Vysya’s need for a business intelligence (BI) implementation first reared its head when the bank started noticing how different end users attended meetings with inaccurate reports. The leading Indian retail and wholesale private bank realized at the point that it had to replace the inaccurate manual reporting system—SAP BO architecture was a possible match.

ING Vysya’s retail division (operation, business, sales and operation controls) was the target user base.  According to Ravi Rathinam, the head for centralized MIS at ING Vysya Bank, business users spent much time developing reports like account balance details, or those from business segments that track initial cheque value. “End users seldom checked accuracy of manually entered data. Different department users ended up with inaccurate reports during meetings,” he says.

ING Vysya’s quest required a solution to help users generate accurate and timely reports. SAP BO based infrastructure proved to be the right solution.  SAP BO enabled the bank to create universes for different domains—users could access it using SAP InfoView. The SAP BO implementation started in April 2010.

The internal team evaluated three BI tools prior to the rollout. SAP BO was selected based on ING Vysya’s general evaluation criteria, which included brand recognition, features and vendor support. Quality of reports and analytics was the key reason for selection of SAP BO. Approximate project cost is Rs 60 lakh, and annual maintenance cost is in the range of Rs 9 lakh per annum.

Implementing SAP BO

With an increased focus on the accuracy of data, ING Vysya decided to establish a common data repository. Though the bank had a repository for its core banking system, the 550 ING Vysya branches stored data at the branch level. Reports were generated based on data residing at different locations, using manually written SQL code.

After setting up the common repository, ING Vysya ran BI on it to generate accurate reports. “Earlier, you had to manually insert the conditional joins in SQL to generate a report with multiple tables. A BI tool eliminates manual effort—users just drag and drop the required columns to create a report,” explains Rathinam.

SAP BO architecture comes under ING Vysya’s centralized MIS department which has two divisions–business MIS and Data Quality. During the implementation, eight internal SAP BI experts started developing the universe for different departments and needs—starting with current account and savings account reports. “We opted for an internal BI professional team, as they understood ING Vysya’s evolving reporting needs,” says Rathinam.

Every department has a username and password for the systems. The top management, IT, marketing, sales, operations and operation control management teams access the universes using InfoView for quality reports and basic analytics.

After SAP BO came into place, the Data Quality team ensured accurate filling of all necessary fields in reports. The team analyzed these reports and classified 150 exceptions (for example, reports with missing fields and incorrect data). These exceptions were dispatched to various departments for appropriate corrections. The data quality team still continues to analyze reports and correct exceptions on a monthly basis.

The tricky parts

ING Vysya’s SAP BO deployment faced several challenges. Understanding BI’s overall scope and the business team’s expectations from the universe proved difficult. Experts had to identify data points frequently used by the business team, and accordingly develop the universe. “Certain users did not give enough inputs on their requirements, which led to constant back and forth meetings with users. In-depth study was necessary. The team took a month to perfectly create different universes,” explains Rathinam.

User apprehension proved to be another challenge. While some users were supportive of the new implementation, many weren't. “They did not mind waiting three days for the MIS reports. They did not want to undertake the work themselves,” says Rathinam. To spread awareness, ING Vysya undertook training sessions to help users understand the BI tool’s simplicity and benefits.

All round gains

ING Vysya’s users have derived multiple gains for the SAP BO rollouts. Some of these benefits are:

  • Quality reports: Manual reports are error prone. With SAP BO, ING Vysya now ensures accurate reports.
  • Timely delivery: Manual reports are time consuming. SAP BO enables ING Vysya’s users to schedule reports and automate delivery. Last year, around 2200 reports were auto scheduled in the bank. With time savings of at least 70 users, ING Vysya has gained cost savings of around Rs 1.75 crore per annum.
  • Improved analytical skills: Technology savvy business users develop reports on their own. They only look to the MIS team for complex analytical reports.
  • Ease of use: After report generation users don’t have to rewrite the query for additional information. They only need to add additional columns to the query for generation of new reports.

In the near future, ING Vysya will venture into a data modeling project to consolidate reports from trade and finance, Internet banking, phone banking, ATMs, and core banking. This project will also cover the bank’s statutory reports, especially those for The Reserve Bank of India’s (RBI) requirements. Following the data modeling project, ING Vysya plans to establish an operational data store (ODS). The bank is also evaluating ETL tools at the moment.

Read more details of ING Vysya’s data modeling and ODS plans.

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