“After I started using our new Business Intelligence system, I got a complete insight into the most valuable information, based on corporate data sources. Every morning, the first thing that I do is go on my personal site and analyze a business scorecard that contains most recent values of key performance indicators of our business. The user interface is very sophisticated, easy to use, intuitive, and attractive. The system is reliable. Information produced as a result of complex analysis of large volumes of data can now be obtained in a matter of seconds. That is all I need.”

Banca Intesa Belgrade is second largest bank on the Serbian market and a reliable partner for more than 900.000 clients. It is a member of the newly founded Intesa Sanpaolo group, the largest banking group in Italy and one of the strongest in Europe.  Intesa Sanpaolo group, according to the market value, is ranked as fifth in Europe. This group has more than 18 million clients and a network of around 7.000 branches in 34 countries throughout the world, while it counts more than 6 million customers and 1.400 branches in the region of Central and Eastern Europe - in Serbia, Croatia, Slovakia, Albania, Romania, Hungary, Bosnia and Herzegovina, Slovenia, Czech Republic, Ukraine and Russia.

In the last few years Serbian FSI was changing dramatically. Market was opened for foreign investments and many local banks have been acquired by foreign, mostly European banks. Also, local regulations were changing and improving rapidly so banks needed to adopt quickly. Competition tightened up and customers became more demanding. These are the challenges that each bank should have been aware of and Banca Intesa Belgrade was one of the first.

After comprehensive analysis provided by bank experts, they concluded that the answer on challenges should be found on better usability of information potential that was present in the corporate data sources.

Banca Intesa was looking for a tool that would help it analyze the huge volumes of data captured by its OLTP systems. The objective was to analyze new business opportunities, provide better customer service, and boost profitability.

Banca Intesa Belgrade previously used Online Transaction Processing (OLTP) system, which facilitated and managed transaction-oriented applications. The system was reliable but provided little scope for in-depth customer analysis. It answered the financial queries and generated reports at a broad portfolio level, which included total earnings, debt situation, interest income, cost, fee income, customer risk category and profits.

The bank realized that it needed to go a step further and deploy a solution which can be used to analyze the huge volumes of data captured by its OLTP systems. The idea was to search for crucial nuggets of information from the vast amounts of available transactional data and to get to submit the right information to the right executive, in the right time.

The bank's IT team studied business requirements in detail and deduced that the bank needed a data warehousing and analytical solution that would help them analyze customer data and enable fact-based decision making in areas ranging from acquisition and risk management to cross-selling and portfolio management.

After evaluating a number of vendor offerings, Banca Intesa Belgrade decided to use a suite of products from Pexim Solutions - TEZAURI - Pexim Banking Business Intelligence Solution based on IBM IFW Data warehouse model and fully implemented on MICROSOFT platform (with SQL 2005 as a backbone).

Tezauri Solution is based on n-tier architecture. On the server side, enterprise data warehouse runs on SQL Server 2005. ETL applications that integrate all banks information data from internal and external sources are developed on Integration services 2005 (SSIS). Multidimensional databases (based on data marts) with definition of cubes (measures and dimensions) and data mining models runs on Analysis Services 2005. Share Point Portal Server 2003 is used as portal integration and collaboration platform for end-users.

On the client side, reporting system is based on Reporting services 2005, Microsoft Office 2003/2007 Applications (mostly MS Excel). Business Scorecard Manager 2005 is used for corporate and specific scorecards that give additional business value on Tezauri to higher level of management. End-user applications are web oriented, developed in Visual Studio 2005 and they run on .NET framework. Web services are developed as data integration service between Tezauri solution and end-user 3rd party applications (if any).

The solution has helped the bank to effectively manage and optimize all information potentials from internal and external sources for making their business decisions and solving business problems.

Tezauri solution forms a central part of the bank's BI strategy. It is easier for bank to run targeted campaigns and elicit substantially higher returns, since bank performs profit modeling for each account. This also enables micro-segmentation. Using analytics, test-and-learn culture, bank executives know the likelihood of customers to take a new product. They now know which card member is more likely to take an auto loan. This has resulted in more focused marketing campaigns and reduced costs with improved customer satisfaction.

The organization's marketing team is now empowered with information to increase cross holding and can target its most valuable customers (not accounts within a product line) and also helps in creation of the next best product strategy for a customer.

Now, Banca Intesa is able to successfully calculate risks. Information on customer profiles and segments forms the backbone of product strategy for the bank. It allows tailoring Banca Intesa’s products across a diversified consumer base, enabling spreading of the risk across a much wider spectrum.

In summary, with successful implementation of Tezauri solution and thanks to Microsoft BI platform Banca Intesa is able to:

• integrate information from multiple sources, eliminate data errors and redundancies, tailor data for efficient access and analysis, and reduce the complexity of data management;
• anticipate customer expectations and predict customer behavior like, propensity to purchase, lifetime profitability and credit risk;
• allow cross-sell and up-sell. It can help identify the best candidates for purchasing particular combinations of products and services, and focus the marketing efforts on a more receptive audience;
• combine business rules and analytic models to accurately segment and profile customers, and conduct a personalized strategy for each group;
• deliver customer intelligence into front office systems and enable smarter customer interactions through various channels;
• combine behavioral insights derived from analytics with attitudinal data obtained from online and offline customer surveys.