X'PRESSIONS
Credit Information Management Using Business Intelligence
Business Intelligence (BI) is a business management term which combines the tools and technology to extract relevant information from large volume of data in various parts of an organization. It includes applications and technologies which are used to gather, provide access to, and analyze data and information about their company operations. Business intelligence systems can help companies to have a more comprehensive knowledge of the factors affecting their business, such as metrics on sales, production, internal operations and they can help companies to make better decisions.
Credit professionals have to respond to new regulatory and internal pressures constantly. All the shareholders and the regulators want more transparency and access to the relevant information regarding credit and risk portfolio. For example Basel II is a driver, exposing it to risk is our target and credit analysts have to deal with these and answer with the help of effective tools.
Almost 30 years back from today, the access to credit data was not an easy task as it is today. But the most important task today is to convert that data into useful and actionable information, which consumes so much of time of credit analysts. It includes collecting data from various sources and then creating links for providing data as and when demanded. Business Intelligence (BI) has been offering help to the data analysts in various industries for last several years.
Reduced costs and wider availability of BI tools and applications have made BI solutions achievable for most institutions and even individual departments of banks. A properly engineered BI solution can deliver different views of the same information when and where they are needed. Various persons of an organization like CEOs, Loan Review, board members, and regulators all need the same information, but they have to be able to customize it for their immediate area of focus. BI automatically generates the periodic credit reports and charts as well as report on the bank's strategic key performance indicators.
There are some specific issues that a bank has to consider while evaluating a credit data BI project, which can make the investment resources really pay off. There are plenty of instances of "black hole" data warehousing projects, but there are reasons to believe that bank's BI credit solution is going to succeed.
In the 1970s, banks were more or less completely dependent on mainframe systems to collect and manage data. Management and performance information was prepared in a series of standard hard-copy reports. In the 1980s, office automation products like VisiCalc and Lotus provided the bank professional with the freedom to take some data from the mainframe and manipulate it to create more useful information.
In the 1990s, desktop computers became very powerful, with more storage space. Personal database applications like Access and advanced spreadsheet applications like Excel workbooks provided the users with more sophisticated reporting and analytical capabilities.
The disadvantage of the personalization of data management was that important corporate information was now available to individuals on their workstations, with little control or security. Certain departments in the bank manually created and controlled the numbers and built up their own technology and controls.
The key issue today is the need to pull together credit and risk data from different sources and systems, and the requirement of linking this data into one centralized, consistent authority for credit analysis and reporting.
The decade of Business Intelligence
In mid 1990’s, the Gartner Group introduced the BI concept to banking and other industries, where these institutions have to use various data management systems, tools and formulas to automate the data collection and analysis process and then provide a multidimensional view of business information to business community.
In brief, a BI solution is an automated process of gathering related data from different sources and then categorizing and aggregating that data into meaningful information and delivering it to the users in a quick and easy t use format.
Delivery of information will be in the form of formulaic analysis, trending, charts, and graphs. The goal is a format that will lead to decisions and actions. In many cases, BI solutions are actually called Executive Information Management (EIM) and Decision Support Systems (DSS).
Today most financial institutions use some form of BI systems somewhere in the bank. Marketing, Finance, and Sales Management often have specialized data-mining and management tools to deliver aggregated information for performance management needs. These solutions are point solutions that deliver information for specific departments in specific formats to meet their business needs.