Banking

The banking sector is developing at a rapid pace. Year by year the list of services offered by lending institutions to the general public and business clients is expanding. The growing competition is forcing banks to use efficient credit scoring techniques, to reduce decision-making time, and to use analytical reports for strategic planning.

The solutions based on Loginom allow users to automate the processes of making decisions related to bank clients, to find patterns in large amounts of data, and to efficiently manage risks. The most important features are:

• Data consolidation. Loginom contains a fully-fledged data warehouse, which can be used for consolidating information from geographically distributed units and enriching the user’s system with information from multiple data sources, both internal and external. The powerful integration mechanisms make it possible to receive data from virtually any source such as office applications and automated banking systems.
• Analytics. Dozens of data visualization methods are supported, including tables, charts, diagrams, multivariate maps, hierarchies, OLAP cubes, etc. An ordinary user can generate any analytical report with just a few mouse-clicks, without the help of IT experts.
• Credit scoring. Loginom implements the most advanced and internationally proven self-training algorithms. These algorithms are used for building scoring maps, application and behavior scoring models based on decision trees and neural networks, automatically finding significant factors, and determining the relevant score. Such an approach allows the implementation of the selected lending policy and brings down the level of overdue debt.
• Underwriting. Prior to the scoring, borrowers usually undergo the underwriting procedure in order to check whether they meet the bank’s minimum requirements. Using the analytical platform it is possible to create a borrower application passage scenario which will register any deviation from the credit rules and calculate the credit limit. Thanks to the interactive visual environment of Loginom Studio, the underwriting rules can be easily added and modified without the help of programmers. The integration of such a subsystem with the credit application input system reduces the application pendency time by a considerable margin.
• Account balance forecasting. In order to control bank liquidity it is necessary to forecast the clients’ account balances. Having taken the daily balance information from the bank system of the data warehouse, Loginom converts it to a time series, thus allowing the analyst to forecast the future balance. For this purpose Loginom has various forecasting techniques: statistical, econometric and neural network.

Loginom is capable of addressing other issues typical of banks, credit brokers and financial institutions. These include loyalty management programs, cross-sales of credit products, investment portfolio management, fraud scheme detection, investment project profitability appraisal, legal entity scoring and many others.