Predictive analysis can process enormous amounts of data and discover patterns and trends in order to avoid financial risks
GDS Modellica provides effective solutions for combatting fraud, making the best possible decisions and helping businesses to build profitable relationships with their customers
The rise in fraud due to a lack of controls has negative consequences, both financially and socially, for organisations, businesses and institutions right across society. This is particularly true of the banking and finance sector, where risk management is a key activity, involving identifying, analysing and assessing potential risks. As the potential risks continue to grow in the modern world, predictive analysis is helping to manage risk in an ever more efficient and effective way.
Predictive analysis has been made possible thanks to new technology that can process enormous amounts of data (Big Data) and identify patterns or trends (Business Intelligence). This way, it is possible to analyse multiple datasets using statistical techniques and detect behaviour patterns which can then be used to create prediction models. The applications are infinite, ranging from predictions about consumer purchases to customer identification, consumer behaviour and combatting banking fraud.
As a result, it has become an essential tool for financial institutions because it can help anticipate and identify risk and avoid non-compliance simply by analysing current and historical databases. This is a huge benefit to banks as it can help them to identify opportunities, address incidents, increase productivity, reduce costs, increase revenue and retain customers.
GDS Modellica supplies software, decision analysis and machine learning tools to help banks manage risk, combat fraud and help businesses to build profitable relationships with their customers. The risk management solutions they offer to the financial sector include predictive analysis, Big Data and decision management tools, all of which make it possible to apply tailor-made solutions according to each business’s individual needs. According to managing director Antonio García Rouco, for effective risk management, “it is vital to collect all the possible data about the likely risks that a business may face so that predictive analysis can extract useful information. The information obtained makes the most of Big Data, which is key for discovering hidden patterns, correlations and other useful information”.
GDS Modellica knows exactly how important it is to improve risk management and get a solid return on investment when implementing analysis and decision technology. Thanks to the firm’s extensive experience and international presence, they have been able to develop new analytical techniques that help avoid risks and make the best possible decisions. According to García Rouco, their solutions “offer personalisation and flexibility in order to develop new, more dynamic strategies and eliminate the common obstacles inherent in legacy systems. These services are ideal for any organisation looking to optimise and automate their credit risk management processes”.
Managing financial risk is obviously a key part of providing credit or loans. Through effective analysis and predictive logic, businesses can work more efficiently, make better decisions, increase revenue, anticipate potential issues, deal more effectively with greater risks and establish a competitive advantage.