IFRS 9 – Impairment
In order to meet the criteria and requirements of the International Standards, namely the IFRS 9 - Financial Instruments, this solution enables Financial Institutions to calculate the Expected Loss of the Financial Institution's Assets. The practical implementation of the Conceptual Model for calculating Impairment can be supported in this solution, with the automation of the calculation of Risk Factors, which actively participate in the collective analysis, and sophisticated methodologies for the individual analysis of customers with greater exposure.
Central Balance Sheet and Rating Database
The establishment of a company's risk profile, within the framework of a loan proposal, is essential for an accurate evaluation of the financial situation. For companies, the qualitative and financial profiling may represent their capacity to fulfil their responsibilities towards the Institution. In this respect, the Central Balance Sheet solution allows managing and monitoring the company's qualitative and financial information, as well as effectively identifying the relationship between the company and other companies or shareholders. This information is vital for the implementation of an internal rating model, underpinned by the company's financial, business, sector and economic risk profile. As such, the Rating solution also has the advantage of automating the application of an internal model, with consistent information quality control for all customers and operations.
Financial Institutions face more and more demands in terms of reporting to the Regulator, within the framework of risk management. As such, this solution aims to automate the calculations for producing these reports, mitigating the operational risk involved in producing them and guaranteeing that the basic data for their preparation is the same between systems, provided that they are integrated with this solution.
Management of Guarantees
Financial Institutions are exposed to different types of risk, namely Credit Risk, which may include non-performance risk, concentration risk and collateral risk. The fall in the quality of the collateral may translate into a decrease in the expected return, and a consequent increase in the Expected Loss, which will have a direct impact on the Financial Institution's profits and losses. In short, the management of formalisation, documentation, valuations, appraisers, executions and sales will allow the risk associated with the loan portfolio to be determined more accurately, both from the point of view of non-performance and recoverability.
The Scoring solution makes it possible for the Financial Institution to predict the behaviour of a customer who wants to take out a loan, based on the behavioural history of similar customers and loans, while simultaneously matching the type of product requested, its characteristics and the attributes of the customer. This solution, based on a sophisticated machine learning model, focuses essentially on mitigating credit risk, ensuring the stability and reduction of the NPL of the institution's loan portfolio.
To support a more effective and efficient risk management, as well as to safeguard the solvency and liquidity of the Financial Institutions, this solution acts as a support tool for the implementation of the Institutions' Stress Test Model, focused on their main risks and with the possibility of carrying out sensitivity analyses, scenario analyses and reverse stress tests. This solution also enables reports to be generated for each analysis carried out, allowing them to be properly and fully documented.
All solutions interact with each other ensuring a holistic approach to risk management and compliance in the Financial Institution. This integration is only possible with the existing centralisation of the data layer.
WEB interface, with business functionalities made available in a user friendly manner.
This suite ensures functional coverage to meet current regulations, as well as efficient financial, non-financial and compliance risk management.
All solutions are based on a layer of parametrisation and configuration designed to meet the need of adapting solutions to internal and regulatory models.
Solutions designed to identify, measure and mitigate the risks to which the Financial Institution is exposed, namely Reputational Risk, Compliance Risk, Operational Risk and Credit Risk.