StatDec's expertise is in providing Consultation and Decision Support Analytics to Financial Institutions who are seeking an efficient and effective approach in managing their Retail Portfolios and increasing their Profitability.
StatDec brings to the market an array of skills of the highest calibre combined with extensive practical experience.
Application and Behaviour Scorecards are our core business with hundreds of statistical models being developed and supported over a 30 years period, implemented in over 100 Financial Institutions in more than 35 Countries around the world.
Over the years we have gained a wide experience in data analytics and processed a vast variety of databases. Our expertise covers all the areas of:
- Data management, data cleansing, data mining
- Application of methodologies for models’ development and validation, forecasting, essential analytics, reporting.
Application and Behaviour Scorecards have now attained a vital role for the Risk Assessment and Management of Financial Institutions, used for Capital Requirements and IFRS9 Provisions. StatDec expertise in statistical modelling and portfolios analysis positions the company as the ideal partner for effective risk management and covering Supervisory Requirements Basel Framework on Internal Rating Models (IRB) and IFRS9 Standard on Provisions.
Besides Scorecards and Supervision, Statistical Decisions’ services cover every aspect of a Customer-Lender relationship range from Credit Initiation and Marketing Response Models to Credit Risk Modelling and Debt Collection consultation.
Our analysis toolkit includes well-proven statistical, econometric and stochastic methods. Going further, we closely follow and incorporate in our analyses the state-of-the-art methods of Machine Learning and Artificial Intelligence. ML AI techniques such as Random Forests, Neural Networks and Gradient Boosting algorithms are being used in giving answers to real problems:
- To challenge existing models developed with regression methods
- To unveil underlying trends and enhance traditional regression models
- To model with large datasets and Big Data, e.g. transactional models