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Consultancy Services

Fermac Risk provides assistance to businesses in optimizing their processes and operations by using advanced technologies such as Generative AI and quantum computing. These cutting-edge technologies can help organizations improve their models, fine-tune parameters, enhance algorithms, and employ advanced techniques to enhance the accuracy, efficiency, and speed of their models. Our consultancy services offer valuable insights on how to effectively use these technologies to achieve business objectives and ensure maximum return on investment.

Select one of our three available tariffs:

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  • The Lite rate tariff includes scripts and your own databases.

  • If you opt for the Standard rate tariff, you will receive scripts along with consulting services to deliver a final result, using your own data

  • The Pro rate tariff allows you to add more variables from your data than the Standard rate.

  • Finally, the Premium rate tariff provides you with the ability to add more variables than the Pro rate tariff, in addition to a generative artificial intelligence model.

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 By incorporating Generative AI techniques, consultancy can help businesses develop more accurate and reliable credit scoring models. Generative AI algorithms can analyze large datasets, learn patterns, and generate new synthetic data, improving the credit risk assessment process. Credit scoring consultancy can create personalized credit scoring models. These models take into account an individual's unique financial situation, behavioral patterns, and transactional data, resulting in more customized and targeted credit scoring decisions.


Consultancy specializing in Generative AI and quantum computing can help financial institutions accurately forecast demand for non-maturity deposits. By analyzing historical data and market trends, these technologies can generate predictive models that improve forecasting accuracy, enabling banks to manage their deposit accounts better.


Consultancy specializing in AI,  Generative AI, and quantum computing can enhance the accuracy of Lifetime PD:

  • Employ machine learning algorithms, such as supervised learning (e.g., logistic regression) or ensemble methods (e.g., random forests), to build predictive models that estimate Lifetime PD.

  • Incorporate advanced techniques like deep learning, recurrent neural networks (RNNs), or long short-term memory (LSTM) networks to capture temporal dependencies in credit risk data.

  • Utilize natural language processing (NLP) techniques to extract valuable insights from textual data, such as borrower information or macroeconomic indicators that impact PD.


Enhance pricing accuracy, generate synthetic data, and explore quantum computing applications in electricity and natural gas markets.

Machine Learning for Pricing Analysis:

  • Develop machine learning models, such as regression, time series analysis, or ensemble methods, to analyze historical pricing data and identify patterns in electricity and natural gas markets.

  • Incorporate external factors like weather conditions, market indicators, and demand patterns to build comprehensive pricing models.

  • Utilize advanced AI techniques like deep learning or reinforcement learning to capture complex pricing dynamics and optimize pricing strategies.

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