Spanish Business Award 2025
Fermac Risk Wins "Most Innovative Financial Risk Solutions Company 2025 – Spain" at the Spanish Business Awards We’re proud to announce that Fermac Risk has been named Most Innovative Financial Risk Solutions Company 2025 – Spain by Euro Business News magazine as part of the Spanish Business Awards 2025.
17 Years of Training
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Since 2008, our clients have invited us to their cities, allowing us the privilege of delivering in-person training across 35 cities throughout Europe, Africa, and the Americas.
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Over the past 17 years, we have had the honor of serving nearly 3,000 participants — professionals committed to advancing their knowledge in financial risk, modeling, and innovation.
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Our journey is enriched with memories of clients from Belgium, Poland, France, Costa Rica, Ecuador, Mexico, Brazil, Chile, Peru, and Angola, many of whom traveled to attend our courses in Madrid and Barcelona.
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Since 2024, we have expanded to new horizons, reaching Asia — with clients in India, Singapore, and the United Arab Emirates placing their trust in our expertise.
Machine Learning and Quantum Computing
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In 2017, we incorporated machine learning into our financial risk courses to enhance the course quality.
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Looking ahead, we have meticulously planned to incorporate quantum computing in 2022 and implement generative AI by the end of 2023, a testament to our commitment to staying at the forefront of technological advancements.
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We are passionate about what we do and have tested these new technologies, yielding excellent results. This includes better credit scoring models, more accurate scenarios, synthetic data creation, improved backtesting, modeling with uncertainty, and faster calculations.
🚀 Why Our Subscription-Based
and Self-Paced Learning
Is a Smart Investment
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Cost-Effective Talent Development
Access over 15 advanced courses through an annual subscription — a fraction of the cost of traditional consulting or live seminars, with measurable returns in staff capability and regulatory readiness. -
Flexible, Scalable, and On-Demand
Teams learn anytime, anywhere, with self-paced modules that accommodate international operations and remote work environments. -
Regulatory Alignment
All content is aligned with IRB, IFRS 9, Basel III, ICAAP, and emerging guidelines — ideal for risk, audit, compliance, and model validation teams. -
Hands-On, Practical Training
Exercises in Python, R, Excel, and SAS using real datasets simulate actual bank modeling challenges — not just theory. -
Cutting-Edge Technology
Go beyond traditional risk training with modules in AI, Generative AI, AI Agents, and Quantum Machine Learning, preparing your teams for the future of risk analytics.
Why Banks Should Invest in Our Training Solutions
In a constantly evolving financial landscape, staying ahead is not a luxury — it’s a strategic necessity. Regulations are more demanding, risk models more complex, and the integration of AI and emerging technologies like quantum computing is reshaping how we measure, manage, and mitigate risk.
At Fermac Risk, we offer a training ecosystem designed for banks and financial institutions that want to build stronger teams, reduce model risk, and comply with global standards — all while embracing innovation.
How could Quantum Computing and
AI benefit the Financial Industry?
- We utilize Transformers and Quantum LSTM models to forecast time series of deposit rates. This decreases MAPE, one of the best error metrics, and enhances backtesting.
Credit Risk
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We increase the ROC in credit scoring using Quantum Convolutional Neural Network, improving the discriminant power and Backtesting.
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We use Bayesian Neural Network to reduce the uncertainty in the forecasting of PD.
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Use Deep Learning Survival and Random Forest Survival instead of Cox Regression to estimate lifetime PD improvement backtesting.
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With noise, uncertainty, and lack of data, we utilize Robust Machine Learning to model LGD, reducing Model Risk.
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The economic capital for credit risk has been estimated using Quantum Monte Carlo faster than Simulation Monte Carlo.
Counterparty Credit Risk
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We utilized a Quantum Neural Network to simulate paths for calculating the Credit Value Adjustment of a derivatives portfolio. The trained neural networks replace the original pricing model.
CyberRisk
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We explain how Shor's algorithm, which can factorize quickly on a quantum computer, undermines RSA's cryptography security assumptions. We also expose how Lattice-based constructions support standards of post-quantum cryptography.
Model Risk
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Expose the state-of-the-art methods in interpretable machine learning and model diagnosis.
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Reduce the uncertainty in lifetime PD estimation using Quantum Markov Chain Monte Carlo QMCMC over traditional MCMC approach
Portfolio Optimization
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With 16 qubits and quantum annealing, we optimize a portfolio and perform calculations faster than the classical approach.
Stress Testing
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We utilize Generative Adversarial Networks (GANs) and Variational AutoEncoders to generate synthetic data that retains the original data's statistical characteristics while generating new data points. This is particularly useful for creating economic scenarios during turbulent periods such as war, geopolitical tensions, and climate change.
Green AI
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Tensor networks in machine learning reduce the number of parameters in neural network models, lowering energy costs.
Derivatives Pricing
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We showcase the superiority of Quantum Monte Carlo Simulation over classical Monte Carlo Simulation in terms of speed for pricing exotic options.