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Consultancy in AI,Generative AI and Quantum Computacional in
Lifetime PD IFRS 9
Consultancy specializing in AI, Generative AI, and quantum computing can enhance the accuracy of Lifetime PD:
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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.
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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.
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Utilize natural language processing (NLP) techniques to extract valuable insights from textual data, such as borrower information or macroeconomic indicators that impact PD.
Benefits of Consultancy of Generative AI and QC in
Lifetime PD in IFRS 9
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To use Generative AI and quantum computing for Lifetime Probability of Default (PD) in IFRS 9, consider the following approaches:
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Generative AI for Lifetime PD:
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Use generative models, such as Variational Autoencoders (VAEs) or Generative Adversarial Networks (GANs), to generate synthetic data that can capture the underlying distribution of default probabilities.
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Train generative models on historical loan data to generate new samples that represent potential future default scenarios, taking into account the dynamic nature of PD over time.
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Use generative models to augment your training dataset, increasing the number of samples and improving the accuracy and stability of your Lifetime PD models.
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Quantum Computing for Lifetime PD:
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Explore quantum algorithms to analyze large-scale datasets and perform more accurate simulations of complex credit risk models.
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Utilize quantum machine learning algorithms to enhance the precision and efficiency of PD estimations, especially for models involving vast amounts of data and variables.
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Utilize quantum optimization algorithms to enhance the calibration and parameter estimation of Lifetime PD models, potentially improving their accuracy and robustness.
Compare Consultancy Packages
Package
Description
Scripts (1) in Python or R
Credit scoring using machine learning and deep learning
Quantum Machine Learning
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Credit Scoring
Estimation PD (3)
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Cox Regression
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Panel Data Logistic Regression
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Bayesian Logistic Regression
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LASSO Logistic Regression
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Random Forest Survival
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Deep Learning Survival
Calibration PD
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Approximation methods
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Scaled beta distribution
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Asymmetric Laplace distribution
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rubber function
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Platt scaling
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Broken curve model
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Isotonic regression
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Gaussian Process Regression
Vintage model
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Exogenous Maturity Vintage EMV Model
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decomposition analysis
Matrix Models (3)
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Basel ASRF model
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Multinomial Regression Model
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Multi-State Markov Model
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Machine Learning
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SVM
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Neural Network
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PD Probabilistic Machine Learning with scenarios
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PD Forecasting using Bayesian Neural Networks
PD Forecasting
Econometric Models
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VAR Autoregressive
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VEC Error Correction
Deep learning
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Long short term memory LSTM
Advanced DL
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DeepAR
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Transformer Model
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Quantum LSTM
Lifetime PD Generative AI
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Variational Autoencoders
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Generative Adversarial Networks
Hours
Lite
We offer a script that can be used to model Lifetime PD based on our data
Python
Our data: Default status and 8 exploratory variable
Our Data with 10 explanatory variables
Our Data with 10 explanatory variables
Our Data with 3 macroeconomic explanatory variables
3
Immediately
8.000 EUR
Standard
We offer a script that can be used to model Lifetime PD based on your data
Python
You can input your data along with up to 10 explanatory variables
You can input your data along with up to 10 explanatory variables.
You can input your data along with up to 10 explanatory variables.
You can input your data along with up to 5 macroeconomic explanatory variables.
6
3 Days
12.000 EUR
Pro
We offer a script that can be used to model Lifetime PD based on your data
Python
You can input your data along with up to 25 explanatory variables
You can input your data along with up to 25 explanatory variables
You can input your data along with up to 25 explanatory variables.
You can input your data along with up to 10 macroeconomic explanatory variables.
10
5 Days
18.000 EUR
Premium
We offer a script that can be used to model Lifetime PD based on your data
Python
You can input your data along with up to 100 explanatory variables
You can input your data along with up to 100 explanatory variables
You can input your data along with up to 100 explanatory variables.
You can input your data along with up to 10 macroeconomic explanatory variables.
15
10 Days
24.000 EUR
1. The scripts are delivered as Jupyter Notebook files.
2. Your data for the Credit Scoring Model could include the ID and Default Status along with the explanatory variables x1 to xm. We accept panel data, and the identification of panel data does not take into account as an explanatory variable.
3. Your data for the Calibrating PD Model could include the Aging, Date, Months Of Books, N Total, and Bad, along with the macroeconomic explanatory variables x1 to xm. We accept panel data, and the identification of panel data does not take into account as an explanatory variable.
Important: Firstly, we will perform an audit of the model. If the audit is positive, we will proceed with the model development. Otherwise, we will charge a fee of 5% of the contracted package value.
Important: The number of account operations exceeding a certain limit may result in additional charges.
Please remember the following message regarding the Generative AI Model data we need to discuss with you.
Clients
