
Explore overview of financial models, use cases like valuation, pricing, and credit scoring, and four-step modeling process, with generative AI accelerating data gathering, shaping assumptions, building the model, and validation.
Explore the value at risk (VaR) model for banking stress testing, covering historical, variance-covariance, and Monte Carlo methods, confidence intervals, and limitations such as tail risk and biases, with backtesting.
Explore how to enhance value at risk models with Gen AI to stress test banking systems, capturing tail risks and emerging scenarios through synthetic data and unstructured text.
Learn to build anti-money laundering financial models with traditional methods and Genii, including transaction monitors, client risk scoring, and network models, using transactions, client profiles, payment networks, and relationships.
Explore data and features for anti-money laundering, including transaction data, customer information, sanction and watch lists, politically exposed persons, velocity and anomaly indicators, and network-based relationship mapping.
Explore how generative AI enhances financial modeling, covering LLM basics, the modeling process, and how AI gathers data, shapes assumptions, applies formulas, and checks errors.
GENERATIVE AI IS CHANGING THE MODELING GAME
Generative AI has revolutionized several industries. And financial modeling is no different.
With the capability to summarize data, transform them and process them, validate assumptions, generate scenarios, apply formulas and templates instantly, and more, text generative AIs such as ChatGPT are changing the modeling landscape.
This course will cover how to incorporate generative AI into your financial modeling pipeline, improving it for this new era.
LET ME TELL YOU... EVERYTHING.
Some people - including me - love to know what they're getting in a package.
And by this, I mean, EVERYTHING that is in the package.
So, here is a list of everything that this course covers:
You'll learn about the basics of generative AI, including its capabilities, limitations, common models and technology used, and how it accelerates various tasks;
You'll learn about the basics of financial modeling, including the general modeling process with four steps (gathering data, establishing assumptions/constraints, building the model, and validating it/using it);
You'll learn about some common modeling use cases in finance, such as the Discounted Cash Flows analysis for valuation, regression for credit scoring, time series and machine learning for security price prediction, and actuarial/catastrophe models for insurance risk pricing, as well as the usual inputs and assumptions in general;
You'll learn about the main types of financial models: mathematical (where we apply operations to the inputs given), statistical (where we calculate results based on causality, correlation, or other relationships among variables), simulations (where we stochastically simulate various scenarios and gauge variations in outputs due to these), and algorithmic/computational (where we execute a set of steps, in a programmatic manner), as well as how these are used for common use cases such as banking/lending, trading, fraud detection or insurance;
You'll learn about the steps of the modeling process in depth, including what to take into account at each step (when gathering and preparing data, when establishing assumptions and constraints, when building the model itself, and when validating or using the model);
You'll learn about ways in which gen AI can accelerate or augment each of the four main steps of the modeling process (extracting or transforming data when gathering data, double-checking and generating assumptions when establishing assumptions, applying formulas or making calculations when building the model, and validating outputs or generating various scenarios when validating or using the model);
You'll learn about the usual models used for credit analysis (regression models, credit scoring models, and machine learning models), and how Gen AI can augment them;
You'll learn about the usual models used for fraud prevention (rules-based systems, anomaly detectors, and network algorithms), and how Gen AI can augment them;
MY INVITATION TO YOU
Remember that you always have a 30-day money-back guarantee, so there is no risk for you.
Also, I suggest you make use of the free preview videos to make sure the course really is a fit. I don't want you to waste your money.
If you think this course is a fit, and can take your knowledge of dealing with change to the next level... it would be a pleasure to have you as a student.
See on the other side!