Book Image

Financial Modeling Using Quantum Computing

By : Anshul Saxena, Javier Mancilla, Iraitz Montalban, Christophe Pere
5 (1)
Book Image

Financial Modeling Using Quantum Computing

5 (1)
By: Anshul Saxena, Javier Mancilla, Iraitz Montalban, Christophe Pere

Overview of this book

Quantum computing has the potential to revolutionize the computing paradigm. By integrating quantum algorithms with artificial intelligence and machine learning, we can harness the power of qubits to deliver comprehensive and optimized solutions for intricate financial problems. This book offers step-by-step guidance on using various quantum algorithm frameworks within a Python environment, enabling you to tackle business challenges in finance. With the use of contrasting solutions from well-known Python libraries with quantum algorithms, you’ll discover the advantages of the quantum approach. Focusing on clarity, the authors expertly present complex quantum algorithms in a straightforward, yet comprehensive way. Throughout the book, you'll become adept at working with simple programs illustrating quantum computing principles. Gradually, you'll progress to more sophisticated programs and algorithms that harness the full power of quantum computing. By the end of this book, you’ll be able to design, implement and run your own quantum computing programs to turbocharge your financial modelling.
Table of Contents (16 chapters)
1
Part 1: Basic Applications of Quantum Computing in Finance
5
Part 2: Advanced Applications of Quantum Computing in Finance
10
Part 3: Upcoming Quantum Scenario

The relevance of credit risk analysis

With the objective of providing a broader context and understanding of the relevance of addressing classification problems in the finance sector, for this part of the book, it is important to define some core concepts, even from a high-level perspective. The term “credit risk” in the context of this chapter is the chance that a lender will lose money if a borrower doesn’t pay back a loan by a certain date. As the credit card business has grown quickly, as illustrated in Figure 6.1, and the financial players have grown over the years, the challenge of expanding the scope of targeted people requires more sophisticated underwriting systems. This puts a big portion of financial institutions at risk if the means to assess this risk are not accurate enough.

Given the situation previously described, it is often necessary to look at the credit risk of customers who have little or no credit history to expand the current client segments...