AI in FinTech -  Quantum Computing

AI in FinTech - Quantum Computing

he future of FinTech is here!

And it is with AI!

But…

How to Manage AI Risk?  Join in, and let's explore together.


This week, I came across quantum computing in my daily reading. The word "Quantum" piqued my interest. To my surprise, there is a lot of talk about Quantum Computing, although it is in its nascent stages.  Let's dip our toes to find out what this is all about.  As I continued reading about this topic, I realised I was scratching the surface.  Let's start here and study more in the following days, weeks and beyond.  

What is Quantum Computing?

Quantum computing is a revolutionary technology where quantum mechanics forms the basis.  There are two key concepts that we need to understand to explain quantum computing.

(1) Superposition:

As we all know, traditional computers are ultimately represented by 0 and 1, and a bit is either 0 or 1 at any time. Quantum computing uses a concept called "qubits", where more than one state can coexist at the same time.  This concept of multiple states existing simultaneously is called "superposition". This superposition allows Quantum computing to be faster than traditional computing.  The superposition collapses as soon as the states are measured.

(2) Entanglement:

As the name suggests, entanglement occurs when two independent particles become "entangled," meaning that when measuring the state of one, the second particle's state is determined regardless of the distance between two particles.


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How Quantum Computing Can Tackle Climate and Energy Challenges - Eos

How Quantum Computing works?

The concept of superposition allows for multiple states to coexist simultaneously. The Quantum Superposition has the potential to solve complex problems without being limited by traditional bits, which are either 0 or 1. Let's try to solve a simple probability problem of a coin toss.  The answer is either head or tail at any given time.  Imagine quantum computing dealing with the problem as both head and tail (superposition) until it is decision time when the answer is either head or tail.  Say two coins are "entangled".  According to the concept of "entanglement", measuring the state of one coin reveals the state of the second coin without explicitly measuring the second coin.

Quantum Computing in FinTech

  • Risk modelling: Quantum computing may allow the handling multiple factors required for robust risk modelling.
  • Accelerated Machine Learning: Quantum computing could drastically reduce the time it takes to train a model as it's more efficient and faster.
  • Fraud Detection: Quantum-powered fraud detection systems will improve as quantum computing may be capable of handling more factors than traditional computing.

Challenges with Quantum Computing

  • Quantum Hardware - complex and expensive
  • Quantum Algorithms - new algorithms may be required to use Quantum Computing effectively.
  • Data Quality -  collecting and sanitising data is already complex. Quantum computing may need more data and new methods to ensure data quality.

Although there are NO Quantum Computers available today for regular commercial use, Quantum Computing is undoubtedly fascinating and has the potential to impact FinTech in a big way. This is evident with the partnership between IBM, AWS and financial institutions such as Goldman Sachs and HSBC to explore quantum computing for various applications.


References

What is quantum entanglement? | Space

The quantum coin toss – Physics World

What Is Quantum Superposition? - Caltech Science Exchange

What Is Quantum Computing? | IBM

Quantum Entanglement - Higgs Centre for Theoretical Physics

The quantum coin toss – Physics World

What Is Quantum Superposition? - Caltech Science Exchange

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Did you find the article informative?

 If you liked this, you may also find the previous articles in this series interesting. Here are the links:

1. AI in Fintech - Exploring Regulatory Landscape of AI Governance - Framework and Approaches

2. AI in Fintech - The Power of Large Language Models (LLMs)

3. AI in FinTech - Ethics in Financial Markets

4. AI in FinTech - The Future of Human-AI Collab

5. AI in FinTech - Explainable AI (XAI)

6. AI in FinTech - AI Risk Management - Part 1

7. AI in FinTech - AI Risk Management - Part 2

8. AI in FinTech - Building a Robust AI Security Framework

9. AI in FinTech - Continuous Monitoring for AI Risk Management

10. AI in FinTech - Taming the Risks, Seizing the Rewards

11. AI in FinTech - Build a Culture of AI Governance Beyond the Checkbox

12. AI in FinTech - The Future of Security to Protect Data and Systems

13. AI in FinTech - The Impact on Financial Inclusion

14. AI in FinTech - Microfinance for Financial Inclusion

15. AI in FinTech - Financial Literacy for Financial Inclusion

16. AI in FinTech - Financial Inclusion in Remittances

17. AI in FinTech - Financial Inclusion with Micro-Insurance

18. AI in FinTech - Anti-Money Laundering (AML)

19. AI in FinTech - The Rise of Generative AI

20. AI in FinTech - Generative AI Implementation

21. AI in FinTech - The Role of Central Banks in AI Governance

22. AI in FinTech - Need for Robust Governance

23. AI in FinTech - Data Readiness for AI Solutions

24. AI in FinTech - The Impact on Financial Stability

25. AI in FinTech - Job Displacement Landscape

26. AI in FinTech - Synthetic Data

27. AI in FinTech - Defenses against Cyber Crime



Vidhya Vijayakumar

Business and Technology Program Leadership | Technology and Operational Risk Management | Specialising in Regulatory, Risk and Governance | Equity & Debt Markets, FX and Security Lending

6mo

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