10 Questions
Why do banks in India need to build AI systems with GDPR and similar privacy regulations in mind?
Because India has its own data privacy regulations
What is the biggest challenge faced by the AI segment in the banking sector according to experts?
The scarcity of trained human resources
What is the primary geographic region where the GDPR regulation is currently applicable?
European countries
What is a potential consequence of the mass adoption of AI in the banking sector?
A grave unemployment problem
What is essential for the successful implementation of AI technologies in banking functions?
Identification of right use cases for AI implementation
Why do banks in India need to work with universities?
To develop skilled data scientists
What is a challenge faced by the industry in India, not just banks?
The unavailability of people with right data science skills
What is necessary for the development of skilled data scientists?
Both in-house training programs and working with universities
Who is the CEO of Finway Capital, a Delhi-based non-banking financial company?
Rachit Chawla
What is the significance of domain experts in AI implementation?
They are necessary for the identification of right use cases for AI implementation
Study Notes
Banking Industry Overview
- The Indian banking system consists of 12 public sector banks, 22 private sector banks, 44 foreign banks, 43 rural regional banks, and 1,484 urban cooperative banks.
- As of 2021, the total number of ATMs in India reached 210,940.
- Foreign exchange reserves of India reached $582.42 billion as of April 16, 2021.
Artificial Intelligence in Banking
- Artificial Narrow Intelligence (ANI) performs basic tasks like chatbots and personal assistants.
- Artificial General Intelligence (AGI) involves human-level tasks like self-driving cars.
- Artificial Super Intelligence (ASI) refers to intelligence beyond human capabilities.
Types of Artificial Intelligence
- AI: building systems that can do intelligent things.
- NLP: building systems that can understand language, a subset of AI.
- ML: building systems that can learn from experience, a subset of AI.
- NN: biologically inspired network of artificial neurons.
- DL: building systems that use deep neural networks on large datasets, a subset of ML.
History of Artificial Intelligence
- The term "Artificial Intelligence" was coined in 1956.
- AI has become popular due to increased data, advanced algorithms, and improved computing power and storage.
ICICI Bank's AI Initiative
- ICICI Bank has scaled up its RPA initiative to over 750 software robotics, handling approximately 2 million transactions daily, which is 20% of the transaction volumes.
- The bank has deployed software robotics functions across various operations, including retail, wholesale, and agri banking, to improve operational efficiency.
Challenges in Implementing AI in Banking
- Unavailability of skilled engineers to drive AI adoption.
- Scarcity of trained human resources, with existing workforce not familiar with latest tools and applications.
- Mass adoption of AI may cause unemployment in the banking sector.
- Need for more data scientists and in-house training programs to develop skilled data scientists.
- Identification of right use cases for AI implementation with the help of domain experts and data scientists.
This quiz assesses knowledge on the application of Artificial Intelligence in the banking industry. It covers various aspects of AI in banking, including its benefits and challenges. Test your understanding of AI in banking with this quiz!
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