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ROLE OF AI
IN
BANKING
NELLORE CHANDANA
LEKKALA VASAVI REDDY
PATIL SAGAR
GOUTHAMI
KUSHALAPPA
Artificial intelligence
The simulation of human intelligence processes by
machines.
Intelligence demonstrated by computers.
AI refers to computational tools that are able to
substitute for human intelligence in the
performance of certain tasks
History of AI in Banking
The first bank in the world to adopt Al (Artificial
Intelligence) can be traced back to the 1980s. The Bank of
Scotland implemented an Al-based system called "Fraud
Detection System" in 1985 to detect potential fraudulent
transactions. This system utilized a neural network to analyze
patterns and identify suspicious activities, marking an early
application of Al technology in the banking sector
Scope of AI
The main aim of AI in the banking industry is to assist the
customers by keeping their preferences a priority.
Additionally, AI plays an essential role in assuring that
customers are happy with the services offered by the bank.
It also plays a crucial role in risk management by preventing
fraud and fighting money laundering in real-time.
1: Process optimization-In claims processing-In mortgage
processing-In customer service-In operations-
2: Credit risk management
3: Fraud and money laundering-In fraud-In money laundering
4: Trading and wealth management-Robo advisors-Trade
channel optimization-Stockmarkets
5: Marketing
6: Security and compliance-Security-Compliance
APPLICATIONS OF AI IN
BANKING
CYBERSECURITY AND FRAUD DETECTION REGULATORY
COMPLIANCE
CHATBOTS AND CUSTOMER SERVICE PREDICTIVE ANALYTICS
LOAN AND CREDIT DECISIONS DATA COLLECTION AND
ANALYSIS
Real-World Examples of AI In Banking
Initialization
 Credit scoring
 Clerical
automation
 General
Digitization
Continuation
 Offer+Pricing
Optimization
 Introducing
Upcoming
 Advanced
Recommenders
 Full ABA Decisioning
 Automated Portfolio
Management
CHALLENGES FACED BY BANK USING AI
1.Data quality and availability
2.Data privacy and security
3.Regulatory compliance
4.Explainatory and transparency
5.Talent and expertise
6.Ethical consideration
7.Change management and cultural
shift
Why must banking sector embrace AI-FIRST
1.Enhanced efficiency
2.Improved customer experience
3.Fraud detection and prevention
4.Risk assessment and credit scoring
5.Predict analysis and investment strategies
References
■ https://analyzingalpha.com/history-of-ai-in-finance
■ https://www.techtarget.com/searchenterpriseai/feature/AI-in-
banking-industry-brings-operational-improvements
■ https://www.hcltech.com/blogs/how-artificial-intelligence-
transforming-banking-
sector#:~:text=Even%20the%20traditional%20banks%20hav
e,money%20laundering%20in%20real%2Dtime.
■ https://bfsi.eletsonline.com/rise-of-artificial-intelligence-in-
banking/
AI is not the future of banking
It is the present!

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role of ai in banking (2).pptx

  • 1. ROLE OF AI IN BANKING NELLORE CHANDANA LEKKALA VASAVI REDDY PATIL SAGAR GOUTHAMI KUSHALAPPA
  • 2. Artificial intelligence The simulation of human intelligence processes by machines. Intelligence demonstrated by computers. AI refers to computational tools that are able to substitute for human intelligence in the performance of certain tasks
  • 3. History of AI in Banking The first bank in the world to adopt Al (Artificial Intelligence) can be traced back to the 1980s. The Bank of Scotland implemented an Al-based system called "Fraud Detection System" in 1985 to detect potential fraudulent transactions. This system utilized a neural network to analyze patterns and identify suspicious activities, marking an early application of Al technology in the banking sector
  • 4. Scope of AI The main aim of AI in the banking industry is to assist the customers by keeping their preferences a priority. Additionally, AI plays an essential role in assuring that customers are happy with the services offered by the bank. It also plays a crucial role in risk management by preventing fraud and fighting money laundering in real-time. 1: Process optimization-In claims processing-In mortgage processing-In customer service-In operations- 2: Credit risk management 3: Fraud and money laundering-In fraud-In money laundering 4: Trading and wealth management-Robo advisors-Trade channel optimization-Stockmarkets 5: Marketing 6: Security and compliance-Security-Compliance
  • 5. APPLICATIONS OF AI IN BANKING CYBERSECURITY AND FRAUD DETECTION REGULATORY COMPLIANCE CHATBOTS AND CUSTOMER SERVICE PREDICTIVE ANALYTICS LOAN AND CREDIT DECISIONS DATA COLLECTION AND ANALYSIS
  • 6. Real-World Examples of AI In Banking
  • 7.
  • 8. Initialization  Credit scoring  Clerical automation  General Digitization Continuation  Offer+Pricing Optimization  Introducing Upcoming  Advanced Recommenders  Full ABA Decisioning  Automated Portfolio Management
  • 9. CHALLENGES FACED BY BANK USING AI 1.Data quality and availability 2.Data privacy and security 3.Regulatory compliance 4.Explainatory and transparency 5.Talent and expertise 6.Ethical consideration 7.Change management and cultural shift
  • 10. Why must banking sector embrace AI-FIRST 1.Enhanced efficiency 2.Improved customer experience 3.Fraud detection and prevention 4.Risk assessment and credit scoring 5.Predict analysis and investment strategies
  • 11. References ■ https://analyzingalpha.com/history-of-ai-in-finance ■ https://www.techtarget.com/searchenterpriseai/feature/AI-in- banking-industry-brings-operational-improvements ■ https://www.hcltech.com/blogs/how-artificial-intelligence- transforming-banking- sector#:~:text=Even%20the%20traditional%20banks%20hav e,money%20laundering%20in%20real%2Dtime. ■ https://bfsi.eletsonline.com/rise-of-artificial-intelligence-in- banking/
  • 12. AI is not the future of banking It is the present!