This document discusses the use of artificial intelligence in finance. It begins with an introduction to AI and how it can be valuable in finance by automating tasks, improving security, and helping businesses move in innovative directions. It then discusses how machine learning is used in finance to extract insights from data and solve complex problems. Specific uses of AI in finance mentioned include personalized banking, credit scoring, and fraud detection. The document also covers advantages like automating work and preventing fraud, and disadvantages such as cost and lack of regulatory scrutiny. It concludes that AI contributes significantly to the financial industry by helping it learn patterns from data and stay updated.

1. WELCOME

2. ARTIFICIAL INTELLIGENCE
IN FINANCE
PRESENTED BY
VIDYA BORADE

3. CONTENT

5. ENTRODUCTION
ARTIFICIAL INTELLIGENCE refers to machines or system that mimic
human intelligence to perform tasks.ai is intended to significantly
enhance human capabilities and contribution, making it very valuable
valuable assest.
FINANCE is the management of money and includes activities such as
investing ,Borrowing,lending,budgeting,saving and forecasting.
ARTIFICIAL INTELLIGENCE IN FINANCE can free up personal,improve
security measures and ensure that the business is moving in the right
technology-Advanced,ennovative direction.

6. HOW ARTIFICIAL INTELLIGENCE AND
MACHINE LEARNING IS USE IN FINANCE
machine learning works by extracting meaningful
insights from raw sets of data and provides accurate results. this
information is then used to solve complex and data-rich problems
that are critical to the banking & finance sector.

7. USES OF AI IN FINANCE SECTOR
Personalized Banking Experience
Customers can now effortlessly log into their banking apps by
simply looking at their phones. All this is thanks to advances in machine
learning and the development of cutting-edge neural engines
Credit Scoring
According to Forbes, 70% of financial firms are using machine
learning to predict cash flow events and adjust credit scores.
Fraud Detection and Risk Management

8. Fraud Detection and Risk Management
AI applications in the fintech industry range from recognizing
abnormal transactions to identifying suspicious and potentially fraudulent
activities by analyzing massive amounts of data. AI can quickly gain insights
that help protect organizations against losses and increase ROI for their
customers.

9. Advantages and disadvantages of
using AI in finance sector
advantages
 AI can automate manual work
 By relying on AI technology for data entry,
review, and verification, financial institutions
can reduce the time necessary to approve an
application while increasing accuracy by
avoiding human error.
 AI can quickly identify and prevent
fraud
 AI does an exponentially better job of
correctly identifying abnormal behavior than
any human could, and it, therefore, helps
financial services organizations reduce fraud
risk and costs, all while enhancing customer
satisfaction.
disadvantages
 Expensive
 It may not be possible for all the
finance companies to go for this big
expensive model
 Implementing the proper
algorithm
 Although the AI works flawlessly with
faster results, its accuracy depends on
the algorithm it works on.
 Lack of regulatory scrutiny
 AI and its technologies use data of the
individuals to drive results

10. APPLICATION OF AI IN FINANCIAL WORLD
AI in personal finance
AI in consumer finance

11. AI in corporate finance

12. GLOBAL GROWTH OF AI IN LAST 3
YEARS

14. • GROWING EMPACT OF AI IN FINANCIAL
SERVIVES
AI and Process Automation
AI and Personalized Banking
AI and Trading

15. CONCLUSION
AI in finance is generally about learning of patterns, data and
many developments in the financial world. In conclusion, artificial
intelligence significantly contributes to the finance industry,
will continue to keep the financial services updated and ready
face the market

16. THANK YOU