Ishaan Arora, FRM

I started-up with ₹1,500 at the age of 19. 💡

I remember I was in the 2nd year of my college and everyone around me were talking about either placements or MBA entrance prep, very few talked about startups. 🧠

Unfortunately those who did, had surrounded themselves with various negative thoughts that didn't let them startup like -

• You need a lot of money to start-up.
• It's better to start after experience.
• We need a remarkable idea then only we will get funding.

And the most common 9/10 startups fail.😮

My goal was just to give it a shot, until I fail. In the age group of 18-25 when you've no major responsibilities, you can literally do anything, fail at it and it still won't matter much. 🤔

My major learning in the last 3-4 years?

It is literally not as hard as it is shown.
Do not care about what others are saying, just have faith in yourself and put in your 100% - More often than not you'll be on the better side of things :)

Thoughts? 💯

#experience #learning #money #startup

Will AI kill finance jobs? 💡\n\nAccording to Forbes, 70% of financial firms are using machine learning to predict cash flow events, adjust credit scores, and detect fraud!\n\nHere are 5 ways financial firms are using AI right now, plus a look at what the future of this rapidly evolving industry could be.\n\n🪙 Risk Assessment and Management: AI uses smart algorithms to evaluate loan eligibility by analyzing various data points, allowing banks to make quick and fair decisions. It also helps manage risks by identifying trends and potential issues through data analysis, improving future planning.\n\n🪙Fraud detection \nAI-powered fraud detection systems monitor consumer purchasing patterns, generating alerts for unusual transactions that deviate from established behavior, thus protecting against fraud.\n\n🪙Credit Decisions \nAI rapidly assesses creditworthiness by integrating various data sources, including smartphone usage, which allows for more accurate and unbiased credit evaluations.\n\n🪙Preventing Cyberattacks \nAI strengthens cybersecurity by establishing baseline data patterns and identifying anomalies, thereby detecting potential threats before they escalate.\n\n🪙Predicting loan risks \nAI leverages customer spending behavior and digital footprints to forecast loan repayment likelihood, providing insights for individuals lacking traditional credit histories.\n\nHere are some examples of the financial firms that are using AI:\n\n🚀Bank of America: Their chatbot, “Erica,” started in 2018 and has helped over 10 million users. By mid-2019, Erica could understand nearly 500,000 different ways people asked questions.\n\n🚀JPMorgan Chase: This bank uses smart tools to catch fraud. They have an algorithm that looks for patterns in suspicious activity. When you make a credit card purchase, the details go to their data centers, which check if the transaction looks fishy.\n\n🚀Kensho: This company creates analytical tools used by top financial institutions like Goldman Sachs, Bank of America, Merrill Lynch, and JPMorgan Chase.\n\nBut the real question is, Will AI Uphold Ethics in the Finance Industry?\n\n➠ Bias in Decision-Making:\nAI algorithms can sometimes fail, especially when programmed with profit-focused goals. For example, an AI system evaluating creditworthiness may push predatory practices like offering subprime loans to individuals with low credit scores, which is ethically questionable.\n\n➠ Accountability Issues:\nWhen AI makes a wrong decision, such as in a self-driving car accident or a poor financial recommendation, it's unclear who should be held responsible—this raises concerns about accountability.\n\n➠ Lack of transparency:\nAI algorithms are complex, and it’s not always clear how or why they arrive at certain decisions, making it difficult to fully trust or understand their conclusions.\n\nEven with these three big concerns, experts think AI could save the banking industry about $1 trillion by 2030.\n\nThoughts?💡\n\n#finance #ai #jobs