As much as we are absolutely terrified (and rightfully so) of AI stealing all our jobs and replacing all our artists, we must also be quite receptive to the fact that if we deal with the sudden surge of AI technology in a constructive way, we could definitely channelise it towards more productive avenues. Especially in the Fintech atmosphere, the applications of AI technology are simply growing day by day and to stay informed is becoming really important so that we don't fall behind. That is exactly what we’re here for (You’re welcome)

Challenges and considerations:

Now before we get into the AI-driven fintech kaleidoscope, let’s understand the risks and opportunities that using AI with finance actually brings.

1. Data quality and security:

Now, for AI’s effectiveness, it all matters on the quality of data that WE feed it. If we give our AI model really low quality data, for example, some missing values, incorrect data, highly biassed data (bias is actually a really interesting part here) the predictive aspects of AI that we want will be highly flawed. Hence as users our responsibility starts with providing high-quality data

2. Ethical considerations:

Elaborating on the aspect of bias mentioned before, ‘bias’ in terms of AI means feeding data that contains any preconceived notions or opinions. Sometimes even our algorithms may fail to account for certain possibilities that as developers we oversee due to personal bias. That is why good AI models require extensive research.

FinTech applications:

Finally let’s start talking about why y’all are really here, the financial applications of AI and how the advent of it is completely changing the FinTech landscape.

1. Share market and company evaluation:

AI can quickly analyse large volumes of data (surprising!) to identify trends and help forecast future performance, letting investors chart investment growth and evaluate potential risk. When data reveals which company is expected to do very well in the near future, it makes investors interested in capitalising on the expected large gains. But this is exactly where our discussion on the data quality comes into play, if the data is not of high quality, it can manipulate people into investing in the wrong avenues which just sounds like a financial nightmare to experience.

2. Risk management:

 AI allows for real-time risk monitoring, proactive threat detection, and better preparation for economic downturns. By continuously monitoring internal and external data sources to identify potential risks early on, AI allows institutions to take timely and appropriate mitigation measures. Long story short, AI tells you when (economic) danger is approaching so you can save yourself (mitigate risk).

3. Treasury management:

AI forecasts cash flow with greater accuracy, optimises investment portfolios based on real-time market trends, and empowers informed financial decisions. AI-powered cash flow forecasting helps businesses manage their liquidity more effectively, preventing potential shortfalls. In short, AI just makes sure you do not spend so much so that your funds deplete to such an extent they are almost unusable (like your gpay balance)

4. Payments:

 AI detects and prevents fraud in real-time, ensuring secure and efficient transactions. Moreover, AI can analyse transaction patterns and identify anomalies that might indicate fraudulent activity, such as unusual purchase locations or significant deviations from typical spending habits. This proactive approach not only safeguards clients’ assets but also fosters a sense of trust and security. That is why the next time you will be making a very impulsive purchase with your card, AI is going to keep track of that and keep analysing your spending habits to check whether it was really you who bought all those Coldplay tickets, or whether it was a scamster. Additionally, AI can streamline payment processing, allowing for faster and more convenient transfers of funds.