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5 Ways AI Is Influencing the Fintech Ecosystem

GettyImages-1249307374Artificial intelligence (AI) is poised to alter the Fintech ecosystem over the coming years. As the market size of AI in Fintech continues to grow – already estimated to be in the ballpark of $43 Billion in 2023, new innovations are expected to emerge as the computational power of AI continues to expand. In a world driven by simplicity, AI will be the accelerator of enhanced customer experiences. The days of one-size-fits-all financial products and services are gradually fading away, ushering in a new era of hyper-personalized solutions. Let's explore the five ways AI has already exerted its influence on the Fintech landscape.

 

1. AI Chatbots

AI-powered chatbots have reformed customer support in the fintech world. These intelligent bots provide around the clock assistance to consumers for a wide range of financial questions.

The ubiquity of chatbots is unquestionable, as 80% of people said they have interacted with a chatbot at some point in the last year. In order to keep pace with the mercurial demands of fintech users, these AI chatbots are continually trained using natural language processing (NLP) to extract meaning from text to output solutions. Let’s take a look at some of the questions AI chatbots are able to answer.

 

Account Related Questions
  • How can I open a new account?
  • What documents do I need to provide for account verification?
  • How do I update my account information?

 

Transaction Assistance
  • How do I transfer funds between accounts?
  • Can you help me track a recent transaction?
  • What are the fees for international money transfers?

 

Bill Payments
  • How can I pay my utility bills through the platform?
  • Can I set up automatic bill payments?
  • What payment methods are accepted for bill payments?

 

Loan and Credit Queries
  • Am I eligible for a personal loan or credit card?
  • What is the interest rate on personal loans?
  • How can I apply for a credit limit increase?

 

Investment Guidance
  • What investment options are available?
  • Can you recommend suitable investment products based on my risk profile?
  • How do I diversify my investment portfolio?

 

2. Fraud Detection & Prevention

It is estimated that digital fraud losses globally will surpass $343 billion from 2023 to 2027. Ensuring the security and integrity of financial transactions should therefore be a top priority for every Fintech.

AI plays a crucial role in strengthening the security and fraud prevention measures in fintech. Machine learning algorithms can analyze vast amounts of historical transaction data and identify patterns associated with fraudulent activities. By detecting anomalies and suspicious behavior in real-time, AI systems can help financial institutions prevent unauthorized access and efficiently identity theft.

Major Fintech players like PayPal, have leveraged machine learning algorithms to confront fraud. In fact, PayPal experiences remarkably low fraud rates due to their early integration of AI-driven models. Fraud accounted for only 0.32% of its revenue, which is significantly better than the 1.32% average observed by most merchants.

 

3. Analyzing Credit Reputation

Traditional credit scoring methods often rely on limited data, which might not paint an accurate picture of an individual's creditworthiness. Artificial Intelligence, on the other hand, can analyze vast datasets to assess credit risk more accurately. This enables fintech companies to extend credit to a wider range of customers, including those with limited credit histories, while maintaining risk levels.

Underwrite.ai is a company using AI to assess credit risk. The tool analyzes thousands of data points from credit bureau sources to accurately model credit risk for any consumer. The machine learning algorithm was first applied to correlate DNA data to the likelihood of developing prostate cancer – and has since been applied to business lending. A cool example that sheds light on the large range of machine learning applications.

 

4. Automating Trading and Investment Strategies

The majority of trading and investment choices can be effectively automated through AI-driven algorithms. These algorithms can analyze market trends, geopolitical movements, and various financial indicators at a speed and scale beyond human capabilities. As a result, AI-powered trading systems can execute trades, optimize investment portfolios, and manage risk more efficiently, potentially leading to better returns for investors.

The multinational financial services firm, JPMorgan Chase, recently filed a trademark for a product called 'IndexGPT' that relies on AI to help customers pick stocks. Other banking giants, like Goldman Sachs and Morgan Stanley, are expected to follow suit and develop AI-driven tools to help customers invest in the near future.

MetaTrader 4 is another example of AI-powered algorithmic trading. This software leverages Expert Advisors (EAs), otherwise known as AI-based bots, to automate trading decisions. The user has the ability to configure their trading environment to leverage adjacent applications to optimize their investment approach.

 

5. Personalized Portfolio Management

Quantum Machine Learning – the intersection of machine learning and quantum computing – is being leveraged in the world of fintech to create customized investment advice. This technology can optimize portfolio diversification, adjust asset allocations in real-time, and adapt strategies to changing market conditions, ultimately offering more sophisticated and personalized investment management solutions with the aim of maximizing returns and minimizing risk for individual investors. While the technology is still in its infancy, it projects to have a massive impact on typical operations with the realm of portfolio management.

Take Acorn for example – this Fintech leverages an AI-driven tool to manage the user’s investment. The tool asks the individual investor a series of financial questions to allow AI to build a customized strategy to align with their personal interests – see below.

 

Questions
  • What is your employment status?
  • What is your yearly income?
  • What is your net worth?
  • What is your investment goal?
  • What is your level of financial education?
  • How do you plan to invest initially?
  • When will you access your Acorn investments?
  • Are you looking to invest in portfolios for how they approach (ESG) environment, social, or governance issues?

 

From there the AI-driven tools sets a risk level at your discretion – from conservative to aggressive – to diversify your portfolio accordingly – see below.

 

Risk Levels
  • Conservative – 20% Bonds 80 % Stocks
  • Moderately Conservative – 60% Bonds 40% Stocks
  • Moderate – 40% Bonds 60% Stocks
  • Moderately Aggressive – 20% Bonds 80% Stocks
  • Aggressive – 0% Bonds 100% Stocks

 

Locate Elite Talent in the World of AI

The transformative power of artificial intelligence in the fintech industry is undeniable. As every company continues to morph into a Fintech, executives should be mulling over how they can harness AI to improve company operations. If your Fintech is looking to capitalize on the AI boom and drive long-term success consider reaching out to our experts here to help locate elite talent in the world of AI.

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