This is How AI will disrupt Fintech

Table of contents

Artificial Intelligence (AI) has been slowly asserting its influence in almost every industry in the 21st century. With advanced technological advancements over the years, AI has become a supreme force that when implemented can do wonders for any business.
The financial industry has its own share of technologies called “Fintech” (a combination of finance and technology) that are used to enhance and automate various financial processes. With the arrival of AI, financial institutions are leveraging AI-based models to work in tandem with their Fintech applications to boost operations and revenue.
Earlier, the financial industry was dominated by people who were experts in areas such as investing, lending, and trading. Today, AI has proven that it can perform the roles of these experts with much better speed and accuracy. By analyzing large amounts of financial data, advanced AI algorithms are capable of learning on their own and make optimal financial decisions without human bias.
According to a recent research report, the AI in Fintech market is expected to grow up to $26.92 billion by 2024. Owing to all the above factors, let’s take a look at how AI will disrupt Fintech and the financial industry:

  1. Customer Engagement – This is one of the primary areas where AI will play a major role. Every company in the financial industry is looking to increase user engagement on its website and other digital touch points. There are a lot of digital technologies in the market which can assist in increasing customer engagement. However, these technologies don’t have the means to operate at scale as well as target each individual customer. Coupling AI with these Fintech tools can help increase engagement with millions of customers.
  2. Financial Advisory – Digital financial advisors can be integrated with AI-powered platforms to offer users advising services related to investments, banking, asset management. These advisors have completely eliminated the need to have human financial advisors and relationship managers.

For example, an AI-based digital advisor can collect the details about an investor’s financial goals and the level of risk that they are willing to incur. Using advanced algorithms, it can analyze the data and come up with investment suggestions to the investor. It also has the capability to fully automate the purchase and management of the person’s investments.

  1. Underwriting, Pricing and Credit Risk Assessment – For underwriting services, AI can help in speeding up the whole process and reducing the turnaround time. It, therefore, increases the efficiency of client proposals and improves the overall customer experience. For assessing a client’s credit risk, an AI-powered model can provide an immediate assessment, which then helps advisors to deliver the right offer to the client.
  2. Regulatory Compliance – The regulatory landscape is a constant challenge for most financial companies as it keeps changing all the time. AI’s biggest advantage is that it can remember, learn, and comply with all applicable financial laws. It can help financial institutions in meeting regulatory standards on a regular basis. Moreover, it eliminates human errors from compliance and detects patterns to spot fraudulent activities.
  3. Risk Management and Fraud Detection – AI has many applications when it comes to risk management and fraud detection. It helps banks and other financial firms by alerting them to potentially fraudulent transactions. It can accurately predict if an account is at risk through factors such as the number of compromises endured in the past, etc. Using appropriate machine learning algorithms, AI can also help in the reduction of false positives. This not only improves the fraud detection efficiency but also improves customer satisfaction.
  4. AI-powered Chatbots – Thanks to AI, chatbots have become more sophisticated in recent times. Apart from communication purposes, they are being used as customer-facing tools. Customers can avail the services of these AI-driven chatbots for requests and queries related to their accounts. These include details such as balance enquiries, personal information, spending habits, etc.

Bank of America is known for using an AI-powered chatbot called Erica. Within the first 3 months of its launch, Erica’s services were used by 1 million of the bank’s customers.

  1. Algorithmic Trading – Algorithmic trading is all about data analysis and fast decision-making. These are the areas where AI thrives. Machine learning algorithms can easily analyze data irrespective of its size and density. These self-learning algorithms can detect patterns that are difficult to spot by a human. Based on the insights derived from the data, AI can execute trades automatically and faster than human traders.

Conclusion
The advancement in AI and machine learning has produced smart systems that can learn and adapt from data. The financial industry is leading the way with respect to the adoption of such AI-based systems with existing Fintech applications. These systems have brought automation to the most mundane financial tasks. Through predictive analysis, they can safeguard sensitive financial data by detecting fraud and mitigating risks. They also play a huge role in helping financial marketers enrich the customer experience and increase the ROI on their marketing spend.
The future of Fintech and the financial industry is thus bright and exciting, thanks to Artificial Intelligence.

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Great Learning Editorial Team
The Great Learning Editorial Staff includes a dynamic team of subject matter experts, instructors, and education professionals who combine their deep industry knowledge with innovative teaching methods. Their mission is to provide learners with the skills and insights needed to excel in their careers, whether through upskilling, reskilling, or transitioning into new fields.
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