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AI: The Future of Fintech - Part 2

Updated: Nov 27, 2023

Part 2: AI Applications in Fintech

New and emerging use cases for AI are expected to transform the fintech industry in the coming years and decades. And savvy companies and business leaders stand to benefit.

User Behavior Analysis

With AI, users can analyze their spending habits and get forecasts of their account balances over time. AI can also help classify spending and offer filters to see what changes in financial behavior can lead to healthier money management. Additionally, fintech service providers can rely on recommendations from predictive analytics to cross-sell financial products such as loans, financial health monitoring, financial goal reporting, and more to customers exactly when they need them. Overall, AI-powered apps can provide instant personalized financial advice to help users achieve their financial goals and track their income and expenses more effectively.

Image 3 User behavior analysis focuses on what a user is doing, how they are doing it, and for how long

It is mainly thanks to AI-enabled fintech innovations that this personalization is possible. As fintech solutions gain prevalence, customers’ purchasing behavior has changed. Today, users focus more on the customer experience rather than just the movement of funds. Therefore, technology-oriented and experience-driven solutions have emerged as the most convenient and preferred options for financial transactions.

To provide the best customer experience possible, service providers must know as much as possible about their customers. Obtaining this information using traditional methods is difficult. However, with the power of AI, fintech has the potential to be far more effective at this than conventional banking. According to Forbes, several companies implementing AI and ML have increased customer satisfaction by more than 10%. In addition, analyzing customer behavior with AI capabilities could save a significant amount of time compared to human employees by automating all routine tasks.

Anomaly and Fraud Detection

Whether it is banks, enterprises, or financial institutions, all work hard, employing every means at their disposal to prevent fraud. Artificial intelligence provides a viable solution. It blocks access to an account immediately if it detects potential fraud. Using AI to detect fraudulent behavior has significantly enhanced internal security and simplified banking operations.

Artificial Intelligence has emerged as an essential tool for avoiding financial crimes due to its increased efficiency. AI can analyze vast numbers of transactions to uncover trends and prevent fraud in real-time. When fraud is suspected, AI models may reject transactions altogether, flag them for further investigation, and rate the likelihood of fraud. Since AI can handle most of the manual work, investigators can focus their efforts on the most promising cases.

Image 4 Spotting anomalies quickly diminish threats to the software ecosystem

An anomaly is an observation or item that does not conform to the regular or common patterns found in data. In financial data, these outliers are essential because they indicate potential business, control failures, or opportunities. Additionally, they often point to critical areas that need further scrutiny.

The never-ending cyber onslaughts of hackers cost consumers and businesses millions of dollars annually. However, the costs of investigating and retrieving stolen funds are billions more. Money-handling organizations must incorporate effective fraud-prevention techniques into their plans to protect themselves and their clients. Using artificial intelligence for anomaly detection is a powerful strategy for detecting fraudulent transactions and behaviors.


In fintech, AI chatbots are revolutionizing how banking institutions approach customer experience. For a fintech provider, customer service is just as important as the products or services it sells. Businesses can use AI to improve customer experience and customer service in many different ways. For example, AI-powered chatbots minimize the workload placed on call centers and tackle routine user problems. In addition, with the help of chatbots, businesses can grow their customer network. For example, a chatbot can instantly display the user’s credit and search history, remind them of bill payments, inform them of duplicate charges, and hint at their financial health.

Image 5 AI chatbots are constantly learning from their conversations

Fintech users benefit from lower tech barriers and less conflict with chatbots. Chatbots can be trained to detect human behavior and understand consumer needs. Then, with a few simple questions, they can offer personalized recommendations based on the user’s answers, making engagement more proactive and rewarding.

Because a chatbot is available 24X7, it attracts more customers to the website, especially those who want to search for services or products without having to depend on another person. By collecting consumer information via chatbots, companies can identify a consumer’s needs and provide appropriate solutions. By making information and help readily available, chatbots make customers feel more connected and loyal.

Risk Score Profiling

With technology ushering in a new era and driving transformative changes in every industry, corporations and financial institutions are redefining their business models and operations using automation, robotics, and AI.

Digital transformations increase consumer choice and access and simultaneously introduce many unknown risks. With an ever-increasing range of threats in digital environments, financial organizations will need a robust digital risk control strategy to succeed.

Image 6 AI processes massive amounts of data quickly to create a more holistic picture of risk

Risk scoring is essential to the manager’s routine when categorizing clients. Instead, development teams can train artificial neural networks to analyze a user’s historical data and classify them based on their risk profile. In addition, AI can provide clients with suitable service recommendations matching their risk levels.


Image 7 RegTech offers a cost-effective solution to meet complex, ever-evolving regulatory challenges

Regulatory technology simplifies compliance management and helps minimize regulatory risks. In the current banking environment, banks rely on inadequate legacy solutions to meet the stringent requirements increasingly demanded by regulators around the globe. Through RegTech, banks can meet these requirements without completely overhauling their existing business models.

RegTech has established a solid foundation within the fintech ecosystem to address this challenge. These solutions focus on new, complex regulations, litigation, and regulatory remediation areas while ensuring an overall reduction in cost compliance. Businesses around the world provide a wide range of compliance solutions and services. Most of these RegTech solutions are available as open APIs and SaaS.

RegTech uses artificial intelligence to manage regulatory compliance. It includes the identification of clients, the monitoring of transactions, the analysis of regulatory compliance, and the reporting of results. For financial service companies, compliance regulation is an unavoidable pain. Every company transaction must be conducted within the existing rules while also considering what’s to come. RegTech applications using AI and ML help monitor and report regulatory-compliant transactions much faster than traditional methods.

Until AI, monitoring and reporting were extraordinarily complex for companies operating across multiple jurisdictions. With the increasing use of AI in this domain, regulatory updates can be sent in real-time, and companies are alerted to the relevant policies and rules that need to be followed. With such capabilities, the company will be able to assess downstream business impacts rapidly and make informed decisions.
Image 8 Various features of AI are used by different fintech companies around the world to make operations safer and more efficient

Various AI solutions are being developed to resolve business process problems, ranging from human augmentation to process improvements to forecasting and planning. These solutions enable superior decisions and outcomes. Additionally, advancements in voice, speech, and vision technologies and multi-modal AI solutions are revolutionizing how humans operate.

fintech uses AI for lending, decision-making, customer support, fraud detection, credit risk assessment, insurance, wealth management, and more. A modern fintech company also uses AI to enhance efficiency, improve precision levels, and speed up query processing.

Innovation in fintech using AI leads to better customer service, faster and more secure services, and a wider global reach. Undoubtedly, financial markets will be dominated by AI-driven innovation for a long time!

About Us

Based in the US with offices in India and Singapore, Copperpod Digital is a next-generation Digi-Tech Transformation Group that enables businesses to power purposeful brand-consumer gravity. A division of Copperpod Digital, Metamaxx enables companies and brands to build web3-powered digital offerings. Together, our practices emphasize digital experimentation and scaling up at speed, essential for achieving continuous delight and intimacy between businesses, their brands, and their consumers.
Our Artificial Intelligence capabilities help clients consistently run, maintain and scale AI and Machine Learning solutions from prototype to production. In addition to deepening customer relationships, we help our clients find new revenue sources and increase customer bases. Our team of experts guides clients on their AI journey and accelerates the implementation of winning solutions and strategies.
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