By Bhuvan Rustagi COO & Co-founder, Per Annum
A young entrepreneur receives a notification that he has just been approved for a loan — the one he applied for just a day ago. Surprised, he taps into the app to find a personalised offer from his bank, tailored perfectly to his financial situation and with better rates than he’d ever seen. It wasn’t luck or coincidence. It was AI (artificial intelligence) working silently in the background, analyzing his spending habits, forecasting his needs, and offering him exactly what he needed. This is the new face of finance, where algorithms and machine learning redefine how we interact with money.
Welcome to the world of AI in fintech, where invisible code transforms everyday transactions into something magical — instant, personalised, and predictive while being secure. But how did we get here, and what lies ahead in this fast-evolving landscape? The integration of different technologies into finance gave rise to Fintech, which is worth $340.1 billion globally. With AI spearheading the Fintech revolution, the value of AI in Fintech is $44.08 billion, and it is expected to be $50 billion over the next few years. The Indian Fintech industry is also flourishing, strengthening its position as a global leader with a market value of $90 billion, while AI and GenAI are the focus for innovation among Fintech companies.
It is clear that the world of finance has come a long way from traditional banking to the era of AI dominance. Let’s take a closer look at how this revolutionary technology is transforming finance with unique solutions and services.
AI-powered Robo-advisors
Traditional wealth management relied on costly human financial advisors. Robo-advisors now offer a budget-friendly alternative using AI and algorithms for automated investment guidance. These platforms appeal to smaller investors, creating portfolios based on individual goals, risk tolerance, and timelines. They analyze vast financial data to inform investment choices, resulting in well-informed, impartial recommendations. Robo-advisors construct diverse asset mixes, typically including stocks and bonds, providing a fresh perspective on digital-age wealth management. This data-driven approach offers accessible, cost-effective investment solutions, challenging the traditional model of personalised but expensive human advisory services.
AI-driven fraud detection
Financial institutions face diverse fraud challenges, from identity theft to fund transfer scams. Manual analysis of countless daily transactions is impractical. AI-based systems are empowering Fintechs to analyze data, detect anomalies, and flag suspicious activities. AI is monitoring transactions, filtering spam, and identifying malware. It can recognise social engineering patterns and alert users to potential threats. While fraudsters also use AI for sophisticated scams, financial institutions can leverage AI to identify synthetic content and distinguish between trustworthy and untrustworthy information. AI’s advanced modeling techniques improve operational efficiency, automating repetitive tasks and allowing fraud analysts to focus on complex cyber threats.
Loan underwriting with AI
AI revolutionises credit underwriting by analysing diverse data points for lending decisions. Traditional personal loan reviews often take a week or more, involving multiple specialists. AI accelerates this process by automating document scanning and data gathering. Now, applications typically take minutes to complete, with approvals within two days. AI algorithms assess creditworthiness using traditional factors like income and credit history, alongside non-traditional sources. This comprehensive approach enables quicker, more informed lending decisions, reducing processing time and costs. Deloitte projects potential savings of up to $31 billion in underwriting and collection expenses by 2030, highlighting AI’s significant impact on the lending industry.
AI resolves customer queries
AI is transforming fintech customer service, enhancing retention and loyalty. It provides personalised, consistent experiences across channels, anticipating needs and offering value-driven recommendations. AI-powered chatbots handle common queries efficiently, allowing human agents to focus on complex issues. This technology enables 24/7 support across various platforms, meeting customer expectations for instant access. AI analytics predict customer needs based on financial history, transaction patterns, and life events, enabling targeted, timely offers. By improving engagement and satisfaction, AI-driven customer service not only streamlines operations but also leads to positive word-of-mouth referrals.
Protections against security breaches
The financial sector faces significant cybersecurity threats, with average data breach costs reaching $5.9 million in 2023. However, organisations extensively using AI in security protocols experienced $1.76 million lower breach costs and resolved incidents 108 days faster. This showcases how AI systems continuously monitor network activity, swiftly detecting anomalies and preventing data breaches. They enable advanced biometric authentication and, combined with IoT, enhance physical security in financial institutions. This proactive approach safeguards sensitive information, maintains customer trust, and protects against various threats, from digital breaches to physical robberies.
The future of AI in fintech
AI has become a game-changer in fintech, transforming operations, customer experiences, and innovation. It’s reshaping financial services through automated data processing, advanced credit scoring, algorithmic trading, and personalised offerings. To stay competitive, companies must embrace AI, but effective implementation requires deep expertise in both technology and finance.
Looking ahead, AI in fintech is poised for exponential growth. We can expect more sophisticated predictive analytics, hyper-personalised financial products, and AI-driven risk management systems. Quantum computing may further revolutionise AI capabilities in areas like cryptography and complex financial modelling. However, as AI becomes more prevalent, addressing ethical concerns and ensuring responsible AI use will be crucial. The future of fintech will likely see a seamless blend of AI and human expertise, creating more efficient, secure, and inclusive financial ecosystems.
