By Karan Mehta, Co-founder and CTO, RING
Fintech companies have brought about a significant shift in the financial industry by embracing advanced technologies like Artificial Intelligence (AI) and Machine Learning (ML). The market for AI in Fintech grew from $9.15 billion in 2022 to $11.59 billion in 2023 at a compound annual growth rate (CAGR) of 26.8%. (Source) This clearly shows AI and ML in Fintech have fundamentally changed the banking sector by introducing a new level of security, and efficiency. Through the utilisation of cutting-edge technologies, fintech firms are actively developing customer-centric solutions that cater to the evolving needs of users, paving the way for innovation, streamlined operations, and reshaping the financial landscape.
Utilising AI for Personalised Services: Fintech companies recognise the significance of providing tailored experiences to their customers. By utilising customer data encompassing transaction history, spending patterns, and demographic information, these firms acquire profound insights into individual preferences and behaviors. Armed with this knowledge, fintech companies deliver personalised product recommendations, customised investment strategies, and targeted promotions that align with each customer’s distinct requirements. By leveraging extensive data analysis, powered by AI, these systems generate remarkably precise predictions and recommendations. For instance, AI algorithms can analyse customer spending habits and provide real-time budgeting suggestions, helping individuals manage their finances more effectively.
Streamlining Processes and Enhancing Efficiency: AI and ML are revolutionising financial processes, driving improvements in speed, efficiency, and accuracy while minimising errors. In the past, loan underwriting and risk assessment procedures relied heavily on extensive paperwork and manual evaluations. However, fintech companies are reshaping these operations by harnessing the power of customer data to automate decision-making. By analysing customer information, including credit history, income, and employment records, fintech firms employ AI-driven algorithms to assess creditworthiness swiftly and accurately. This automated underwriting process significantly reduces the time needed for loan approvals, allowing customers to access funds promptly.
Real-time Fraud Detection and Prevention: AI algorithms detect patterns and anomalies in financial transactions, helping identify potential fraud or money laundering activities in real time. By leveraging these technologies, fintechs are building robust security systems that safeguard customer information and provide enhanced protection against cyber threats.
Driving Financial Inclusion and Accessibility: AI and ML are instrumental in driving financial inclusion by broadening access to financial services for underserved populations.
Traditional financial institutions typically rely on traditional credit scoring models that tend to exclude individuals with limited credit histories. In contrast, fintech companies utilise alternative data sources and ML algorithms to evaluate creditworthiness based on various factors such as utility bill payments, mobile phone usage, and social media behavior. This approach allows them to extend credit to previously unbanked or underbanked individuals.
Optimising Customer Service and Support: AI-powered chatbots and virtual assistants provide a convenient channel for customers to access financial information, seek advice, and perform transactions. These virtual assistants can assist users in multiple languages, overcoming language barriers and ensuring accessibility for diverse populations. Moreover, ML models enable chatbots to improve over time by learning from past interactions, ensuring more accurate and helpful responses.
Overcoming Challenges and Ethical Considerations
While AI/ML offers tremendous potential, fintechs must navigate challenges and ethical
considerations. Ensuring data privacy, transparency, and compliance with regulations is crucial. Fintechs should prioritise ethical AI practices, including fairness, accountability, and explainability, to prevent biases and discriminatory outcomes. Regular monitoring and auditing of AI models are necessary to address potential risks.
The new-age technologies have given fintechs the ability to analyse massive amounts of data and gain valuable insights. AI and ML have empowered fintech companies to build trust, deliver exceptional experiences, and unlock the transformative power of customer insights in the pursuit of financial inclusion and improved financial well-being for all.
