Some of the most cutting-edge, effective, and secure solutions in the financial services industry today have emerged as a result of the development and integration of artificial intelligence, machine learning, and data science in technology automation. These technologies have affected and enhanced operational capacities across industries, kicking off a period of better functioning supported by the expansion of reliable information and data availability.
The financial sector has been significantly impacted by this technological transformation, which has seen the rise of multiple firms using AI and data science to forecast cash flow events, determine creditworthiness, and identify fraud. In order to gain a competitive edge, startups are adopting AI to improve data-driven decisions, automate repetitive operations, increase profitability directly through effective targeting, and do much more. As a result, we have achieved substantial progress towards financial inclusion and have been able to reach a larger proportion of the formerly unserviced population. Additionally, it is anticipated that by 2024, global spending on AI would exceed $110 billion, nearly doubling the amount spent in 2020.
Better Lending
Credit scoring is an essential use of AI in the finance sector. AI is being used by big banks, fintechs, and NBFCs to streamline operations and make accurate borrower assessments. To determine a customer’s creditworthiness, AI and ML use sophisticated classification algorithms using a variety of explanatory variables, including demographic information, income, savings, transaction history, historical credit history, their digital footprint, and more. These technologies enable borrowers without significant credit histories to access capital and demonstrate their ability to repay loans, giving institutions the added benefit of unbiased decision-making.
Trading Using Advanced Algorithms
The application of AI methods like probabilistic logic, deep learning, and evolutionary computing in algorithmic trading is a fascinating trend. These strategies are enhancing traders’ prediction abilities by enabling them to plan and execute deals in a methodical manner. AI-systems are also assisting traders in tracking risk exposures, adjusting or exiting the position according to the user’s requirements totally automatically, doing so without requiring any human involvement. Additionally, AI and ML systems offer traders competitive pricing, liquidity management, optimization, and streamline execution, and NLP techniques used in AI-systems enable traders to precisely discern attitudes from sources such as Twitter, Reddit, news articles, etc.
Avoiding fraud
Machine learning algorithms come in a wide variety, and many of them are made to stop fraudulent transactions and spot irregularities. The conventional ways of preventing fraud used sets of hardcoded rules created by subject matter experts, which may later be found and abused by fraudsters. A more secure and protected system that can be utilised to discover anomalies and trigger alerts is made possible by AI-based solutions that can change over time and react to new patterns found in transaction data, such as past behaviour, location, spending patterns, and much more.
Banking Experiences That Are Customized
Banking institutions are utilising chatbots, which have grown in popularity over the past two years, as well as cutting-edge NLP and AI techniques to better understand the demands of their consumers. Banking organisations are also using a large quantity of data to analyse how people spend their money and then give them individualised financial advice to help them reach their financial objectives. These include advice on how to cut monthly expenses, foresee future recurrent transfers, and much more. The usage of AI and ML offers countless opportunities to enhance client experiences.
Automation of Process
One of the most important benefits that AI has to offer is automation. AI-based systems can simplify complex tasks like extracting information from documents, digitising them, and processing forms, while optical character recognition can greatly improve the efficiency of lengthy procedures. The advantages of adopting AI-systems can significantly improve financial institutions’ regulatory, supervisory, and oversight capabilities.
Thus, AI, ML, and data science are giving the financial sector a fresh level of robustness and resilience, enabling them to lower the cost of credit underwriting, increase the complexity of algorithmic trading, and provide secure, effective, and transparent methods of operation. The use of such cutting-edge technology is increasing the nation’s potential for financial inclusion, opening up several avenues for citizens to achieve financial independence and raising the standard of goods and services on offer.
