Written by Nilesh Jahagirdar
The Indian government has a vision of achieving a $5 trillion economy and at the same time aims to make the digital economy worth $1 trillion by 2025, according to a report cited by the Institute of Banking Technology Development.
while inside Vuka In a world where no sector is secure (volatility, uncertainty, complexity, ambiguity), the banking industry has undergone a remarkable transformation due to the proliferation of digital technologies. Over the past decade, India has seen a wave of innovation driven by its advanced IT industry and the country's demographic strength, and with government efforts to digitize key aspects of the economy and support from global innovation, India has become one of the world's leading players. It has become the second largest digital ecosystem. Private sector and investments to stimulate internet use and access. the government,
Additionally, with the rapid evolution of banking apps and the rise of digital banking, financial institutions are increasingly leveraging machine learning (ML) to provide a seamless user experience and build a robust digital footprint.
It is imperative for banks to become AI-first.
There is no doubt that advances in the field of technology have taken the world by storm and emerged as a powerful tool to revolutionize the banking sector.
It is widely known that we are now in an era of AI-driven digital progress, driven by falling costs of storing and processing data, increasing accessibility and connectivity for all, and rapid advances in AI technologies. . These advances have the potential to greatly automate processes and, if implemented carefully, can often exceed human decision-making in terms of both speed and accuracy. The scope of value creation is immense across a variety of industries, with AI potentially creating $1 trillion in new value for banks annually.
ML, a subset of AI, can further help transform the way banking services are delivered and consumed by analyzing vast amounts of data and identifying patterns. ML algorithms also allow banks to provide personalized experiences to individuals' needs, strengthen security measures, and optimize marketing strategies. Another trend-setting subset of AI, Gen-AI, is the ability to analyze broad data sets, recognize complex patterns, and extract valuable insights that can change the way decisions are made. It offers countless benefits. Gen AI also plays a key role in fraud detection, risk assessment, and coordination of customer interactions, increasing efficiency and accuracy. Its applications span algorithmic trading, credit risk analysis, and the development of customer service chatbots, demonstrating its diverse and significant impact on digital banking practices.
Improving user experience with ML and Gen AI
Currently, the global banking market is $6.256 billion by 2032a huge jump from Valued at $865 million in 2022 With a compound annual growth rate (CAGR) expected to be 22.5% from 2023 to 2032, it says the financial sector is poised for revolutionary change with the introduction of generative AI.
Leveraging AI tools such as Gen AI also helped achieve productivity gains of 22% to 30%. However, the real transformation lies in the impact on the bottom line. Integrating AI with human efforts in sales, marketing, and customer care could generate an impressive 6% increase in new revenue streams within the next three years.
Through ML algorithms, banks can provide customized financial advice, suggest relevant products and services, and predict users' needs based on their transaction history and behavior. Additionally, when combined with a 24/7 AI-assisted chatbot that can respond to customer inquiries, provide account information, and assist with transactions, it improves user accessibility and convenience.
In a VUCA world, AI tools will be a game changer as their ability to detect anomalies in real time and the assistance of ML algorithms will help banks identify and mitigate fraud and protect customers' financial assets and sensitive information. brings about.
The need for a robust digital footprint
ML is almost essential for streamlining banking processes and improving customer engagement and retention. ML will ultimately help banks understand customer behavior and preferences through advanced data analysis of transaction history, spending patterns, and browsing habits, enabling them to offer customized services. will help you understand. Competitiveness.
obstacles to combat
A study conducted by National Business Research Institute and Narrative Science found that around 32% of financial service providers in India are already using AI technologies such as predictive analytics and voice recognition, leading to a We can see that the adoption of AI is progressing. Until that day. Banks like SBI, Bank of Baroda, HDFC, ICICI, and Yes Bank have already implemented AI to streamline their regular processes.
According to the survey, India has surpassed the global average of 79% in expectations for AI-human collaboration within the next two years with a staggering 83%, citing confidence in the superiority of AI. However, the same report also found that 77% of Indians agree that AI tools need to be properly created and/or integrated into banking services as they also come with challenges such as: I observed.
- Cost of training personnel
- Understand the importance of data standardization
- Different enforcement approaches
- user capacity
- Reading and decoding multiple languages
- Data protection and privacy issues
It also suffers from technical challenges such as data integration, model deployment, and scalability, which require careful consideration to ensure a smooth implementation.
But on the bright side, there are case studies demonstrating how large banks have successfully integrated ML into their apps. For example, Erica, Bank of America's virtual financial assistant, leverages ML algorithms to provide personalized insights to assist customers with financial management tasks and improve the overall user experience.
The road ahead
Looking ahead, the future of ML in digital banking holds exciting possibilities, from predictive analytics for credit risk assessment to natural language processing for customer support. By keeping pace with technological advances and embracing innovation, banks can develop new opportunities and gain an advantage in today's competitive environment.
By finding the right balance between effective physical strategies, existing technology, industry collaboration and the introduction of innovative technologies, a resilient banking sector can meet customer demands and lead the country into a new era. It is poised to contribute to financial stability.
(Author: Nilesh Jahagirdar, Co-Founder and VP of Marketing & Solutions) [x]cube LABS and the views expressed in this article are his own)
