Banking
How Artificial Intelligence is Transforming Banking
Published by Jessica Weisman-Pitts
Posted on January 23, 2023
4 min readLast updated: February 2, 2026
Global Banking & Finance Review®
Company
Published by Jessica Weisman-Pitts
Posted on January 23, 2023
4 min readLast updated: February 2, 2026
By Ankur Rawat, Director, Products and Solutions, Banking and Financial Services, Newgen Software
By Ankur Rawat, Director, Products and Solutions, Banking and Financial Services, Newgen Software
Banking has transformed over the years. It has come a long way from unorganized peer-to-peer banking to organized branch-based banking, and now digital banking with virtually connected branches, devices, and customers.
With digital banking, banks’ focus has shifted to delivering a superior customer experience, and new-age technologies have emerged as key enablers to achieve it. Artificial intelligence (AI) has surfaced as a promising technology, helping banks meet customer expectations and stay future-ready.
Decoding the AI Disruption
AI optimizes business processes by adding intelligence and eliminating or reducing human effort. In today’s digital age, AI is one of the most sought-after capabilities for global enterprises, and the banking sector is no exception. Banks are increasingly leveraging AI to deliver a seamless customer experience, augment the efforts of their workforce, and drive greater revenue.
Leading analysts highly rate AI for banks to gain a competitive advantage and thrive in the market. Per Mckinsey, “to thrive in the AI-powered digital age, banks will need an AI-and-analytics capability stack that delivers intelligent, personalized solutions and distinctive experiences at scale in real-time.”[1]
AI Leading the Banking Transformation
Here are the four ways how AI is empowering banks to provide best-in-class services and streamline business operations:
Decisions like loan disbursal and allocation of credit limits are critical for banks’ financial health and sustainability. With the help of AI, banks can enable intelligent and automated loan underwriting and credit analysis. AI-based credit assessment tools consider applicants based on financial profile, credit history, and account conduct. Rules-based engines augmented with AI for loan underwriting and credit services can empower banks to make more accurate and informed disbursal-related decisions. Banks can significantly improve their scalability, profitability, and fiscal sustainability through such solutions.
Personalization is the key to customer acquisition and retention in most industries today. Banks can leverage AI in tandem with data analytics to deliver customized offerings. For this, insights are derived from different customer journeys, financial profiles, and browsing patterns. Banks later leverage these insights to provide customized and contextual offers for up-selling and cross-selling to existing customers and generate greater revenue. Banks can also target prospects through such offerings to boost their propensity of becoming customers, thereby improving conversion rates and acquisition.
One of the most important use cases of AI in banking is enabling personal identity verification and processing of documents. As exclaimed by Deloitte, many organizations are devoting more financial and human resources to deploying intelligent document processing capabilities. The market is expected to grow 70-80 percent over the next two years to US $1.1 billion.[2] Using AI, banks can verify the authenticity of application documents and ensure accurate processing. Moreover, AI-based facial recognition tools can aid in personal identity verification and help prevent fraud. With a reliable digital identity authentication capability, banks can simplify and accelerate the customer onboarding process and eliminate the hassle of physical identity verification and documentation.
Banks can significantly enhance customer experience by leveraging AI at multiple interaction points. Mapping trends from multiple customer journeys can help develop and update AI-enabled bots and virtual assistants for providing personalized solutions. With such AI-based self-service tools, customers have an option to raise queries anytime, anywhere. This can ensure a high success rate of queries resolution. Furthermore, insights derived from such engagements can help the agents in the back-end to better assist customers and quickly resolve complex queries.
To Conclude
AI has made a strong case for itself in the financial industry by driving banks’ profitability and revenue growth today. In a PwC survey of US companies, 40 percent of banking and capital markets (BCM) respondents cited revenue growth as the top goal of their AI strategy.[3] The onus lies on banks to push their AI adoption initiatives to grow their customer base, increase revenue, enhance customer experience, and ensure sustainability to thrive in the digital age.
[1]building-the-ai-bank-of-the-future.pdf (mckinsey.com)
[2]https://www2.deloitte.com/content/dam/Deloitte/uk/Documents/consultancy/deloitte-uk-intelligent-document-processing-report.pdf
Artificial Intelligence (AI) refers to the simulation of human intelligence in machines that are programmed to think and learn like humans, enabling them to perform tasks such as problem-solving and decision-making.
Credit analysis is the process of evaluating a borrower's creditworthiness, assessing their ability to repay loans based on their financial history, income, and other relevant factors.
Personalized banking involves tailoring financial services and products to meet the specific needs and preferences of individual customers, often using data analytics and AI to enhance customer experience.
Identity verification is the process of confirming a person's identity, often through documents or biometric data, to prevent fraud and ensure security in financial transactions.
Contextual customer engagement refers to interacting with customers in a way that is relevant to their current situation or needs, often facilitated by data analytics and AI technologies.
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