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The baking industry has evolved a lot in the last 50 years. Let’s look back to the evolution of banking in technology. We see a significant shift from first e-payment to commercial computer tablets, P2P transfer to quantum computing, and mobile banking to Google Wallet. Now, Gen AI in banking is the most influential development in the banking sector.
Generative AI in Banking industry brings many advantages, including task automation, improved operational efficiency, AI-powered customer service, fraud prevention, and compliance with advanced regulations. According to McKinsey Global Institute (MGI) estimation, across the global banking sector, gen AI could add between $200 billion and $340 billion in value annually, which is 2.8 to 4.7 percent of total industry revenues.
Banks are unlocking the tremendous value of Gen AI through strategic planning and apt Generative AI banking use cases. This blog will shed light on the significance of Gen AI in the banking industry, use cases, benefits, and future trends in generative AI banking, followed by how generative AI development services can help maximize the Generative AI usage. Let’s explore!
Table of Contents
Generative AI for banking means leveraging Generative AI technology to revolutionize the banking sector with process automation, chatbot-led customer support, risk score generation, hyper-personalization, LLM models, and intelligent recommendations. It’s improving banking services and opening new avenues to gain customers’ attention.
Generative AI is the unparalleled match for advanced banking digital needs with its unmatched potential. The following use cases will highlight how the transformative force of Generative AI translates into various benefits with different Generative AI banking use cases. They are-
AI-driven chatbot customer service is one of the latest AI trends that’s used in almost every industry vertical. The banking industry is no different. NLP-based chatbots offer human customer support services 24/7, including answering customer queries, updating profile information, executing transfers, and providing balance updates.
They provide virtual assistance in complex queries, such as letting customers know how much mortgage they can get from banks with a quick evaluation of annual salary, ongoing loans, credit score, and interest rates. It enables conversationalizing complex inquiries humanly. Fargo implemented Gen AI virtual assistant, which handled more than 20 million transactions to answer customers’ banking queries.
Fraud detection and prevention is one of the famous Generative AI use cases that every sector needs. Generative AI capabilities help banks proactively identify and fix vulnerabilities before they worsen the system. Fraudulent activities such as unusual spending patterns, transactions from odd locations, or detection of new device usage by Gen AI help discover transaction anomalies.
Gen AI techniques train fraud detection models, ensuring the algorithms can automatically track and flag potential breaches. Mastercard uses Gen AI technology to help banks detect fraud at scale by training fraud detection models with more than 125 million transactions.
Risk management is vital in preventing financial disasters and ensuring banks operate smoothly. Gen AI algorithms trained with data can identify financial risks and send alerts to the banks so that losses are mitigated or avoided. Similarly, relying on credit score calculation using traditional ways to determine people’s creditworthiness was tedious. So, banks have started embracing Gen AI to analyze massive data from disparate sources and provide credit scores for loan applicants.
Massive paperwork involved in banking services is time-consuming and challenging to deal with. Further sorting through papers, required analysis, and finalizing the documents with bank stamps is quite a task that wastes a lot of valuable time for the bank staff. Gen AI models reduce operational cost and time by sifting through large volumes of documents, extracting essential data, and providing a summary in a fraction of a second.
Banks often look for lucrative opportunities with minimum chances of losses. It requires analyzing market trends, economic indicators, and financial market data to launch new investment options. The banks considerably leverage generative AI tools to assist them in evaluating new strategies’ effectiveness and the creation of strategic financial plans that benefit in the long run.
Similar to every industry vertical, the banking sector must invest in targeted marketing that helps attract customers and maximize the outcomes. It requires investing in Gen AI implementation that analyzes customers’ online behavior and preferences to create different buyer personas.
It further helps create marketing campaigns for different customer groups and track campaigns’ performance (Conversion and customer satisfaction) to evolve a marketing strategy that improves the results. Personalized marketing campaigns with customized email responses, automated query handling, and follow-ups engage customers in specific bank services.
Bank customers often find it challenging to decide which investment option is good and which one will help them achieve their financial goals. Banks can also provide intelligent suggestions using Generative AI technology.
The AI models provide human experts-like financial advice based on market trends analysis of different investment options, customers’ income, and spending habits. It empowers data-driven decisions and optimizes portfolio management.
Thanks to AI use cases, banks can provide greater convenience, efficiency, and security. Gen AI brings significant shifts with several use cases, such as extra cherries on the cake. Explore Gen AI benefits in banking helping banks to get to the table.
Implementing Gen AI in banking to create AI-powered chatbots. These bots can handle customer queries as a virtual agent available 24/7. Also, they can convert customer call conversations into data, search data, and provide contextual answers promptly that delight customers. The reduced waiting time and improved interaction with banks result in improved customer experience.
Manual processes often include errors that hamper bank operations; instead, Gen AI technology automates repetitive tasks and scales operations with optimal resource utilization, enabling banks to deliver great value to the customers.
Gen AI allows banks to improve security and protect customers’ data by continuously monitoring and analyzing online threats. The technology helps spot threats before they make the bank system vulnerable.
Task automation, enhanced operational efficiency, reduced errors, and personalized services save substantial costs for banks. Simultaneously, efficient AI-driven customer services, tailored marketing strategies, and custom financial advice improve the chances of conversion and increase sales and ROI.
Generative AI in banking is now widespread across the globe in the form of various Gen AI use cases. The new trend we expect to see in the Gen AI initiative is customer-centered AI integration. Banks are expected to embrace the emotional experience mindset to streamline the customer journey, integrate customer-centricity at all levels, and adopt a human-centered culture to deliver unparalleled customer value.
Gen AI impact will be enhanced with repurposed ChatGPT use cases, including bank operations. Personalization level will be improved, surpassing customers’ expectations. Gen AI technological leap will turn banks to AI-first. For this, we expect banks to hire AI developers to stay up-to-date with the evolution of Gen AI.
The banking industry is heavily regulated, and Generative AI use cases are transforming the banks like no other. Considering integrating Gen AI services in banking strategy is the best bet to place that streamline banking business operations. However, harnessing the value of Gen AI technology requires the expertise of a Generative AI development Partner with Generative AI development service to maximize ROI.
That’s where Prismterics team’s experience with Gen AI solution development and successful implementation will help you. Gen AI experts are avid at harnessing and integrating Gen AI capabilities into banking operations and processes. Browse extra benefits with Prismetrics Gen AI services that help business in achieving Gen AI initiative.
Gen AI supersedes traditional AI implementation by addressing challenges that AI systems fail to overcome. A growing number of Generative AI use cases in the banking sector showcase its immense impact across various banking aspects. Leading banking players incorporating Gen AI is evidence of the value technology adds to the banking business and their customers. It’s high time to seize the chance and go the extra mile with Gen AI applications. Let’s shape the future of banking with Gen AI.
Banks can implement Gen AI following a strategic process:
Define priorities and set goals to meet using Gen AI.
Modernize infrastructure, ensuring Gen AI seamlessly works.
Hire an AI engineer and start with a pilot project.
Create strong controls to build secure, scalable applications.
Generative AI is used in banks to analyze increasing data and provide insights to make informed decisions, automate repetitive tasks, and optimize existing operations.
Gen AI poses data privacy, regulatory concerns, legacy issues, ethical challenges, and change management concerns when leveraged in the finance and banking industry.
Gen AI is transforming the banking industry with various use cases such as personalized financial advice, fraud detection, changing risk management and credit scoring, enhancing customer service, creating customized marketing campaigns, KYC verification automation, and regulatory compliance monitoring.
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