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CEO’s Corner

Reaping the Benefits: The Endless Possibilities for AI Transformation

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CEO’s Corner Series: Unlocking Intelligent Banking: A Deep Dive into the Impact of AI on Banking and Payments

About this series:

In this exclusive series, we will explore the world of Artificial Intelligence (AI) within banking and payments. This series will be a deep dive into how AI is transforming financial experiences, from fraud prevention and hyper-personalization to streamlined transactions and intelligent financial planning. We’ll also explore the challenges of AI adoption – the cost of implementation, identifying the right entry point, navigating a limited talent pool, and achieving faster turnaround times. The era of intelligent banking and payments is upon us. Join me and explore the strategies to make AI work for you.

With evolving customer expectations and rising demand for hyper-personalized experiences, frictionless payments, and real-time insights, AI has transitioned from a futuristic concept to a strategic enabler for staying competitive and capturing new customers and markets. However, navigating the vast potential of AI can be a challenge. Simply upgrading to a cutting-edge technology for existing problems won’t guarantee results. For successful implementation and tangible ROI, financial institutions need to understand their specific needs and identify the value drivers within the organization.

In the third edition of our exclusive blog series, we will expand our horizon to identify and discuss critical use cases that have evolved alongside AI’s rise in the financial services industry.

A 2023 ISG study surveyed 121 decision-makers (including 26% at the board level) from the world’s top banks and identified operational efficiency and customer experience as the top priorities for AI implementation. The survey also revealed that 92% of respondents are already using or planning to use AI by 2025 to combat security threats and fraud.

Scaling AI in the World’s Top Banks

Source: ISG Banking Industry Study, 2023

Implementing AI in banking and payments goes beyond security and fraud detection. A good read of the 2022 annual report of JPMorgan Chase & Co. gives a clear understanding of the potential extent of AI’s impact on the financial services industry. Per this report, the bank was actively working on 300 AI use cases in areas like risk management, customer acquisition, marketing, customer experience, and fraud prevention.

Given the rapid adoption of AI, it’s crucial to categorize these use cases and explore how they can translate into a sustainable competitive advantage. For ease of understanding, we will continue with the categorization system used in the second blog of this series for our analysis – Automation, Prediction, and Generation.

Automation: Unleashing Efficiency with Precision

One of the areas with the most potential for AI applications is automation. Repetitive, rule-based tasks that require a significant number of human resources are among the easiest targets for AI intervention. According to a McKinsey report, up to 80% of retail bank transactions can be automated using AI. Similarly, Accenture research predicts that employees in the financial services industry can achieve a 30% boost in productivity by 2028 through AI automation.

Here are some of the potential use cases within automation:

  • Algorithmic Trading: Investment banks leverage complex machine learning models to identify and execute optimal trades precisely. The financial markets offer a wealth of data that allows AI systems to train effectively and build accurate models. These models can help traders in making informed decisions in real-time. A Boston Consulting Group report highlights that AI-assisted trading can reduce operational costs by up to 25% and increase portfolio returns by 1.5%.
  • AI-powered Payment Routing: Machine learning can replace rule-based configurations, suggesting the most efficient payment routing for retail and commercial transactions across various payment methods. This applies to account-to-account payments routed through RTP, RTGS, ACH, and SWIFT. It can also be applied to payment processors, acquirers, PSPs, and alternate payment methods.

    Here are some parameters that can be configured to optimize payment routing: transaction cost, payment processor failure rate, transaction amount, transaction capture device, and chargeback history.

Prediction: Data-Based Insights to Power Innovation and Risk Management

AI is being widely used for automation. However, the true potential of this disruptive technology lies in processing massive volumes of data to offer valuable insights. This is what can make AI powerful in achieving business goals. AI-powered predictive analytics can help financial organizations identify customer needs and respond with innovative product or service offerings. By analyzing transaction data, AI solutions can deliver hyper-personalized financial products, such as tailored investment strategies, customized insurance plans, and timely reminders to pay installments. Some of the popular applications in this category are:

  • Robo-advisory Services: A 2022 study by Forrester revealed that 72% of customers value products more when tailored to their personal needs. Powered by AI, robo-advisory services can democratize wealth management by offering personalized financial guidance to a broader customer base. This will enable FIs to expand their reach to millions of underserved customers. We have witnessed phenomenal progress in this segment and will continue to see newer applications for this use case.
  • Risk Management: FIs are deploying AI solutions to assess loan applications and mitigate credit default risk. These solutions eliminate data inaccuracies and provide a risk score based on multiple parameters. According to a research paper published by IMF, AI-powered risk management leads to better credit decisioning and can reduce loan defaults by up to 25%.

Fraud Detection: A survey conducted by Mastercard in 2022 found that the banking and payments industry is highly optimistic about AI’s ability to detect fraud schemes with high accuracy. Unlike traditional AML models, AI-based fraud detection solutions are more resilient and evolve at a faster pace. These AI models score payments based on several risk factors: location, transaction amounts, recipients, countries of origin, and past behavior. This helps in the near-accurate identification of high-risk payments and ensures customer protection.

Generation: A New Era of AI-Driven Innovation

Beyond automation and prediction, GenAI unlocks entirely new service possibilities. Imagine personalized loan or insurance products tailored in real-time using AI algorithms to meet each customer’s unique needs. You must have interacted with an AI-powered chatbot hosted within your mobile banking application. These chatbots are revolutionizing customer service by providing 24/7 support and resolving issues with unmatched efficiency. Financial organizations can also deploy these chatbots to empower internal teams by automating routine tasks and freeing them to focus on building stronger customer relationships.

According to a 2023 report by McKinsey & Co, generative AI could add value between $200 billion and $340 billion, representing 9%-15% of banks’ operating profits, if fully implemented. GenAI can assist with software engineering tasks, streamlining development processes and accelerating innovation. As generative AI continues to evolve, we can expect even more transformative applications to emerge.

The Future is Intelligent

The financial services landscape is constantly evolving. For organizations trying to ride the digital transformation wave, agility is the need of the hour. By embracing AI as an enabler for value creation, FIs can stay competitive and focus on what matters the most – business innovation, process efficiency, and customer-centricity. This isn’t just about technology adoption; it’s about harnessing the power of intelligence to redefine the very essence of how we serve our customers.

As we move into the ever-changing landscape of AI, future editions of this series will explore how small financial institutions can better adopt AI and drive ROI significantly in the field. Stay tuned!

Opus Official

Praveen TM

Chief Executive Officer, Opus


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Opus Official

Praveen TM is a highly accomplished global payments leader with over 20 years of experience. A veteran in the payments industry, Praveen has immense wealth of insights to share in payments innovations, emerging technologies, FinTech, and financial services.

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