The financial industry has been encountering a multitude of challenges in recent years, particularly in the aftermath of the Spring Bank Run of 2023, due to economic uncertainty and the rapid pace of technological change. Presently, banks are prioritizing liquidity management, enterprise protection, operational resiliency, and sustainability as the ultimate goals for balanced risk management.
In order to address these risks, financial institutions are increasingly turning to artificial intelligence (AI) to analyze decades of accumulated data and reevaluate business processes. By becoming an AI-first financial institution, they can navigate challenges and become trusted orchestrators of the economy by exploring innovative business models with open finance across the ecosystem.
Advancements in AI and generative AI have significantly influenced institutions such as JP Morgan, Deutsche Bank, and Morgan Stanley, where these technologies have been leveraged to enhance digital, data, and cloud infrastructure. Generative AI has found diverse applications, from streamlining software development to offering personalized financial advice and recommendations.
While some institutions have made early investments in AI, going AI-first is becoming an imperative for growth and efficiency in the industry. Not only does it have a direct bearing on all connected stakeholders, but it also enables faster, smarter customer decisions, amplifies employee potential, and distributes higher capital to low-risk shareholders.
So, what does an AI-first financial institution look like?
An AI-first financial institution fully leverages data and AI to automate tasks, streamline workflows, enhance products and services, and differentiate against peers with utmost efficiency and ethical decision-making. This value-based approach can leverage the existing power of digital and cloud to evolve quickly with complete transparency and auditability, especially in response to changing stakeholder expectations.
An AI-first strategy focuses on three key layers: foundation, core, and growth.
The foundation involves handling and interpreting data volumes, which includes modernizing technology, infrastructure, and AI operations, managing talent and change, and making the enterprise data-ready for AI. The primary challenge that executives face is usable data, so institutions must establish an effective data estate to ensure that data assets are available, accessible, discoverable, and of high quality.
The core layer supports back and middle office operations, including credit scoring, regulatory compliance, customer service, and fraud detection. AI integration across operations drives efficiency and ‘autonomous automation,’ while AI-driven systems assess credit, market, and operational risks and are adept at tracking regulatory changes and scrutinizing customer data.
The growth layer augments front-office operations by personalizing sales and marketing at scale, deepening client relationships, and improving portfolio management and product design. AI-based products can use synthetic customers – human-like avatars with personality and knowledge – to interact with prospects and help employees learn about product features, benefits, and services, and answer customer questions accurately and confidently.
However, privacy, security, and ethical implications must be considered when integrating AI, with human oversight in high-risk use cases. Responsible design principles should guide AI integration to help financial institutions achieve higher margins, create new revenue streams, design better products, and become more productive.
Lastly, talent is key. To be truly an AI-first financial institution, the culture around embracing AI and future innovations needs to be encouraged across organizations. New roles will emerge, and AI fosters a culture of continuous learning and adaptability, making institutions agile and adaptable to future advances as this new era unfolds.
In conclusion, the era of AI-first financial institutions is upon us, and institutions that embrace this transformation will be better equipped to navigate the challenges of the banking industry in the coming years. Through leveraging AI and generative AI, financial institutions can enhance their operations, improve customer experiences, and drive growth in an ever-changing landscape.
About the Author: Bal Shukla, an AI evangelist and Forbes Council Member, leads AI and business transformation for the financial services segment at Infosys. With over 20 years of experience, he drives business and IT domain-based blueprint and strategy, developing purposeful business cloud hybrid platforms, products, and services across retail and commercial banking, risk management, payments, personalization, and digital products.