From reshaping traditional banking operations to enhancing customer experiences, GenAI emerges as a disruptive force driving innovation and efficiency. Generative AI (GenAI) stands as a subset of AI, focused on generating new content or data using algorithms trained on large datasets. Within enterprise contexts, GenAI finds applications in automating repetitive tasks, generating personalized content, summarizing documents, and enhancing employee productivity by providing quick access to information.
In the dynamic realm of banking and financial services, the integration of GenAI has evolved into a transformative journey. The surge in ambition and investment observed in 2023 has prompted banks to explore a myriad of AI use cases. The heightened pressure from leadership to demonstrate tangible return on investment has led to the establishment of dedicated leadership teams focused on scaling up GenAI initiatives, globally.
- In BFSI, GenAI is revolutionizing customer experiences through risk management, fraud detection, personalized services, and operational efficiency. Gartner forecasts that banks’ spending on security and risk management will reach $215 billion by the end of 2024, worldwide, marking a 14 percent increase YOY.
- The latest advancements include anomaly detection as a key use case. AI models can detect anomalous transactions that are not easily identified by rules-based systems. Swedbank reported a 20-30 percent improvement in fraud detection using these models. This application is critical as BFSI entities process enormous transaction volumes.
- Case studies showcase GenAI applications in robo-advisors for portfolio management, algorithmic trading, customer service chatbots, AI-based underwriting, automated contract management, personalized financial planning, optimized trading strategies, and enhanced customer support.
While banks are reaping the rewards of AI implementation across various use cases, the true challenge lies in fundamentally rethinking the very nature of bank operations.
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Building a vision for the GenAI era
How do we redefine the essence of banking by envisioning entirely new ways of delivering products and services?
This shift goes beyond improving existing processes — it’s about reconstructing the very essence of bank operations, moving from a traditional physical facade-focused model to an edifice built around data and AI infrastructure. The journey to becoming a GenAI-driven institution is daunting but crucial for staying relevant in the evolving landscape, leveraging data analytics (for e.g. regulatory compliance data, credit risk assessment, investment data etc), to bringing in automated processes and improving overall efficiency gains.
Driven by the wave of digital innovation, India has maintained an unwavering momentum toward progress and promise. The (2024) Digital India Story is set to revolutionize every user experience by leveraging advanced AI/ML capabilities such as analyzing user preferences, behaviors, and past interactions to deliver highly customized and relevant content.
Investing in scalable capabilities
Leaders in the financial sector must identify the necessary capabilities, skill sets, and investments required for the GenAI-centric future. Balancing the urgent delivery of new products along with designing the organization to deliver on this agenda poses a significant challenge. The focus should be on building repeatable tasks and tools that yield compounded returns.
For instance, in banking operations, GenAI presents a progressive solution for contract management. By automating tedious tasks like reviewing agreements, suggesting compliant clauses, and auto-redlining contracts, GenAI streamlines processes, saving time and resources.
Similarly, for better credit risk assessment, banks are using AI-based systems to help make more informed, safer, and profitable credit decisions. Machine learning algorithms can look at behaviors and patterns to determine if a customer with limited credit history might, in fact, make a good credit customer or find customers whose patterns might increase the likelihood of an upsell.
These algorithms assess creditworthiness using thousands of alternative data points beyond traditional scoring.
Another example is in the mortgage sector where GenAI capabilities extend to leveraging customer data to generate tailored contracts. By optimizing terms based on past loans while ensuring compliance with regulatory standards, GenAI enhances efficiency and accuracy in mortgage transactions.
Harnessing the power of GenAI for BFSI
GenAI holds the potential to reshape the game in three key ways:
- Changing the nature of conversation: Early leadership in AI is no longer a relative competitive advantage. GenAI has altered the discourse around AI, making it an essential consideration for all.
- Disrupting early-mover product advantage: Technologies like chatbots, once considered cutting-edge, are no longer state-of-the-art. Investment in GenAI can deliver a suite of products that are at the cutting edge.
- Leapfrogging competitors: Large Language Models (LLMs) may allow banks to leapfrog competitors in technical skills and deep data sets. Decades-worth of data infrastructure investment might now be replicable in significantly shorter time frames and at lower costs. While the impact of these changes is still uncertain, deeply ingrained cultures focused on optimizing data-driven business models may retain a competitive edge.
A recent study by McKinsey indicates that the total potential value of Gen AI in banking is in the $200-$340B range, encompassing engineering, customer service, sales & marketing, and risk management use cases.
By 2025, there will be over 100M adult generative AI users (i.e., ~82 M “at-work” users).
Typically, they see this being used across four areas:
- Product R&D/Software Engineering
- Customer Operations
- Marketing & Sales
- Other functions like risk model documentation
Adobe solutions in the Gen AI landscape
At Adobe, as we embrace the motto — “Creativity is the new productivity,” we are leading the way with solutions like Adobe Firefly and Digital Experience solutions infused with Sensei and more GenAI capabilities.
Adobe’s approach to GenAI revolves around scale, trust, and enterprise readiness. How you go about your jobs in campaign creation, audience identification, experience delivery, simulating journeys, and ultimately understanding the insights that are reported out of our systems.
- Designed to be commercially safe: Trained on Adobe Stock’s 300 million+ high-res, high-value assets and openly-licensed, public content where copyright has expired, backed by Adobe with indemnification.
- Integrated workflows: Firefly’s GenAI capabilities will be embedded into tools across Adobe Creative Cloud, Adobe Document Cloud, and Adobe Experience Cloud.
- Co-pilot for design & delivery: Marketers and creative professionals will always be at the helm and will be able guide and supervise generative outputs.
- On-brand, at scale: Exploring ways for customers to train Firefly with their own collateral, generating content in their brand style & design language.
As banks strive to extract value from GenAI today, they face the dual expectations of digital transformation and strengthening shareholder returns. The economic challenge lies in transforming variable cost exercises into fixed cost processes.
While this challenge may be less stark for banks than for professional services firms, aggressive GenAI roll-out is likely to exert competitive price pressure, potentially from nimble start-ups or from legacy banks leveraging AI to scale up offerings and enhance efficiency.
Additionally:
- Governance frameworks must be instituted early, covering risk, testing, and responsible use
- Focus initial applications on improving employee productivity through knowledge search and document generation
- Upskill talent through executive training, new capability building, and skill-based hiring
- Adopt centralized models to steer org standards while encouraging business unit inputs
- Validate model outputs through subject matter experts and automated validation tools
- Design solutions end-user first, allowing human input to shape system evolution
In summary, while GenAI introduces transformative potential in BFSI, prudent governance and change management will dictate successful scaling. Banks that address these challenges effectively can unlock immense value.
Conclusion
GenAI in BFSI holds immense potential to revolutionize banking and financial services, from enhancing customer experiences to optimizing operations. The strategic and ethical implementation of GenAI capabilities will be key for BFSI institutions to gain sustained competitive advantages in this ever-evolving landscape, in 2024 and beyond. We acknowledge the fact that AI and GenAI can transform and supercharge data discovery, to accelerated content creation, to hyper-personalization and delivery.
Source: https://blog.adobe.com/
