News!: Opus Technologies Launches FinGeniusAI Solutions – An Open Innovation Platform for Building Future-Ready Solutions.. Know More
News!: Opus Technologies Launches FinGeniusAI Solutions – An Open Innovation Platform for Building Future-Ready Solutions.. Know More

CEO’s Corner

Entering the AI Arena: How Banks and FinTechs Should Plan Their AI Entry Strategy

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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.

The financial services industry is facing a confluence of rising customer expectations and heightened pressure from shareholders. Customers demand intelligent solutions that seamlessly integrate into their existing ecosystems. Shareholders, meanwhile, expect financial institutions to demonstrate a clear ROI from their growing AI expenditures.

This urgency surrounding AI adoption underscores its existential role in the future of the global financial sector. Financial institutions that fail to embrace AI risk falling behind in the competitive landscape. According to the AI benchmarking and intelligence platform Evident, large banks and financial institutions across the world are making significant strides in adopting and implementing AI across different organizational functions. JPMorgan Chase leads the race in the latest Evident AI Index, which assesses a financial organization’s AI readiness based on four key maturity parameters. The bank has invested heavily in AI prototyping and development, widening the partner ecosystem, and building data engineering talent metrics. Capital One and Royal Bank of Canada closely trail JPMorgan Chase in AI domination in financial services.

Source: Evident AI Index, November 2023

One can safely confirm that 2023 served as a year of AI exploration for banks and FinTechs through pilot programs and proof-of-concept initiatives. Now, in 2024, we are poised to see a shift towards production as large banks and FinTechs move their AI use cases from pilot to mainstream implementation, benefiting both employees and customers.

Understanding Your Needs: Identifying Value Drivers

For financial institutions, embarking on a successful path toward AI adoption requires a comprehensive understanding of their specific needs. Broadly, the potential use cases for AI in banking and payments can be classified into these three categories:

A thorough review of the institution’s product and service portfolio is essential to identify areas that require immediate improvement. This strategic alignment ensures that the AI strategy directly addresses these gaps, leading to a faster realization of tangible benefits.

Furthermore, conducting an AI-readiness assessment provides a valuable roadmap for successful adoption. This evaluation should delve into five key dimensions of AI maturity:

  • Data Mastery: This dimension assesses data management practices, focusing on data security and real-time processing capabilities, particularly those that are critical for seamless payment operations.
  • Strategic Business Impact: Aligning AI initiatives with prevailing market trends and prioritizing customer experience is paramount to achieving a competitive edge.
  • Governance and Compliance: Ethical considerations, robust security practices, and comprehensive risk management procedures are essential for responsible and trustworthy AI adoption.
  • Technology Infrastructure: This assessment evaluates the bank’s technological preparedness for AI integration, including scalability and lifecycle management within high-transaction environments.
  • People and Partnerships: The survey should analyze the organization’s internal team skillsets and identify potential strategic collaborations to foster a culture of AI innovation.

By prioritizing needs assessment, strategic alignment, and a comprehensive understanding of their AI readiness, financial institutions can position themselves for a successful and impactful AI journey.

Enforcing AI readiness is not an option, but a need. With large banks and financial institutions rapidly moving from pilot projects to full-scale deployment, AI laggards are at risk of losing their market share in the near future. According to a 2022 study by Accenture Research, AI transformation is expected to occur 16 months faster than digital transformation. This data underscores the need to move swiftly and strategically.

Source: Accenture Research

Setting the Stage for Success: Building a Strong AI Foundation

Financial services have prioritized transitioning from a traditional delivery model to a digital-first model since the early 2000s. A similar organization-wide transformation is required for moving to an AI-first model. Without setting the proper foundation and building a core that leverages AI, an organization won’t be able to deliver personalized customer experience and increase revenues.

In a 2020 report, AI-bank of the future, McKinsey identified four transformation layers for an FI to streamline their capability stack for AI-based value creation.

Rethink customer touchpoints and delivery: To reap the benefits of AI, banks and financial institutions need to move beyond generic products to personalized solutions that cater to specific customer needs. This might involve integrating non-core services to offer comprehensive solutions. Additionally, seamless partner integration allows traditional banks and credit unions to embed their services within partner ecosystems, reaching customers where they already are and leveraging partner data for a more engaging experience. Designing a seamless omnichannel experience ensures a smooth journey for customers across all touchpoints, be it web, mobile, or branch, with consistent context recognition throughout.

AI-powered decisioning engine: Developing an enterprise-wide AI roadmap for deploying advanced analytics and machine learning models across core business domains. While the banking industry has been actively involved in digital transformation for the past 25 years, embracing AI requires them to go the extra mile.

To ensure efficient model creation and deployment, establishing repeatable processes is crucial.  For employee adoption, it’s essential to make the models understandable and implement effective change management strategies. This layer can be further augmented with cutting-edge AI capabilities like natural language processing and computer vision to enhance experiences and efficiencies. Additionally, translating AI insights into coordinated interventions across customer touchpoints through data pipelines, platforms, and campaign platforms helps create an enterprise-wide decisioning engine.

Cloud-first data infrastructure: Align business and technology strategies to determine whether to develop core technology components in-house or leverage partnerships.  To fuel AI models, data must be readily accessible and transposable. This requires ensuring data liquidity and designing a data value chain for efficient data sourcing, cleaning, and labeling.  Implementing controls for data security, privacy, and regulatory compliance is paramount. Additionally, leveraging a modern API architecture with cloud-based platforms allows for controlled access to services, products, and data, both internally and externally, fostering better collaboration and enhanced customer experiences.

Platform-based organizational model: This involves establishing cross-functional platform teams within the organization. These “platforms” own their assets, budgets, and goals, delivering products or services to customers or other internal platforms. There are three main platform archetypes: business platforms for customer-facing activities, enterprise platforms for shared services, and enabling platforms for cross-cutting functionalities.

By implementing the transformation at the core, financial institutions can embrace AI for enhanced customer engagement, improved decision-making, and a foundation for continuous innovation.

Choosing the Right Entry Point: Tailoring Your Approach

The ideal entry point for Artificial Intelligence (AI) adoption depends on your organization’s size, resources, and customer base. Begin with a focused pilot project that addresses a specific pain point, like automating payment routing to enhance the transaction approval rate. This allows for controlled experimentation and learning before committing significant resources. You can gain valuable insights into the chosen AI solution’s strengths and limitations, allowing for informed adjustments before broader implementation. A successful pilot can also encourage internal buy-in for further AI adoption.

Collaborate with partners or solutions providers specializing in AI solutions for your specific industry. Established technology providers with a strong track record in AI can also be valuable partners. These partnerships bring specialized knowledge and experience in implementing AI solutions within your domain. Partnering with experienced providers can help mitigate risks and accelerate your time to value, especially for organizations with limited in-house expertise.

To help FIs accelerate AI adoption and navigate through the challenges, Opus Technologies has launched FinGeniusAI Solutions. It’s an open innovation platform that brings together all the stakeholders involved in the development of AI. As a co-development and value-creation platform, FinGeniusAI is built to incubate innovative ideas and generate proofs-of-concept (PoC) for faster assessment.

Building an AI-ready financial institution requires the right entry point, optimized IT infrastructure, and an appropriate organizational structure. To leverage AI, it’s imperative to unite business and technology teams and prioritize customer experience in all discussions.

In the upcoming installments of this series, we will dive deeper into other crucial aspects of AI adoption in the banking and payments industry. Stay tuned.

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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