Generative artificial intelligence (AI) has gained significant attention lately. The increasing number of creative AI solutions, including well-known ones like ChatGPT, demonstrates the growing awareness among the public regarding AI's potential to enhance productivity.
AI technology has already showcased its capabilities in the banking and finance sector, with larger banks utilizing AI applications for tasks such as risk assessment in lending and know-your-customer processes during onboarding. However, small and medium-sized financial institutions face the risk of falling behind as AI progresses due to limited resources. To ensure that financial institutions of all sizes can leverage AI across their organization, here are five essential steps to consider.
1. Define a company-wide strategy with clear objectives
Many small and medium-sized banks and wealth managers do not have the expertise to pinpoint where AI technology can be effectively applied within their organizations. This deficiency arises from a lack of dedicated in-house teams with experience in both finance and AI development. However, the potential benefits, such as significant cost reduction and efficiency gains, make AI adoption a strategic imperative that requires board-level discussions. This also ensures that it cuts across all departments and aligns it with the overall business strategy. Financial institutions first need to identify the main problem areas or opportunities through data analysis and industry research where AI can make a substantial impact, such as improving client experience and ensuring compliance adherence. Once identified, they can then objectively assess specific use cases, such as client churn prediction, automated risk management or AI-augmented client communication.
2. Seek expert support in AI technology
Small and medium-sized financial institutions with fewer in-house resources can particularly benefit from the AI expertise of external providers – not only for strategy conception, but also for project planning, implementation and operation of the solution. Based on our experience, a successful AI team typically comprises data scientists, business analysts, software developers, product managers and domain experts from various banking functions. However, for financial institutions, sourcing and retaining these experts can pose challenges in terms of both cost and expertise. The hiring costs alone can often surpass the budgets of small and medium-sized institutions, making it difficult to attract and retain the necessary talent. By partnering with a trusted AI service provider that can coordinate all of these expert roles, financial institutions can immediately launch their AI projects without the lead time. Leveraging the expertise and established teams of the service provider grants access to the necessary skills and capabilities for successful AI implementation.
3. Consider cloud infrastructure for AI projects
Once the necessary expertise is secured, the next consideration is infrastructure setup. Deploying AI on the cloud offers many benefits compared to a more traditional on-premises setup. Firstly, cloud-based architecture facilitates seamless scalability for AI projects by providing instant access to the necessary computing resources for banks and wealth managers. With the cloud, they can easily expand their AI initiatives to another market or another client segment, without the need for significant infrastructure investments. This approach is also more cost-effective, as expenses are directly tied to use, enabling better cost management and budgeting while eliminating the need for significant upfront investment in infrastructure. In addition, cloud providers have built-in disaster recovery mechanisms, reducing the risk of downtime, data loss and regulatory breaches. Finally, some of the latest AI technologies, such as natural language processing algorithms or investment recommendation engines, are often exclusively available on the cloud due to their specialized infrastructure requirements. Partnering with a cloud-agnostic AI service provider can greatly assist banks and wealth managers in evaluating and selecting the optimal cloud provider and setup for their specific business requirements.
4. Ensure regulatory compliance and high ethical standards
In the realm of AI, it is crucial for banks and wealth managers to prioritize compliance and ethical considerations throughout the entire AI implementation and operation journey. This includes aligning with regulatory requirements during each phase of the project. For instance, the EU Commission's flagship AI Act establishes a regulatory basis for the use of AI in the region, requiring transparency in AI implementation and maintaining human control over machine learning algorithms. These measures aim to ensure that AI always operates without prejudice or discrimination, particularly during processes such as investor profiling or the creation of personalized investment proposals.
5. Maintain ongoing monitoring and adaptation
The success of any AI project goes beyond implementation. It requires ongoing maintenance, continuous learning, and adaptation to changing business needs. Company-wide AI success depends on getting a handle on data quality, since this data will serve as the foundation for training the AI engine. It is also essential to proactively prevent errors and biases to ensure that outcomes remain fair, compliant, and reliable. By continuously evaluating data quality, monitoring errors and biases, and consistently enhancing AI initiatives, financial institutions can maintain the integrity and effectiveness of their AI-driven solutions.
Integrating AI into a financial institution's business plan is crucial, as it brings numerous benefits such as improved cost efficiency and enhanced decision-making processes. Meanwhile, end clients are increasingly receptive to the idea of incorporating AI into their investment process. According to a recent Avaloq survey, 77% of individual investors expressed comfort with AI supporting or leading the analysis of their portfolio data, 73% are open to receiving AI-supported investment advice, and 74% are willing to receive AI-assisted product recommendations. Failing to embrace AI leaves banks and wealth managers susceptible to being outpaced by competitors. At Avaloq, we anticipate a growing acceptance of AI among end clients, especially as they become more acquainted with AI-augmented tools like ChatGPT. As an orchestrator of the financial ecosystem, Avaloq is committed to empowering banks and wealth managers on their AI journey.
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