Digital strategy
Five years after the revised Payment Services Directive (PSD2) was introduced in Europe, only a third of the world’s biggest banks have meaningfully invested in financial ecosystems. These ecosystems bring together a range of financial services providers into one convenient platform for customers. Many banks are slow to adapt due to a fear of losing control over customer data, a need for a significant shift in mindset, and the challenges of updating security models and legacy technology for safe data sharing. A Boston Consulting Group study found that nearly a quarter of large global banks are not investing in these ecosystem models at all. McKinsey estimates that financial ecosystems represent a $70tn opportunity, as more banks realize their potential for boosting revenue. Experts predict that legacy banks will eventually integrate into broader ecosystems. It’s a matter of updating systems to keep pace with technology and customer expectations.
Digital strategy
Over the last two decades, banking for small and mid-sized businesses has shifted from a one-size-fits-all model to a diverse range of services. Digital banks have tended to focus on niche services to survive in the crowded market but should consider embracing a versatile business model to meet the needs of small businesses. This can be achieved by maintaining diverse deposits from a varied customer pool, pursuing fintech partnerships for technological innovation, offering hyper-personalized products based on comprehensive data analysis, and investing in Banking as a Service (BaaS) to create a seamless client experience. By returning to a model of relationship banking, digital banks can become a vital pillar in the financial market.
Organizational culture
Banks face increasing competition from tech companies expanding into financial services, and to remain competitive, they must adopt a culture of experimentation. This includes fostering an environment that encourages testing new ideas and learning from failures. To manage the risk of experimentation, banks need to anticipate potential pitfalls and define acceptable performance boundaries. Talent recruitment and retention are also crucial, with an emphasis on individuals skilled in driving transformation. To navigate the evolving digital landscape, banks must create a safe environment for risk-taking, align experimentation with strategic goals, manage risk boundaries, and foster collaborative partnerships.
AI/ML
Financial services leaders have heavily invested in customer-facing digital platforms and applications, increasingly driven by AI and ML. They now face the challenge of improving their knowledge of customers (KYC) using these technologies. KYC is necessary from a marketing perspective for personalizing services, as well as for regulatory compliance. Financial institutions can use AI to automate compliance processes and flag potential attacks. AI can also help with fraud detection and validation, reducing manual labor and costs, and enhancing customer satisfaction. Training employees to use these technologies will be the next big challenge in order to optimize these tools to better understand customers, leading to a more personalized experience and promoting security and risk mitigation.
AI/Automation
Automation has already impacted 3% of jobs across 29 countries, and this figure could rise to 30% by the mid-2030s, according to a PwC study. It identified three waves: algorithmic, currently affecting sectors like financial services; augmentation, focusing on service industries where AI supports and upskills workers; and automation, which will primarily hit the travel and transport sector through self-driving vehicles. However, the study also highlights AI’s beneficial impact on businesses through increased productivity and data-driven decision-making.
Embedded finance
Embedded finance is set to grow exponentially, with revenue expected to rise from $41 billion in 2021 to $160 billion in 2025. This integration of financial services into non-financial platforms is driven by fintech players and online platforms, and is disrupting traditional banking revenue sources such as credit card transactions and lending. For banks and credit unions, adapting to this trend involves strategic evaluations and leveraging established business relationships. Institutions such as Citibank and JPMorgan Chase have already adopted embedded finance strategies by offering embedded payment and credit options. The rise of embedded finance creates the potential for improved customer experiences, personalized services, increased competitiveness, valuable customer insights, and innovation opportunities for traditional banking institutions. It does, however, require a focus on technology investment, acquisitions, ecosystem partnerships, customer experiences, organizational agility, open banking, niche markets, and a shift from risk avoidance to risk management.
AI/ML
Artificial Intelligence (AI) implementation in banks often fails due to human-related issues rather than technology, according to Olga Tsubiks, director of strategic analytics and data science at the Royal Bank of Canada. A lack of buy-in, daily operational demands, and mixed messages from top management as the three key challenges that often derail AI projects in banking. Tsubiks stressed that the human element of implementation is often neglected, and empathy and understanding are crucial when dealing with affected employees. She suggested focusing on the “real world” use of an idea rather than specific use cases, not limiting AI to fit into current business strategies, and addressing challenges like security and compliance upfront as keys to successful AI implementation.
