Generative AI is a force to be reckoned with. It moves fast, fanning the flame of change across the banking industry, shifting the boundaries of the art of the possible. Despite the almost limitless scope of potential use cases for this technology, such as enhancing customer attraction, retention and engagement levels, many banks are looking to Generative AI to support with providing tailor-made product offerings with an enhanced value-add. For others, they are implementing this technology to understand internal corporate structures better, thereby facilitating more informed and strategic decision-making for the client.
In both the corporate and banking worlds, risk is an area that requires constant attention. Effective risk management is crucial to ensure a safe and reliable financial ecosystem. In light of this, it is reasonable to think that the most effective technology must be employed to manage risk most effectively.
What is certain is that banks that want to operate at the bleeding edge of innovation, cannot ignore Generative AI. Those who fail to explore and adopt Generative AI technologies risk being left behind in an increasingly competitive and technologically advanced sector. But it's no longer just about keeping up with competitors; it's about paving the way to the future.
Addressing the needs of the market with a win-win approach
Looking at the needs of today’s market, banks’ corporate and SME clients are demanding more client-centric solutions focused on enhancing risk management decisions. As a result, banks are keen to improve commercial relationships by cross-selling a wide range of products but to achieve this goal, a win-win approach is critical, ensuring that actual value is provided to the SME or Corporate CFO.
A win-win approach ensures collaboration and data sharing between the bank and the client, further strengthening their relationship. The collaboration is built to have mutual benefit for both banks and the corporate client, with both gaining from working together.
On the one hand, corporates will receive services from the bank and will be able to improve their risk hedging decisions. They’ll be able to receive alerts about risk position changes, benchmark their levels of risk against industry peers, and build an integrated offering of tailored financial products to cover risks. While banks will be able to enjoy plenty of cross-selling opportunities and increased client engagement, as well as increase visibility of customer needs through transactional data and induce positive externalities for the bank’s credit quality.
Hedging corporate risk through analytics and AI
To adopt this type of win-win approach, a corporate risk hedging solution, and more importantly a comprehensive risk dashboard, is required. This provides banks with a better understanding of their current risk exposures and supports in making superior hedging decisions by including value-added indicators and utilizing advanced analytics.
Such a solution provides incremental value to a banking organisation – it can start with a basic Minimum Viable Product (MVP) in the first instance, focusing on credit and country risk migration statement, as well as a risk dashboard. This can then be developed over time, with the ultimate goal of developing this into a complete solution, leveraging advanced analytics and Generative AI, which would provide hedging recommendations, peer comparisons and even intelligent chatbots to help clients understand the root causes of the risks they face.
Several value levers can be incorporated into this solution too. Firstly, embedded finance is used to provide additional value to the client and address growing concerns around corporate data sharing. Secondly, Generative AI is utilised as a lever to synthesise market information and deliver hyper-personalised narratives regarding potential root causes behind portfolio risk.
There is also an option to augment a human team with Generative AI, ensuring objectivity in the narrative provided. This combination of AI and human expertise can be invaluable in making sense of complex market trends and potential risks. Moreover, it prevents the bank from running into regulatory risk and compliance issues.
Finally, there is scope to scale up the product offering, moving beyond credit and country risk hedging, to other derivatives such as currency and commodity, as well as working capital financing. This involves engineering a billing model that balances data fees with incentives to initiate hedging transactions.
Making risk hedging client-focused
This type of corporate risk hedging solution offers a comprehensive, client-focused approach to risk hedging, providing incremental value to clients and addressing their specific needs and concerns. By leveraging Generative AI and advanced analytics, and by offering a scalable product range, it holds significant potential to improve risk management and enhance commercial relationships.
Banks adopting this approach and solution will set themselves up for greater success in a competitive market. By enabling banks to take a win-win approach to corporate risk, this solution will transform the corporate banking market, and contribute to a more innovative future in banking.