The architecture of hybrid governance: Designing systems that learn to govern themselves

Governance can be seen as a paradox in the financial world. Rules are necessary to ensure stability and fairness, but they often become barriers that impede change and evolution. This inflexibility is compounded by the fact that the protocols designed to build trust are typically created by decision-making boards with little involvement from the people who actually participate in the system.

However, the emergence of blockchain has started to shift the foundations of traditional governance. It is allowing emerging models to take a new perspective on governance, viewing it as something dynamic and evolving rather than static. At IE University, Professor Álvaro Arenas has taken a closer look at how novel governance models make an impact on concepts such as inclusion and value creation. His research explores how hybrid models, which combine the strengths of centralized and decentralized finance frameworks, can make governance more adaptable and accessible.

Hybrid governance systems can help financial institutions evolve efficiently as conditions change, while retaining enough oversight to maintain stability and control. As global financial systems become increasingly complex, this new form of governance model will be essential in adapting to shifting environments.  

Why financial systems ossify

Over the course of the 20th century, traditional financial governance models have supported the weight of great economic growth. Built for stability, they are based on predictable hierarchies and well-defined positions of authority. The problem they face now is that these rules have become too rigid to support the evolving shape of financial markets. They change very slowly and only under duress, in response to crises or major failures.

One reason governance models in traditional banking systems are slow to change is that they rely on interwoven legal frameworks that are time-consuming and costly to modify. Another reason is that oversight is concentrated in centralized authority structures, with no input or feedback from the users of the systems. Aside from slowing progress, this lack of input means that underserved groups are inevitably excluded from the mainstream system. 

The rigidity in centralized systems makes them inefficient and uninclusive. This is a problem in an era where technology and financial behavior can change in the blink of an eye. Decentralized systems offer a potential solution, but they include some risks. The architecture can be considered more complex to manage, requiring greater coordination among participant actors.

This is where a hybrid system offers an ideal solution. By combining the strengths of centralized and decentralized models, it provides stability with the flexibility to adapt to changes and learn from its environment. 

Building adaptive governance systems with blockchain

From a blockchain perspective, governance is defined as a combination of automated rules and social interactions that facilitate collective decision-making. This means that governance is not something simply written and imposed by an external authority; rather, it is an evolving set of rules that change in response to collaborative feedback from all participants and stakeholders.

Governance models can be made self-correcting via feedback loops, opportunities for participants in the system to review the rules, which are then adjusted accordingly. Examples might include: 

• Parameter updates via community decisions
• Regulatory changes in response to operational constraints
• Adjustments due to market conditions that influence incentives and risk

Smart contracts are perfectly suited to this type of evolution because they allow rules to be updated through a structural voting procedure. This means we can create decentralized, democratically regulated policies that can be changed quickly in response to new requirements. At the same time, smart contracts built on blockchain provide the legitimacy and accountability needed for stable, reliable governance.

How blockchain-based and DLT platforms for financial inclusion apply hybrid governance

Professor Arenas’s research uses two platform archetypes to illustrate the strengths of hybrid governance systems. The first archetype – blockchain-based crowdlending plaforms for financial inclusion - connectsmallholder farmers with international financing opportunities. The second archetype – deep-tier supply chain finance platforms - allows small enterprise suppliers to tokenize their invoices, helping them get access to loans. Both platforms adopt hybrid models that incorporate both institutional authority and decentralized governance practices.

Blockchain-based crowdlending platforms as a community-led governance laboratory

Blockchain-based crowdlending platforms can be understood as peer-to-peer funding models that allow global investors to lend to farmers who do not have access to mainstream credit systems.  A distinctive element is that borrowers are not treated as isolated, purely “rated” applicants. Rather, they are provided with cooperative positions in a decentralized governance model, together with auditors, investors and community participants. Since all participants are treated as stakeholders, they cooperate to make decisions about onboarding new borrowers, changing risk parameters and more. 

This type of platforms use community voting and staking to assign liability and accountability to each participant in the system. Governance rules thus evolve quickly in response to users’ needs, which reinforces users’ trust in the system. With consistent feedback, the system always stays up-to-date with changing conditions. 

Through this model, two major problems of traditional lending systems are solved. First, information gaps are reduced because both auditors and cooperatives stake value in the system. This makes them accountable for the data they provide and verify about borrowers. Second, the system reacts quickly and efficiently to changes in its environment. Ongoing community voting provides constant feedback, so the system updates itself in real time. 

Deep-tier supply chain finance platforms as an institutional governance model

Deep-tier supply chain finance platforms, by contrast, are designed to tokenize supply chain receivables. Its governance model is not based on decentralized community participation, but blockchain is still used to ensure transparency and immutability. Overall governance is provided by central institutions. A group of appointed operators oversees onboarding criteria and other key processes, while public sector institutions manage regulation, define operational procedures and establish the legal framework for the tokenized invoices.

This model builds compliance directly into its governance via the overarching public institutions. The smart contracts from the blockchain system provide essential information for regulators to review continuously. The adaptiveness of this model comes not from community participation but from regulatory collaboration. The institutions have immutable records of user behavior, and the data shapes the evolution of the system itself. 

 Across both platform types, the capacity to evolve reliably depends on strong, trustworthy feedback. In both platforms, transparent data and consistent review allow these hybrid governance systems to adapt seamlessly to their environments. 

Is adaptive learning a necessity in governance?

One important lesson from the ongoing research is that adaptive learning in governance increases user trust. In traditional centralized systems, trust is established through stability and consistency over time. In decentralized systems, trust is built through equal participation from everyone. 

Hybrid governance generates trust through its ability to adapt to feedback quickly. Inflexible systems often end up losing their credibility because users stop trusting institutions that refuse to change based on the feedback they are being given. 

Clearly, there is a link between adaptability and trust that applies to both decentralized and centralized governance models. Blockchain can help replace personal trust with programmable verification systems, but institutional trust will still depend on how quickly and flexibly the governance model evolves. Adaptive learning is an essential piece of the puzzle, as it can improve trust in blockchain-based governance systems by allowing them to evolve quickly in response to user needs and environmental changes. 

Here, we see the value of hybrid, self-correcting platforms that improve themselves over time via community feedback. Hybrid governance treats feedback as valuable data that allows it to improve itself for the better. This move towards adaptability aligns with the principles of decentralized governance, envisioning a complex network of interactions between participants rather than a hierarchy of unchanging rules. 

Professor Arenas argues that hybrid governance incorporating adaptive learning will be the basis for the next generation of financial and public institutions. These systems will no longer rely on static rule books. Instead, they will treat governance as a work in progress, always adapting and improving in response to feedback.