Columnist

Intelligent transformation of the financial sector

Technologies, for decades now, have been playing a critical role in the financial sector, enabling a transformative and disruptive innovation to financial services and products.

The emergence of blockchain and its integration with other technologies such as Artificial Intelligence (AI), Internet of Things (IoT) and big data will enable applications that are even more dynamic in the near future.

Current scene

Blockchain technology is considered by many to be the driving force of the Fourth Industrial Revolution.

Blockchains represent one of the most disruptive technological innovations of the last twenty years. They are paving the way to groundbreaking research, technology development and disruptive innovation, igniting the creation of revolutionary business models and markets in a wide number of fields, including financial services, commerce, smart contracts, IoT, cyber-security, machine-to-machine transactions, and many others.

AI, on the other hand, is conquering over all the industries and domains, performing tasks more effectively than humans do.

AI has been around since the 1950s. Even though it is not a new technology, it has become very popular nowadays due to the increased data volumes, and advanced computing power and storage that have enabled unconventional algorithms to make complex decisions with high levels of accuracy.

Decentralised AI

While “Fintech” is a new term, the existence and use of financial technology is not. Financial technologies emerged in the mid-1990s, with the banking industry being its largest buyer and user.

Decentralised AI capitalises on the strengths of both technologies, blockchain and AI for better data protection. Blockchain is a technology permitting the safe and reliable storage and transmission of data creating a new Internet layer and removing intermediaries across industries.

AI, another revolutionary technology that can learn on its own by analysing and discovering patterns in massive amounts of (big) data. The integration of blockchain and AI enables a protected decentralised AI system for sensitive data, such as, data in the financial sector.

Implications

Decentralised AI systems suggest better security than centralised systems as it is much more difficult for hackers or malware to penetrate them.  With the use of blockchain, before any information is accepted and processed on a blockchain platform, it must go through several nodes or phases of the network resulting to an immutable and secure decentralised system.

In addition, decentralised intelligence, caused by the technology integration enables the design and development of applications being able to consolidate multiple algorithms for carrying out various subtasks to the training data exchanged on the network. Such applications could be used in cases where centralised solutions exist for inter-related problems such as security related tasks in networks. Flexible/adaptable AI, a technology capable of learning; a characteristic usually found in humans will enable systems to reprogram themselves to cope with new unexpected tasks.

The Fintech revolution

The integration of blockchain and AI pave the way towards new breakthrough innovations in several areas, including medicine, autonomous vehicles, smart contracts, decentralised autonomous organisations (DAOs), financial services and many additional areas of applications, not yet conceived at present.

Markets rely usually on the mechanisms such as inter-mediation, clearing and settlement, recording and information keeping, rating, recommendation, voting, databases, authentication, incentive schemes (rewarding/punishing), transaction traceability and many more. These are all areas that have already begun their transformation within the new technologies, and banking and finance services are in the epicentre.

The challenges

Before these systems become widely adopted, there are several challenges that we need to solve. These challenges range from technological to other more complicated ones. For example, training this type of systems require massive amounts of data that many times organisations are not willing to disclose. Moreover, if we are looking at models, which they integrate various algorithms distributed to perform individual tasks across 100s of thousands of nodes, can we actually have them working autonomously, transparent without the need of a centralised trustful authority.

Society may still be at an embryonic on decentralised AI.  Nonetheless, the market is growing continuously. There are already several examples of decentralised AI systems such as the SingularityNet which enables people to create, share and monetise AI services and Ocean, a decentralised data exchange protocol to unlock data for AI.

According to William Gibson “the future is here – it’s just not evenly distributed”.

 

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