Role of Blockchain, AI and Machine Learning on Trusted Data

Data is an important asset for any enterprises. So it is of utmost importance to collect data from a verifiable and trusted source. One of the main objectives of this article is to develop a system. The system will enhance the process and quality of data sharing. That system will even track each and every change made to the data.

Tom Dunlap, the managing director of Goldman Sachs works for seventeen years on data normalization, trust, and standardization. And has loads of experience.

Dunlap notices a comprehensive progress in the financial service industry in recent times. And he develops some perspectives on data reliability and data trust. According to Dunlap, the financial services firms are considering data as a corporate asset. Financial firms are using data to enhance the client experience. They are using data to conduct other commercial activities.

Role of Legal Entity Identifier on Trusted Data

Dunlap also provides an example where financial firms are adopting Legal Entity Identifier (LEI) to manage all the systematic risks. Those financial firms take an approach to track data from the initial step of production to consumption. Thus they will get to know every minute of the data lifecycle. Thus Dunlap states that data can now be verified from the source.

From now onwards the financial firms adopting the latest system will face lesser data quality problems. All the financial firms gain noteworthy benefits due to the advent of the system. A new system will certainly boost their business up. It will enhance customer satisfaction as well.

Role of Blockchain

Roleplay Machine Learning and AI Delivers

The quantity of data is increasing every day. Now you can find a wide range of data in the form of texts, pictures, free-form images, etc.  All these data are known as ‘unstructured’ data sources. However, with the aid of Artificial Intelligence (AI) and advanced machine learning techniques, those unstructured data can be managed. Dunlap provides an example of unstructured data where data vary from one financial institution to other.

AI and machine learning come with certain capabilities to detect all the key elements like the economic terms and the legal entity names. Financial firms are using all these data to carry out language translations, to search for data points, etc.

Both the machine learning and AI are expected to come with some attractive features in the mere future. Hope they will be smart enough to know the key attributes what the firms are looking for.  Data capture and the machine process take an entire day to complete. Hope all these processes will be completed within a couple of minutes.

Blockchain and Its Significance on Trusted Data

Blockchain comes with an alternative. With the help of blockchain, you can be able to access data and imbue trust in data quality. David Shrier, one of the lecturers of MIT Media Lab make a mark already in establishing trusted data. According to him, blockchain is a different sort of database that offers transparency for multi-stakeholders environments and greater cyber-resilience.

It offers hackers with fewer chances to hack the system and the database. Thus blockchain offers safety and security.

According to Shrier, there are a lot of things to explore. The blockchain is a pioneer of reforming society. Blockchain gives rise to a new model of funding. Countries like Europe can be largely benefitted as there 70% of the funding relies on banks.

Blockchain offers several benefits. Blockchain offers customers a better digital identity. Customers can even lower the cost of the financial services. With the aid of blockchain, customers can now have better control over their assets as well.

That is pretty much about AI, Machine Learning and Blockchain and their roleplay on trusted data. In case you require any services, feel free to connect with our support team for help.