On May 29-30, DataArt, a global technology consultancy that designs, develops, and supports unique software solutions, exhibited and spoke at the CIO Summit in Chicago.
The Generis American CIO and IT Summit centers around current trends, strategic insights and best practices in technology, cyber-security, risk management, and talent management. The summit brings together top industry influencers and leaders from all industries – retail, automotive, pharma, and finance as well as many others.
Denis Baranov and Kirill Timofeev, principal consultants at DataArt, gave a talk titled “Blockchain Winter: The Story behind the Hype”, in which they discussed ways to find the appropriate use cases for new blockchain technology, the do’s and don’ts for a first distributed ledger (DLT) project, good and bad case scenarios from various industries, and using blockchain alongside current technology systems while reaping the rewards of both.
DataArt has substantial experience in building production blockchain systems for clients, including projects involving security issuance and transaction settlement, security depository and proxy voting, as well as a government public assistance benefits management system. Denis and Kirill delivered practical cases and stories from clients and partners to provide the audience with an understanding of the current blockchain environment.
Baranov explained why a crypto winter has fallen upon the industry: bitcoin isn’t trading at thousands of dollars anymore, and it’s not so easy to raise money. Consequently, fewer people have been talking about blockchain recently. But he emphasized that the situation is misleading because we have to differentiate between crypto and distributed ledger technology. If we talk about crypto, with bitcoins or other currencies, it’s not so easy to do ICOs. But that’s a good thing because right now more industries are thinking about how to use blockchain. And it’s not just how to use it in POC, but in production itself.
The amount of significant investment in blockchain by large companies is not declining, but rather increasing. This is because most of the bigger players initially came from finance and then other industries like travel, healthcare or retail began to show interest. Also, you can see from the news that the bigger players have started to use blockchain for supply chain management and manufacturing, as well as in other projects.
Blockchain is just a technology, not a silver bullet that will change an industry completely.
There have been different stages in the technology’s development, just as with the Internet and machine learning. Each was surrounded by an enormous amount of hype at the beginning and everyone wanted to use the technology just for the sake of doing so.
There were many stories about companies who simply bandied about the words and thought they had begun to do something. Usually, it started from the proof of concept. If it didn’t work out, that was okay. Baranov advises against introducing blockchain until an appropriate business use is identified.
Now more and more production cases with real projects that can add value to business have begun to materialize. And sometime in the future, blockchain will become just another technology, like the cloud, machine learning, or quantum computing. Blockchain is just a distributed ledger technology, and in simple terms, it can be thought of as a distributed database that has a one really important thing inside – it provides immutability.
And right now, since we’re not in the early stages anymore, some of the parameters or properties could disappear, depending upon the platform. It’s important to remember that there is not a single blockchain that everyone uses. Each has its own unique characteristics.
Speaking of the “blockchain winter,” Denis highlighted several positive examples.
Positive Use Cases
First of all, blockchain is a technology and needs to be used appropriately. It’s possible to take a selfie with a MacBook, but it’s not easy. For a good nice selfie, you should use the appropriate device. The same applies to blockchain.
In most cases, blockchain should be used if you need a distributed acknowledgment mechanism for counterparties that need to gain more trust.
Take Lufthansa – they use blockchain for one of their POCs for spare parts. They could use a central database with a history of the spare parts. In a negative scenario, the information could change. No one says it would, or that it has happened already. But what if it could? In this case, blockchain can be used to provide notes to external parties to guarantee this does not happen.
Case # 2
Paper contracts – if you have information to share between contracting parties, you’ll have to go through a long document flow process that can be inconvenient and complex. What about when you need an unalterable audit trail? Blockchain is perfect for these situations. You might want to automate contracts and if you want the automation to be based on unalterable rules blockchain is a good solution.
Case # 3
You could use blockchain if you want to create a new cryptocurrency, e-money or eternity faсets, all quite popular in finance right now. For example, in Switzerland, you can maintain your shareholder register in the blockchain. It’s legal and effective for other activities such as shareholder voting.
Paper documents are part of the problem when clinical data and health care data are not maintained together. This is how we could solve the problem.
Healthcare & Life Sciences Data Exchange
There is a giant network and we cannot just publish all EHR in this global blockchain. We’ll have to fix and deanonymize data. We’ll have to go through some extreme linking and referencing. But this is not the end. If we assume that two items have been fixed, there is also no global protocol that allows us, as human beings, as current patients or future patients, to effectively collaborate with each other. This is part of a bigger problem. It’s essential for us, as human beings, to help others.
As for the clinical trials, the current system is fragile. There is a very long process to bring a new drug to market, and there is a recruitment process. You’ll have to verify if it’s compliant, among other things. And on the patient’s side what matters most is that a patient must be aware that a clinical trial exists to contribute to the EHR or find the treatment.
Another problem is data breaches. In the United States, it’s obligatory to publicize any data breach that happens in a medical facility or hospital. Just in the first two months of this year, almost a million individuals were affected by data breaches, whether due to human error, hacking, or something else.
When we say blockchain, we are not just saying that it is a convenient technology (although it is). We see that we have to think through the problems, and identity a use case first of all.
In clinical trials, there’s a good use case involving the hospital and patients. The hospital holds clinical trials with certain inclusion and exclusion criteria. And there is a patient with a medical condition who would be interested in trying the experimental treatment. But, at the same time, the patient might not be aware of the clinical trial.
Another problem is that the patient might not trust the hospital with sensitive personal data.
They both want to know if a Patient is right for any of Hospital’s Clinical Trials and keep PHI protected.
Typically, the problem is solved by involving a third party. You can use an Escrow, which is highly compliant with regulations and has very strict finance and security protocols. A patient contributes his or her personal data, EHR data, to that data bank and the medical provider pools the data. We use banks every single day, but there are some limitations. When we talk about intermediaries, there are two foundational problems.
Problem #1: Slow processes. Patients are forced to wait; for example, a patient is forced to wait for insurance company notification of coverage.
Trusted third party
Problem #2: Intermediaries undermine privacy.
Kirill’s favorite example is the Equifax hack that happened two years ago. Almost half of the American population was affected, and a significant amount of data, including Social Security numbers, was compromised.
So, what if there was an algorithm providing a solution to allow two parties to collaborate interactively and answer certain questions, having data transfer securely protected?
This can be done with a zero-knowledge algorithm that creates a formal proof.
A patient makes a custom request on the patient’s personal data. The request asks for the necessary minimum.
A hospital computes the response and constructs the proof of correct computation.
Zero-knowledge proof system
A hospital sends a request to a patient asking for a very limited set of data, such as, “I am looking for your heart rate for the last month” and the patient creates a proof.
A proof is a mathematical construction. It threads all the data, EHR data, and this is a one-way transformation, but a mathematical approval transformation, so when it comes back to the hospital, the hospital can verify that this patient matches inclusion & exclusion criteria based on the EHR data a patient provides. But, at the same time, and this is the key, EHR data is never exposed.
If you think about the data transfer, there are three pieces: a source, a destination and there is data in between. With zero knowledge algorithms, you can secure two items out of three, a hospital will never have EHR data in plain text, it will be in encrypted form. You will never transfer EHR data using HDS protocol, or whatever else. So, ultimately it will be the patient who owns data, keeps the data and has full control around it.
Сlassical Difficulties with Blockchain
First of all, blockchain is really effective for shareholder voting or any other voting process. This is because you can guarantee how words go in which spot and it is fully transparent for all involved. We’ve done such projects for some of our clients and they have been hugely successful.
Another big part of the industry in blockchain right now is a collaboration with insurance companies. For one of our clients, a large insurance company, we have developed an insurance collaboration platform.
In the first illustration, you can see how the process currently looks.
Traditional Reinsurance Process
The traditional reinsurance process has a huge amount of participants, with various involvement and information shared between all them. Large numbers of emails with spreadsheets attached have to be sent between them every month. This is inefficient.
Blockchain can be used as a central source of truth and everyone can find information on monthly movements, claims and other issues based on the pre-agreed formulas that provide calculations for claims or other payments immediately. And a full audit trail is available.
You can easily use blockchain right now because it’s in the cloud. It’s similar to machine learning, you could spin off your blockchain network in minutes, from any major clouds – amazon, azure, or other major providers.
All IT professionals are excited to work with blockchain, but it’s not so easy to get started on your own. At DataArt, we have implemented many blockchain projects. We know all the pros and cons. Our recommendation may be not to start from scratch. In some cases, we recommend using blockchain, in other machine learning or another technology, but we recommend using more than one. All of them provide different possibilities and have different pluses and minuses.
DataArt’s recommendation is to experiment and try to find something new. It can increase your business efficiency or revenue, among other things.
About the speakers:
Denis Baranov is a principal consultant at DataArt. With over 10 years of experience in the IT industry as a developer, technical architect, solution architect and IT leader, he specializes in designing and building business solutions in financial services, capital markets and fintech. Denis joined DataArt in 2008 and works from its London office.
Denis is passionate about technology innovation and is currently focused on leading the development of market solutions underpinned by distributed ledger technologies such as blockchain and AI technologies (machine learning.) He is actively engaged in projects and communities both inside and outside DataArt, and is a regular speaker and contributor at various conferences.
Denis holds a PhD in computer science from Lomonosov Moscow State University, and has an MS in Applied Mathematics, Informatics & Mechanics.
Kirill Timofeev is a recognized expert and thought leader in innovation and new technologies in the financial services sector. As a software project manager at DataArt, he has delivered enterprise-grade projects for some of the world’s largest financial services and capital markets, including a securities settlement platform and a digital money solution for payments and FX. Kirill has authored numerous articles on cutting-edge technologies, is a regular participant in blockchain conferences and communities, and an active commentator on uses of Blockchain in intech.
Based in New York, Kirill joined DataArt in 2007 as a software developer and quickly advanced to become a software project manager. Prior to joining DataArt, Kirill worked for several academic institutions. He holds an MS in applied mathematics and informatics from St. Petersburg ITMO University in Russia.
About the Generis American CIO and IT Summit:
The Generis American CIO and IT Summit is an event designed to provide IT executives with news about current trends, strategic insights and best practices in trending technology, cyber-security, risk management and managing talent.