Cindicator is a trading tool which uses human input and artificial intelligence to help investors and traders. They want to create the social and technological infrastructure needed to make effective decision under the volatile conditions of the new economy. By combining a large number of diverse financial analysts and a set of machine learning models into a single system, they are developing a Hybrid Intelligence infrastructure for the efficient management of investors’ capital in traditional financial and crypto-markets. Between the global platform launch in December 2015 and October 2017, 8000 forecasters have made 230.000 forecasts. (1) They started their marketing and currently have 78.000 forecasters. (2)
At the moment most investment venture deals are closed by “syndicates”. One of the reasons for such a deal structure lies in the use of collective intelligence systems for risk hedging against the potential mistakes of group thinking. Now imagine the collective intelligence of professional investors combined with artificial intelligence technology, which, based on the use of a large volume of data in real time, adapts to current market conditions and produces signals for entry or non-entry into a deal, free from emotional factors.
Hybrid intelligence is the combination of human intelligence and machine intelligence, and their interaction in resolving various tasks. One sort of intelligence supplements and strengthens the other. The benefits of Hybrid Intelligence of an ecosystem and community are:
A technological and analytical infrastructure for the efficient and safe management of investors’ capital by investors themselves or licensed managers.
An opportunity for analysts to monetise their intellectual assets without risking their own funds.
Tools and data for making investment decisions under the conditions of market uncertainty.
Up-to-date analytics of the industry, expectations and opportunities, and market growth points.
Ecosystem of Hybrid Intelligence
Thousands of analysts on the Cindicator platform generate various forecasts daily, answering a number of specific questions about the price level of different financial assets, macro-economic indices, and events significantly influencing the market.
“Will Bancor collects more than 100 million during the first week of ICO?”
“Will the Tesla stock price surge to $345 during market hours on friday?”
Cindicator works by using a large dataset that is transferred to a mathematical block consisting of a machine learning model ensemble. Machine learning models dynamically calculate various weightings for each forecaster, identifies stable systematics in their errors and calculate corrections for the errors, in order to eliminate noise and generate final predictions and trading signals. At the core of the Hybrid Intelligence system is the synergy of the collective intelligence of a large group of dissimilar decentralised analysts combined with artificial intelligence. There are two framework components in the ecosystem.
In order to ensure effective operations, any group intelligence system should meet the following criteria: Members of a single group intelligence should posses varied knowledge, competencies and views. A group may have a lot of errors; however, the diversity of the points allows them to be ignored in the modulus. Furthermore, the group should be completely decentralised, no communication or exchange of opinions inside the group is allowed in order to avoid the influence of some individuals on others and each group member must be highly motivated in generating the most accurate forecast.
Each month, Cindicator distributes funds proportionally to each user’s ranking in the application. They have developed internal user rankings, special nominations, and other gamification elements to enhance the competition factor.
Getting daily feedback on the accuracy of their forecasts as well as increasing their level of knowledge before preparing each prediction helps forecasters to enhance their skills and find the best strategies for forecasting various types of events.
The Artificial intelligence system is the first stage which generates a large amount of ‘raw’ data, the next step is Cindicator’s ‘black box’, with the following core elements:
– The system and methods defining the confidence weight (with constant adjustments after each question and trade) for each user, which takes into account the following: the personal track record (signal types, links between answers), dynamic feedback of each user’s forecast (profit loss) and the predictive model.
– Trading strategies and models to seek the best possible way of using the enriched data to create trading robots: Testing various trading strategies, hypotheses, constant backtests and forward tests to adapt the models to the constantly changing market environment.
Trading portfolio of Hybrid Intelligence
In order to validate the Research and Development progress to develop the Hybrid Intelligence technology, and to verify the quality of the Cindicator analytical products, a Hybrid Intelligence Portfolio is created. This portfolio is divided into three parts, in order to cover the most promising and scalable trading strategies, as well as for effective risk hedging. The parts are as follows:
– Active cryptotrading based on Cindicator technologies, along with data and signals retrieved from the consensus of Hybrid Intelligence.
– Protective buy and hold portfolio of crypto assets.
– Active trading of traditional financial assets: stocks futures, and foreign exchange markets on the basis of Cindicator technologies, as well as data and signals retrieved from the consensus of Hybrid Intelligence. This portfolio will be managed by their team of traders and tradings robots. Summaries of the results of the bot can be found on their Medium page. (3) (4)
Use of Cindicator Token (CND)
Each CND token holder can obtain a new level of access to Cindicator’s analytical products. The level of access and the products and tools available will depend on the quantity of tokens in each holder’s possession: Beginner: 5k+; Explorer: 30k+; Trader: 200k+; Expert: 700k+. (5)
75%: Token sale contributors; 20%: Cindicator company (+ vesting); 3.8%: Advisors and partners; 1%: Bounty campaign; 0.2%: Current Cindicator forecasters.
Company, team and advisors
Cindicator is a fintech company founded in 2015. The Cindicator team has created a synergy of people with a variety of expertise. About 85% of the team members are graduates of top STEM universities**. In January 2016 the team was invited to several startup accelerators and raised $300.000 during the pre-seed round of venture investment. From November 2016 to March 2017, Cindicator took part in the first batch of the Moscow Exchange fintech incubator, where it was ranked as the top-performing startup. The company was granted $120.000 for technology development from Microsoft and became a member of the Microsoft BizSprak startup support program. In april-May 2017, the company attracted $200.000 from a number of fintech investors. (**STEM stands for science, technology, engineering and mathematics and refers to any subjects that fall under these four disciplines)
The team exists of 3 founders which are explained below. 8 Data scientists, 10 Developers, 6 Traders & Analysts and 4 community related roles which makes it a total number of 31 team members. Their website mentions 15 Advisors/Partners. (6)
CEO: Mike Brusov, Technological entrepreneur with 8 years of experience in launching companies in big data and predictive analytics. Engineerings degree, Hydraulics and Fluid Power Technology/Technician. Co-Founder Wobot, a professional social media monitoring & analytics tool for brands, agencies and experts. (7)
CTO: Yuri Lobyntsev, Master in Computer Study. Software engineer JSC VNIIRA. IOS engineer Quantum Art, an established Web Content Management System. CEO of Oumobile, Strategic execution of mobile apps studio. (8)
COO: Artem Baranov, Founder of IT companies in development outsourcing, medicine, and financial analytics. A member of St. Petersburg cultural life and start-up movement. ITMO lecturer. (9)
In 2018 they will begin to implement their global marketing plan. They are also planning to implement a significant expansion of their analytical and predictive product range and to undertake work of a broad scope to increase its value and improve its usability. An extensive explanation can be found in their Medium post. (10)