Irish Tech News met with Jane Zavalishina @ at the EnterConf Web Summit event in Belfast. Jane was on the panel discussing how digital revolution allied with big data insights are transforming the entire financial services sector. Here is a deeper dive into her thoughts on how the industry is developing and her take on MoneyConf.
How was the MoneyConf Web Summit for you?
For a conference that was held for the first time, it was really impressive. Very interesting set of speeches and panels, enthusiastic and appreciative audience, plenty of networking opportunities – I liked it a lot!
— Andy O'Donoghue (@ADODonoghue) June 19, 2015
What did you find useful / interesting?
It’s always fascinating to see so many energetic start-ups, trying to reinvent the most conservative industries like finance. Fintech has been a hot topic for the last few years, and MoneyConf have provided great insight into a current state of innovations in the industry.
— Colm Lyon (@colmlyon) June 15, 2015
Where Yandex hope to go in the future?
Being the leading search engine in Russia – and the 4th largest search engine in the world – it was natural for Yandex to begin expansion to the new territories. That’s what Yandex started in 2011 by launching its Turkish search and web portal.
One much less obvious direction is the one Yandex opened in 2014 by launching Yandex Data Factory: completely different business model, based on the same set of core technologies.
This new business is based on the idea of applying the technologies that helped us become the leader in search – big data analytics, very advanced machine learning technologies – to other industries working with large amounts of data.
A few years ago, our first pilot projects with CERN proved that our Internet technologies are universal enough to be successfully applied to the big data issues in science; in 2014, we decided to bring them into the business world. Telecoms, retails, manufacturing companies, and of course, banks and financial enterprises are among our clients.
Potential applications of machine learning and big data analytics are almost unlimited. We can use it to predict what a customer is going to buy and make the best recommendation. We can foresee when a customer is about to stop using the service and suggest the best action to prevent it. We can predict when some equipment is about to fail so it could be replaced before a service disruption happens. We can optimise hiring of new personnel based on a prediction of who’s probably going to fit in. And it goes on and on.
In many cases, human expertise will soon be replaced by machine learning algorithms, that can provide better results than humans when it comes to getting measurable business value from large amounts of data. Humans simply cannot take into account as many factors as a machine can. Moreover, algorithms are quickly evolving and will get only better with time, when human analysis and expertise has its natural limits.
So, in the not too distant future, the technologies born and bred in the Internet can lead us to the next industrial revolution, significantly improving efficiency in many different industries!
What tips do you have for other new companies?
Constantly test your ideas against the market, do not fail by being the victim of your own judgment – talk to your clients, partners, to understand what they really need.
At the same time, keep in mind that building an innovative business is a marathon, not a sprint, so be ready to invest your time and be patient. Choose investors who share your long-term vision, rather than focused on short-term success.
How can people find out more about Yandex Data Factory?
Yandex Data Factory are the Machine Learning and data analytics experts that use data science to improve business’ operations, revenues and profitability. By building upon the real-time personalisation and predictive analytics technology of parent company, Yandex, the fourth largest search engine in the world, Yandex Data Factory helps clients improve their business awareness through the exploitation of their own data.
E-mail [email protected]