News about Empirica, FinTech and software development.
Benefits of robo advice
/in Algorithmic Trading, Digital Asset Management, Digital Wealth Management, Financial Technology, FinTech, News, Robo Advisor, Software Development/by empiricaBenefits of Robo Advice according to ESMA
Benefits to financial institutions
Benefits to consumers
Robo-advisers are systems that use algorithms to handle users’ investment platforms. And they may be threatening to upend the tremendous wealth management business that is international.
BI Intelligence predictions that robo-advisers will handle around 10% of overall worldwide assets under management (AUM) by 2020.
In a fresh report from BI Intelligence, we examine the marketplace for robo-advisory services, the motorists behind consumer adoption of robo- guiding the robo-adviser marketplace presents a chance to wealth management businesses that are conventional, and how startup robo-
As substantial legacy businesses start offering their own services counselors can triumph.
Big riches supervisors that are incumbent will not lose out to startups like Wealthfront and Betterment. Rather, they establishing their own products, which are scaling fast and are adopting the technology.
Consumers across all asset types are open to robo-advisers — such as the rich. 49% of the group would consider investing some of the assets using a robo advisor.
Many assets managed by robo advisers will come from those who have some investments.
Empirica in the press – ‘The age of robots … ‘
/in Algorithmic Trading, Digital Asset Management, Digital Wealth Management, Financial Technology, FinTech, News, Software Development/by empiricaOn the first of July 2014 large polish economic magazine Puls Biznesu published an article “The age of robots comes to Warsaw Stock Exchange’. Article is quoting, among others, Empirica’s representatives speaking on the topic of the growth of algorithmic trading in Poland. Excerpts below.
‘Popularization of algorithmic trading on conferences like this one is step in good direction, says Michal Rozanski CEO of Empirica, a company which delivers Algorithmic Trading Platform. Expert says that computers will never replace a human in all the tasks. First and the foremost machines are taking over the processes that human traders had to perform manually. ‘I am sure that the development of algorithmic trading will not change the soul of the markets. It will not change to the race of engineers. It is and always has been the race on new, better ideas.’ says Michal Rozanski.
In his opinion both small and big investors will benefit. ‘Appliance of algorithmic trading tools increases liquidity and descreases bid/ask spreads which in turn decreases transaction cost born by all investors’ adds expert.
Michal Rozanski stresses that appliance of algorithmic trading does not limit to transactions with shortt time horizon, e.g. counted in miliseconds. Each trader can designs algorithms adjusted for it’s own requirements. ‘Let’s imagine an investor who would like to open a large position on KGHM shares or futures on WIG20. To make it happen it’s best to divde the order to tens or hundreds of smaller orders, which allows to hide her intentions from other market participants. Investor remains anonymous and minimizes market impact of her large order.’ explains Michal Rozanski.
‘I am convinced that development of algorithmic trading can be a breakthrough moment in the history of our market, as long as we will treat the matter seriously and deliberately. On Wall Street share of algorithms in total turnover is estimated at 50%, in Europe at 40%, and in Poland still at below 20%. ‘ says Adam Maciejewski, CEO of Warsaw Stock Exchange.
Link to article…
Empirica holds workshop on Warsaw Stock Exchange
/in Algorithmic Trading, Financial Technology, FinTech, News, Software Development/by empiricaAlgorithmic trading workshop took place on 27th of July 2013 as a part of the second conference held by economic magazine ‘Puls Biznesu’ and Warsaw Stock Exchange.
Michał Różański, representing Empirica, held workshop on the practical aspects of selecting tools for algorithmic trading by financial institutions. He stressed and covered in detail, especially one aspect of algorithmic trading which is from our practical experience constantly undervalued – namely proper testing of algorithms.
Very interesting was also a lecture of Emil Lewandowski who showed an algorithm which was able to detect a flash crash an hour before it actually happened. Algorithm was implemented, backtested, executed and presented to all the participants our Algorithmic Trading Platform. It was indeed very interesting example of application of algorithmic trading!
Among other guest were representatives from IBM, Sungard, List and M10.
Link to event:
http://konferencje.pb.pl/konferencja/705,handel-algorytmiczny-cz-ii
Artificial intelligence in FinTech
/in Digital Asset Management, Digital Wealth Management, Financial Technology, FinTech, News, Robo Advisor, Software Development, Software Vendor/by empiricaFinTech : It is just starting
FinTech sector is producing businesses with scalable products and has seen rapid growth over the past few years. Senior executives at banks are responding to the challenge these companies have started by setting their own incubators up to capture this high-speed initiation.
Technology was once centralised, with companies being run on big databases and transaction engines. Nowadays, it is massively distributed. New businesses have sprung up to take advantage of the chances this shift brings, while leading banks still operate using the old technology. The term “peer to peer” captures some of the phenomenon, in that it is now potential for financial transactions to take place on a platform without needing a bank or indeed any entity as an intermediary.
The financial services marketplace is all about information exchange that is reliable, secure and efficient. In many cases the new alternatives can be cheaper and quicker than traditional models. A broad variety of potential models exist, which explains the increasing number of new fintech startups that have entered the market.
Needless to say, fintech is not new and technology has consistently brought gains to consumers. Back in the day, however, development costs were high, while the technologies of today are more broadly available, affordable and, most importantly, worldwide scalable.
The huge banks are setting up their own initiation arms to investigate opportunities presented not only mobile but also by by P2P and micro-payments cryptocurrencies like Bitcoin,, and distributed ledgers for example blockchain.
But as progressive as traditional financial institutions strive to be, they will remain hampered by their legacy systems and processes. I see the banking landscape continuing to change quickly as fintech businesses with talented management, viable products and clever advertising using new and traditional media take market share. Moving fast, nimbly and economically to capitalise on opportunities is the key.
Artificial intelligence in FinTech
Since its inception in the 1950s, artificial intelligence (AI) has found at least two major boom cycles and long winters of disillusionment. While artificial intelligence endured through the recent disullusionment cycle in the 1990s to today, its easing and corollary technologies have flourished, and we’re now entering into a fresh boom in applictions of the technology.
Financial services have been revolutioned by the computational arms race of the last twenty-plus years, as technologies like big data analytics, expert systems, neural networks, evolutionary algorithms, machine learning and more have enabled computers to crunch much more varied, diverse, and deep data sets than ever before.
While most of the businesses built around machines making decisions are’t true AI, they may be using data-intensive technologies that will help technologies and firms continue to get closer to executing AI in commercial applications.
Despite the hype of intelligent machines, the first uses of AI are’t replacing humans and human intelligence but augmenting them. Text-based conversational chat was adopted by many startups as a way to deliver a personal assistant-like expertise in many industries, and in fintech we’ve seen the case of businesses like Kasisto utilising AI to scale the impact of people using technology. Instead of being bounded in customer support uses by humans reacting to users through chat windows, AI and related technologies are being implemented to deliver a human-like chat encounter without the need for nearly as many human helpers.
By using smart agents that can examine and crunch data about individual behaviour and compare to broader datasets, small and big businesses could have the ability to deliver personalized financial services as a scope and scale never possible before. Consumer banking, advisory services, retail financial planning, investment advice and wealth management, all of these services can be delivered using a conversational user interface with artifical intelligence software behind. The combination of technologies can empower firms to supply services to customers where they were unable to supply human service profitably (i.e. lower net worth sections of personal financial, investment and retirement advisory), but can now function using codified knowledge and AI-powered software.
In addition to new segments, they are able to be more personal, supplying guidance at the transactional level (i.e. every individual transaction). This is the story behind smart wallets like Wallet.ai. Picture having an assistant with you to allow you to assess, price, and consider every single thing you spend money on, at a granular level that you could not be assisted by any human helper with. Is a roboadvisor that offers rule based advice using only a couple of predefined parameters AI? Likely not, but newer technologies as time goes by which are based around learning and viewing about your behaviors at the individual level, could give guidance and outcomes which might be personalized in a way never possible formerly.
AI can also power technologies that overlay humans to supply workers activities with an tracking and oversight mechanism, helping with compliance, security, and the observation of employee actions. Monitoring discrete, repetitive data entry tasks, computers could watch and learn as time passes to verify test and data entry for particular events, evaluate danger, and find fraud. Any segment of fintech that is regulated creates the chance for companies to install AI-powered employee and systems supervision.
AI technologies that allow computers to process information could augment underwriting and lending products and make decisions more easy and better than individuals alone. While it’s still to be determined how new data sets created by technologies like wearables and internet of things can be used for insurance and credit decisions, AI-based technologies make it more potential for businesses to use these new datasets in highly personal ways .
But AI is creating bigger opportunities to go beyond testing and fitting data to create trading systems and more “intelligent ” dealers, using robotraders to optimize and test predictions and trading rules. AI can help manage and augment rules and trading decisions, helping process the data and creating the algorithms managing trading rules.
Some investment firms have implemented trading algorithms based on sentiment and insights from social media and other public data sources for years, but technology companies like Dataminr are installing platforms for a larger set of businesses to use. Getting and utilizing large, heterogenous datasets is now potential for far more companies to use, so how will companies leverage and build on top of these datasets?
The future of AI in FinTech
While much of the investment in artificial intelligence has been into multi-purpose platforms which are figuring out their specific, high-value usecases, the chance in fintech is somewhat different. Fintech has a base of technological prowess in the technologies supporting AI and several immediate high value uses.
Initially, AI was used more in backend technology settings to power large scale decisioning in financial analysis , trading and lending, but now it is becoming a technology that expands how everybody interacts with financial services companies. A number of problems consumers are facing when using financial services are around the problems in getting to quality, personal service. And possibly it’s an artificially intelligent agent that helps deliver cheaper, private services that are better and faster.
Empirica founds IT Corner association to support local entrepreneurship!
/in News, Software Development/by empiricaEmpirica, along with several other software companies based in Wroclaw, has founded the IT Corner association.
IT Corner aims at supporting the development of local IT enterprises, tightening the cooperation among small and medium size high-tech sector companies and developing project and product synergies between organization members.
IT Corner will pursue it goals by:
- organization of IT events and conferences for larger audience
- regular technological meet-ups targeted at employees of IT Corner companies
- cooperate on larger IT projects with member companies
- know-how and best-practices sharing among management of member companies
- common presence on job fairs, IT events in Poland and abroad
First common events are already planned and will be officially announced soon!
The list of founding members encloses over 10 software companies employing altogether over 200 people. Till end of the year IT Corner aims to double its size and establish its position as biggest and most active IT association in Wroclaw.
More on: IT Corner site
Empirica with lecture at ‘Algorithmic Trading Conference’
/in Algorithmic Trading, Financial Technology, FinTech, News/by empiricaConference on the subject of ‘Algorithmic Trading’ was held at Warsaw Stock Exchange headquarters on the 28th of February 2013. The event was open by the WSE president, Adam Maciejewski. Among the invited guests were:
- Peter Van Kleef, Lakeview Capital president
- Michal Rozanski, CEO of Empirica
- Andrzej Endler, CEO of M10
- Michal Kobza, Warsaw Stock Exchange.
Michal Rozanski from Empirica made lecture on topic ‘Tools supporting financial institutions in algorithmic trading’. He showed not only common functionalities and architectures of available solutions, but also talked about practical aspects of hard decision every financial institution faces – to build software tools by own IT department or to buy from external vendors.
Very interesting was lecture held by Peter Van Kleef. Among other topics he shared his experiences from high frequency trading and how it has changed during last years.
We have informations that organizators intend to prepare soon another event relating to topic of algorithmic trading.
Link: GPW conference
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