With Autochartist launching its new futures facing technical analysis brand, Delkos Research, Finance Magnates caught up with Autochartist CEO Ilan Azbel to learn more about the company’s plans and hear his thoughts on the state of affairs of the fintech sector.
With the launch of Delkos, Azbel explained that a major trend he is seeing is the need for on-demand data analytics products. In this regard, he stated that interest is growing for data solutions among different product lines. For example, in the trading world, startups with offerings to track social and news related sentiment have been gaining traction, although whether true trading value exists in these products is yet to be seen. They’ve also attracted rising valuations from venture capital investors as their products have to be able to provide benefits to hedge funds and traders.
Elsewhere, Azbel noted that there is growing interest from banks and brokers for analytic data to better understand their customers to improve retention results, decrease customer acquisition costs, and increase their long term value (LTV). While technology for such features has been available for several years and many firms license such products, there is very little adoption of actually using analytics to improve business decisions. Nonetheless, Azbel explained that he was viewing an increase of firms beginning to start adopting big data analytics within their workflows.
Data through APIs
Causing the favorable sentiment towards using big data, Azbel cited several factors. The leading cause is the commoditization of the trading industry. As such, brokers and banks have become more inclined to license trading analytic tools to provide their customers to distinguish their services from competitors. In addition, as profit margins contract, using customer analytics provides an opportunity to increase LTV of clients. Specifically, Azbel noted more interest from futures and stock brokers due to lower profit margins in more mature markets.
APIs as one of the best means for fintech firms to distribute their analytics solutions
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With many brokers operating proprietary front and back end platforms, Azbel stated that he viewed APIs as one of the best means for fintech firms to distribute their analytics solutions. He explained that using APIs provides one with the ability to embed analytics within their own platforms or back office solutions.
Among emerging fintech niches, one area that Azbel noted was what he called ‘compliance analytics’. Following on the big data trend, he related that an up and coming market are tools for companies to better monitor their employee’s public social profiles. With rules governing how brokers promote products such as stocks or investment offerings, a compliance risk exists when employees comment on social channels about trading and investments.
Another area of note was our discussion about trading platforms, specifically algorithmic systems targeted at retail traders. As an investor in Seer Trading, Azbel has experienced that platform’s difficulties in marketing to the retail market, before finding a comfortable niche with asset managers and semi-professional traders. According to Azbel, “The primary challenge in the retail space is finding traders that actually create value for investors; the playing field has been perverted by copy-follow platforms that have created volume-based incentives instead of performance-based incentives.”
The sector itself has seen a minor explosion of platforms that provide algorithmic trading to retail investors. Included are Ninjatrader which is used primarily for futures and the ever popular MetaTrader 4 platform. Newcomers include QuantConnect and Quantopian. Going forward, Azbel related that he was watching whether professional algorithmic traders contribute any significant strategies to these platforms.
Despite technical advantages that newer platforms are able to provide the retail sector, the reality is that there exists a large barrier in terms of onboarding customers due to skills required for coding. As such, a gap exists where the more complex systems are beyond the capabilities of the vast majority of retail traders, while simpler systems that use drag and drop strategy builders tend to underperform. Conversely, Azbel believed that it is a lot simpler for a professional algorithmic trader to get trading capital from prop desks instead of fighting for the attention of fickle retail investors.