market making experience, incorporating techniques of portfolio management that are closely aligned to financial fund management. Being able to decipher how you should react to information contained in an anonymised data set is challenging enough, and in itself is a huge barrier to entry.
However, beyond that, you need to build the models and infrastructure that can incorporate and process this information with zero latency and that requires a very different technical stack to the basic algorithmic models producing generic derivative markets that are prevalent elsewhere. Incumbent suppliers are poorly equipped to pivot to models that can react to this proprietary information - even if they can work out a way to distill it - which is why price followers cannot become price leaders quickly, if at all.
Your integrated alpha solution claims to offer higher profits and efficiency for operators. How does it accomplish this?
In financial terms, generating alpha refers to generating profits in excess of the rest of the market. Generating alpha isn't the same as a supplier offering a service that improves returns by 10% if the existing solution is 10% worse than the market to start with - this is simply achieving parity. 10star generates alpha through a variety of methods, which either have high barriers to entry - such as the model and data inference processes already described - or through the asymmetric information captured
through our proprietary trading processes that can't be replicated elsewhere.
Tis combination of advanced modelling, unique data analytics and greater knowledge of market liquidity creates an enduring best-in- class proposition for our partners.
10star's founding team has its roots in Jasis, a tennis betting syndicate. Why is this relevant to your operation now and how does it set 10star apart?
Alongside supplying pricing on a B2B basis to operators such as Pinnacle, Jasis is also a dominant market maker on the exchanges, so we are experts in dealing in zero latency, low margin trading and handling anonymised liquidity. To do this successfully, you need to build models and understand the market in a completely different way to anyone else.
B2B supply means we must produce a raft of markets that always have to be available, and both the exchanges and Pinnacle have a "winners welcome" policy. Te fact that they don't kick out customers means our prices, trading and risk management expertise has to be on a level that is way above that which other B2B suppliers are capable of.
All of our models are highly automated, perfectly correlated and risk driven, meaning there is no weakness in any derivative and are also fully extensible across in-play. Put
together, we feel we have an operation that solves problems for sportsbooks in ways that B2B solutions cannot.
Why do you think operators fail to make the most of their existing data?
If you go onto a modern trading floor it isn't unusual to see some form of BI reporting tool surfacing objective reports from a sportsbook's underlying data, and in respect of personalisation and customer management, some sportsbooks are using data in really interesting ways.
However, because of the way the industry has evolved in regard to attracting recreational customers and removing more skilled ones, there is no experience of modelling customers in the same way as there is of modelling sports.
Not only that, but modelling customer behaviour and being able to decipher meaningful predictive outcomes from it is a much harder task. Tis is why we're seeing so much market interest in our neural product: we are able to surface outputs to operators based on betting data that is proprietary to them and which they already possess, but previously have had no means of accessing and monetising. In turn, because these data outputs are incorporated into our integrated alpha solution, we're using real-time data processing in a way which is moving the profit possibility frontier for our partners, and ultimately for the industry as a whole.
NEWSWIRE / INTERACTIVE / MARKET DATA P109
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