Real-time analytics has finally given the fast paced gambling and gaming industry a chance to stay ahead of its data. In order to balance commercial profitability as well as customers’ safety and satisfaction the industry must seize the opportunity to extract data insights into what is happening now, rather than simply studying the past.
A successful business intelligence system in the gambling industry should be able to collect data from multiple sources (e.g. in-game data, clickstreams, social media profiles, payments and transactions, marketing or ad performance among many others). There is great value in analysing, comparing and correlating these different streams as data is received, in real-time, as well as comparing them against historical stored data. Real-time processing means that companies can instantly respond to customers as well as predict or anticipate future behaviour of players.
This is useful throughout the organisation, but one team in particular should be relishing real-time big data: the risk and compliance team.
Here are our key reasons why:
Identifying addictive behaviour and problem gambling
The key aim for businesses is to make use of their vast pool of customer data to meet the requirements of legislators and regulators without disrupting the customer’s experience. This means taking a proactive approach to identifying problematic behaviour.
One approach is to comb historical datasets for users showing worrying patterns. But the risk of a retroactive approach is that corrective action is left too late and the damage is done. A real-time approach increases the chances of catching problems in time, but making sense out of disparate sources of streaming data isn’t easy.
One solution is for companies to build machine learning models, which ‘learn’ the profiles of normal player behaviour. Once these profiles have been built, real time analytics can be used to predict the probability of a player having an unhealthy addiction when there are disruptions to the normal behavioural patterns. This can be used to alert a gambling or gaming company when a player exhibits addictive habits, so that the company can potentially intervene and take corrective action.
Fraud detection and credit risk
In online gaming, there is often a large volume of credit card payments. Many companies also offer newly registered users free credit as an incentive.
The motivation is there for shadier players to try and abuse these offers with multiple or fake accounts – a practice known as ‘bonus abuse’ – effectively defrauding the company. At significant enough scale, this could even feed into the company’s credit risk.
Other fraud risks include legitimate accounts being hijacked, or stolen credit card details being used to place large bets.
Fortunately, predictive analytics can be used to prevent abuse by building a picture of normal account activity and flagging up suspicious patterns.
Analytics for Anti Money Laundering (AML)
There is an increasing amount of regulatory compliance pressure applied to casinos to reduce risk, especially when it comes to money laundering. In fact, casinos are regularly fined millions of dollars for flouting AML laws.
Therefore, much like banks, gaming and casino companies stand to gain a lot from automating their processes for combatting AML. Automated detection software can help to increase the detection rate of suspicious activity, while reducing the investigation time. By aggregating patron and transactional data, compliance staff can more quickly get to the root cause of suspicious activity.
Privacy and Data Security
With data and privacy breaches making headlines every day, companies need to be proactive and think carefully about security with any big data initiative. Companies often suffer from informational chaos, where different types of data are scattered in an unorganised way across an organisation. This is a risk, as it undermines any efforts made to protect that data.
The right big data platform can ingest these data sources regardless of where they come from and store them securely, giving the right people the access to the data they need.
Casinos and online gaming companies play for high stakes themselves. Get it right, and you have a profitable and responsible business. Get it wrong, and you’re open to huge operational risks related to fraud, credit, money laundering, data breaches and issues around addictive behaviour. Though by no means a magic bullet, a sophisticated approach to real-time analytics on streaming big data can increase the odds of getting it right.
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