Crypto corner: How AI can help support the surge

The influence of cryptocurrencies within the igaming industry is ever increasing since entering the space around 2014 and this means greater responsibility for online casinos and bookmakers.

Technology is the catalyst for the relentless development of online casinos and sports betting and the appetite for cryptocurrency is only growing. Cryptocurrencies make it easier for players to frictionlessly access regulated markets and negate exchange rate issues. Another advantage is that players can deposit and withdraw funds quicker from anywhere in the world with fewer restrictions.

Depending on the type of protocols and coins used, handling fees can be significantly reduced if not removed completely. Another benefit is the decentralised nature of crypto, meaning users are not at the mercy of banks or other institutions, as the essence of crypto is that it’s a peer-to-peer transaction between users. Crypto cannot be counterfeited or spent-twice, making it the safest payment mode to use online.

Be ready

Despite crypto’s position of strength, AI is essential to support its growth in gaming. Operators must be capable of handling the surge of demand for cryptocurrencies and closely monitor behaviour to avoid rare, but occasional, instances of fraud. Operators should be able to anticipate players’ needs and respond in a personalised manner to enhance engagement and retention levels. One of AI’s best functions is shaping decision making from continuously collecting and optimising reams of data to provide personalised experiences through accurate predictions.

VIP identification

Historically, the value of cryptocurrencies has been fairly volatile. The sheer range of crypto available and the way they work make the operation increasingly complex. AI plays an integral role in filtering through the complexities by identifying and then best accommodating VIPs. Machine learning algorithms have the ability to analyse huge amounts of data, much faster than the average person, or multiple people can. VIPs depositing with different coins, huge fluctuations in value and a quickly changing landscape means that those who fail to implement AI will fall behind.

AML detection

AML revolves around customer knowledge (KYC), which focuses on due diligence and building highly detailed player profiles by verifying origins of funds placed into gaming wallets. It is incredibly difficult for teams to keep up-to-date with the newest forms of fraud, particularly with the rapidly changing crypto landscape. AI has the capability to analyse reams of data, remove false alerts and identify complex criminal conduct. Machine learning and AI delivers an accurate process of quickly identifying and deactivating cases that are false positives to direct efforts to solving real problems.

Personalised UX

Complexity of segmentation increases when crypto is in play as it brings with it very different player types. AI gives operators genuine insight across all of the business by democratising data and displaying it with clarity. Its ability to crunch data objectively offers a significant edge, as does the technology’s capacity to analyse billions of data points in rapid time. AI is also being used to adapt user flows and personalised journeys and this positively impacts CRM communications.

Data can be used to determine when best to send messaging and even, more excitingly, what content should be sent to help consumers. Not only do operators have to contend with personalising casino games, and sporting events shown on site but they now have to understand which crypto payments to promote, how to adjust their promotions accordingly, and how to segment this new wave of crypto-player. Machine learning is a tool in the bag to reduce this burden.

Jada Gaming CTO Josh Tromans-Jones has been working in the gaming industry for many years, both on the operator and affiliate side. He has led business intelligence and analytics teams throughout his career and has recently held positions as an CIO/CTO of some of the leading gaming companies. His focus on previous roles has been to improve business visibility into operations by improving reporting, data visualisation and data processing, as well as the use of analytics and techniques such as machine learning to solve complex business problems.