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Maximise player engagement & satisfaction

Challenge:

In a multi-room, multi-game environment what are all your players doing right now?  With 500,000+ players, in multi-room, multi-game environments spread across the globe…   The challenge is to intervene with individual players to reduce churn and improve conversion.  Creating a “player journey” to track each player and identify the most appropriate intervention points in real-time.

Solution:

Using a mixture of data relationship discovery, data analysis, pattern […]

By |January 20th, 2016|Algorithms, Analytics, Data, Gaming, Pattern Recognition|

Liquidity Risk Management

Challenge:
Volumes of data are increasing rapidly due to cash flow orientation and banks are struggling to perform finance and risk management in real time.  This is especially acute for liquidity risk management where the current spread sheet applications perform slowly due to the massive amounts of data.  Compliance with new liquidity rules under Basel III is a must and especially […]

By |December 20th, 2015|Data, Financial Markets|

Faster retail analytics

Challenge

Help a Large fashion retailer that was taking 36hrs to process 2 years of ePoS data (8 Billion records) within the traditional business intelligence system. (Microstrategy & Oracle). Merchandising team required predictive analytics and better performance to enable calculations on sales data to enable stock to be in the correct stores for the following week. (Calculations would include last week’s […]

By |November 20th, 2015|Analytics, Data, Retail|

Back to the Future

Taking a timely theme and looking at the way in which fraXses is helping organisations to move from the “rear mirror” view of static reporting, swiftly through the current ability to deliver real-time, streaming data analysis and into the predictive and prescriptive analytics.  

Descriptive analytics: means looking at historic data, ranging from 1 minute ago to years ago. It can […]

By |October 21st, 2015|Analytics|

Maximising revenue by keeping planes off the ground

Challenge:

Airlines need to identify the ideal times to fly to maximise demand, match capacity to demand and meet all operational requirements.  While at the same time establishing how to design their flight schedule in such a way as to maximise revenue.  With an almost infinite number of possible combinations, this process is inefficient and leads to higher costs and […]

By |October 20th, 2015|Algorithms, Data, Machine Learning, Pattern Recognition|

Optimising sales pipelines

Problem:

Without a doubt, the current environment is extremely challenging for sales teams in every industry and region.  Enabling them to react quickly to changing sales conditions could literally mean the difference between overachieving the quota or failure.

Knowing exactly what is happening in your sales pipeline and being able to respond quickly to changes as they appear is critical for every business. […]

By |September 20th, 2015|Analytics, Data|

Stopping the fraudsters

Problem:
For insurance companies, the fraud can range from the use of stolen credit cards, collusion and identity theft. According to the Insurance Fraud Bureau (IFB) in the UK, undetected general insurance claims fraud total £2.1billion a year adding on average £50 to the annual costs individual policyholders, on average, each year.

A growing phenomenon is the “Cash for Crash” scam in […]

By |August 20th, 2015|Fraud, Insurance, Pattern Recognition|

Visualisation libraries

Enterprises are beginning to realise the important role “big data” plays in achieving business goals. Concepts that used to be difficult for companies to comprehend— factors that influence a customer to make a purchase, behaviour patterns that point to fraud or misuse, inefficiencies slowing down business processes—now can be understood and addressed by collecting and analysing big data.  The insight gained […]

By |July 20th, 2015|Analytics, Data|

Pattern recognition for cross selling

Up-Sell/Cross-Sell Recommendations
Providing up-sell and cross-sell recommendations to customers is the mostly widely adopted big data use case in the retail sector. This enables retailers to increase online purchases by recommending relevant products and promotions in real time. Retailers can recommend products based on what other similar customers have bought—providing upsell, cross-sell or “next best offer” opportunities.

fraXses provides real-time capabilities that […]

By |June 20th, 2015|Machine Learning, Retail|

Gambling behaviour analysis

Working in both the online and actual casinos we help the operators work with the vast volumes of data generated through the gaming activity.

We predict players that are going to leave the casino before they actually leave. With this information, the marketing team can intervene with a retention strategy before their players leave.

We also have the ability to predict how […]

By |May 20th, 2015|Algorithms, Gaming, Machine Learning|