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CST Project Case

CST is involved in full stack technology projects that span many industries. It’s how to approach projects that set us apart. Our clients quickly feel the measurable quality CST brings to projects in a diverse range of industries and technology applications. The following are a few case studies to illustrate the varied application of CST consultancy and technology solutions: Note that it is intended that specific client’s names are not mentioned here in the identification of projects. CST solutions provide our clients with real industry advantage and in many cases, have CST sign non-disclosure agreements to protect intellectual property and competitive advantage.

Apex Bank:

Problem Identification: CST worked with this client to identify gaps in its core regulatory functions. It was agreed that the following was required:

  • Real-Time Transaction Monitoring
  • Real-Time fraud detection
  • Real Time Data analysis and pattern learning of transaction data.
  • Predictive analytics
  • Threshold-based alerting.
    Solution: CST worked with the client to design a system that collects banking transaction data in real time and performs real-time analysis, fraud detection, and cognitive predictive analytics of transaction trends and patterns and provides regulatory insight and recommendation of future strategies. The system also supports a robust reporting and alerting framework that functions independent of users.

Police Force:

Problem Identification: This client collects both intelligence and publicly reported data of crime in its coverage area. This data includes structured and non-structured data including biometric data. This is complicated by the fact that organized crime gangs also operate in the area. The client wanted the following:

  • A way to identify gang members and their wider network using available information like phone calls and past associations.
  • Solutions that will also monitor gang member’s already in jail and learn the effect of imprisonment and release trends on crime in the area.
  • Identify nonviolent younger crime members for rehabilitation.
  • To better focus policing to meet the needs of the community by targeting high-risk areas and using police presence to prevent crime.
  • Identify crime trends and predict next crime hotspots.
    Solution: In this case, CST forward deployed engineers engaged with the client to identify the technical infrastructure to accommodate the ever-increasing data storage and security gaps in existing systems. Once an agreed infrastructure was implemented and the solution clearly identified and agreed, the engineers designed a cognitive platform that made sense of all the data collected and ran predictive algorithms to first learn from the crime trends and create predictive models that provided the client with 94% accuracy of future crime hotspots. In addition, the solution identified younger gang members and alerted the police before they committed a serious crime. This support of preventive policing is exactly the kind of measurable value CST is committed to providing to its clients… in any industry, it works in. It is not just enough to talk about it …we want to take an active part in problem-solving.

Oil and Gas:

Problem Identification: TThe fundamental changes in the global hydrocarbon markets drive more production and exploration to a focus on shale and other less-accessible deposits. The oil and gas industry must increase CAPEX investment to identify and extract those new deposits while simultaneously reducing the environmental, health and safety risks of bringing that resource to market.

Global changes in the availability of data are also underway, changing the petrochemicals business in ways similar to recent changes in telecom, retail, and manufacturing.

Advances in instrumentation, process automation, and collaboration multiply the available volume of new types of data like a sensor, geolocation, weather, and seismic data. These can be combined with “human-generated” data like market feeds, social media, email, text, and images for new insight.

In this case, our Client  required the following:

  • A security assessment of its infrastructure.
  • Sensor-based monitoring of wells in exploration in partnerships.
  • Identify opportunities for Log Well Analytics and recommend solutions.
  • Predictive Models for reliable yield predictions.

Solution: CST performed the security and infrastructure audit and identify areas of improvement including a security re-approach.Once the infrastructure was secure CST worked with the client to understand its sources and how these can be used for trend and predictive modeling.

CST deployed a sensor-based system that tracks and stream data from its exploration fields into a central location for modeling and analytics. CST data scientists then got involved to use the data to create a reliable predictive model requested by the client.