Issues (Risk) Correlation & Consolidation Analysis
Issues (Risk) Correlation & Consolidation Analysis Back Objective Each of the issue description in the risk management network was compared against each others to Compute the similarity of the descriptions Flag the descriptions that has a similarity score above a specific threshold for further review and analysis Ability to compare the issue similarity within / […]
Hybrid Cloud Analytics
Hybrid Cloud Analytics Back Objective Develop a 2 year strategy and phased roadmap with a central vision and foundation to ensure that future business needs for data and analytics are met Industry: Healthcare Wholesaler Services: Transformation Enablement Technology: Data Architecture Assessment Increased revenue due to improved insights into customer behavior. Improved margins via insights into automation, inventory, and warehouse operations. […]
Data Strategy Implementation
Data Strategy Implementation Back Objective Implement a common data layer in EDL following the best practices of AWS and Databricks to ensure that current and future business needs for data and analytics are met across the various enterprise teams. Industry: Agriculture and Construction Machinery Manufacturing Services: Transformation Enablement Technology: Data Architecture and Data Management Increased sales volume by […]
ML/NLP for Risk Mitigation & Quality Control
ML/NLP for Risk Mitigation & Quality Control Back Objective Our Risk Identification and Quality control framework is an approach with machine learning and natural language processing to prepare enterprises to identify challenges proactively and address them on an ongoing basis. Industry: Financial Services – Banking Services: Technology Innovation Technology: ML/NLP Analytics Reduced overall human capital costs […]
Automated Issue Mapping
Automated Issue Mapping Back Objective The issues stemming from multiple systems and associated domains need to be mapped the corresponding Domain/class. This will eliminate the human manual mapping process and the need for multiple hierarchical review processes and accurate reporting on time. Industry: Financial Services – Banking Services: Technology Innovation Technology: ML/NLP Analytics Reduction in human […]
ML-aaS Platform Architecture
ML-aaS Platform Architecture Back Objective Assess the client’s AI/ML platform needs and gaps to recommend solutioning approaches that would enable their strategic goals of data and AI/ML models monetization. Industry: Financial Services – Payments Services: Strategic Advisory Technology: AI/ML Strategy Democratization of data to the data science and data analyst community within the enterprise. Provided […]
AML & Fraud Detection
AML & Fraud Detection Back Objective Complement traditional AML and fraud analytics with social network analysis. Uncover nuanced time-evolving connections between entities to surface suspicious activities for review or feedback. Industry: Financial Services – Banking Services: Technology Innovation Technology: Social Network Analysis 8% previously unidentified (new) relationships that held promise were identified vs. manual review […]
Optimizing Order Fulfillment
Optimizing Order Fulfillment Back Objective Identify the root-causes of delivery delays to: Improve customer experience & satisfaction Reduce penalties incurred for not meeting service-level agreements and maximize revenue recognition potential Mitigate the risk of customer attrition due to recurring service-level defaults Industry: Healthcare – Wholesaler Services: Technology Innovation Technology: Predictive Machine Learning Optimize logistics and […]
Scaling Enterprise Analytics
Scaling Enterprise Analytics Back Objective Assess the client’s AI/ML platform needs and gaps to recommend solutioning approaches that would enable their strategic goals of data and AI/ML models monetization. Industry: Global Life Sciences Company Services: Strategic Advisory Technology: Analytics Center of Excellence Improve business agility to respond to market/ competitive threats and regulatory demands. Respond […]
Customer Lifetime Value
Customer Lifetime Value Back Objective Develop customer analytics, inclusive of purchase behaviors, store vs. eCom engagement and source channel usage Demonstrate the scalability and elasticity of MS Azure cloud services for data management and analytics Industry: Shipping and Delivery Services: Technology Innovation Technology: Graph Analytics & Machine Learning Established customer identification as a critical step […]
