Our clients have taken various paths in leveraging analytics, data science, analytics engineering, and artificial intelligence.

The following are example case studies, illustrating typical client results:

Fortune 100 international financial services firm

• Challenge:  Transform firm’s global anti-money laundering (AML) and Know Your Customer (KYC) controls program
• Results:  Developed and implemented comprehensive enterprise-wide AML/KYC program including:
  • Customer risk ranking
  • KYC management reporting
  • Onboarding workflow enhancements
  • Customer periodic reviews
  • Customer screening for political exposure, negative news, and sanctions
  • Updating firm’s global AML/KYC policies and procedure
• Challenge:  Ensure consistency of evaluating AML customer risk enterprise-wide
• Results: Developed methodology to create innovative and industry-leading customer risk ranking capability including:
  • Methods for applying statistical and machine learning techniques to create industry solutions requiring transparency and traceabilityCollaborated with AML Compliance and IT teams to design, develop, and deliver enterprise-wide utility
• Challenge:  Fragmented customer data activity inhibits firm’s ability to evaluate customer risk comprehensively
• Results:  Worked with outside vendor to integrate multiple disparate data systems to enable single view of customer and account activity for AML investigatory analysis

Fortune 150 oil refiner and marketing company

• Challenge:  Enhancing capabilities of internal analytics teams with latest in data science
• Results:  Delivered Fundamentals of Data Science training to IT, analytics, and business analytics professionals as organization moves into advanced data science

Fortune 100 American multinational technology conglomerate

• Challenge:  Increase adoption of IT-provided data and analytics services to business units
• Results:  Created community of predictive analytics business partners including:
  • Promoting use of predictive analytics among business analyst teams
  • Identifying approaches to connect IT and business groups for more integrated operations
  • Gaining insights into various business operations, such as sales, operations and marketing
  • Increasing engagement among business analysts by over 200%

Leading California-based public healthcare agency

• Challenge:  Improve the agency’s capability in generating data-driven insights
• Results:  Assisted client in standing up data science capability including:
  • Hadoop-based infrastructure and Data Science center of excellence
  • Recommendations for operationalization, scaling, management, deployment, and continuous improvement of automated detection and decision analytics technologies
  • Demonstrated capability to identify durable medical equipment (DME) fraud claims

Top 5 US bank

• Challenge:  Enhancing bank’s ability to mitigate money laundering risk associated with banking customers
• Results:  Developed comprehensive and integrated advanced analytics strategy including:
  • Assessment approach of third party data sources in mitigating customer risk
  • Methodology for using machine learning approaches for detecting suspicious activity and assigning customer risk in AML compliance programs
  • Consistency with regulatory expectations and enabling transparency in alert disposition and customer due diligence decision making

Global Fortune 100 multinational technology and engineering company

• Challenge:  Anticipate industry changes due to evolution in urban mobility
• Results: Develop technical requirements relating to big data and analytics for city mobility platform, analyzing urban patterns of life behavior

Fortune 150 global network serviced provider

• Challenge:  Aligning capabilities of IT and analytics in rapidly changing corporate environment
• Results:  Advised IT and advanced analytics organization on the following:
  • Optimal organizational approach when affected by budget reductions, hiring freezes, personnel changes, and business unit restructuring
  • Agile strategy development to enable digital transformation, institute consistent data governance standards, and accommodate evolving technologies

British multinational banking firm

• Challenge:  Assess adequacy of bank’s AML transaction monitoring program
• Results:  Conducted detailed evaluation of AML program including:
  • Deep dive review of AML transaction monitoring system
  • Recommendations for enhancements and improvements

Association of major Fortune 500 CAOs

• Challenge:  Tracking and understanding the value and ROI of analytics
• Results:  ROI and business partnership strategies including:
  • How to calculate the ‘return’ part of the ROI so that business partners and CFOs believe the numbers
  • How to ‘share the credit’ of successful analytics projects with partners in IT and business
  • Techniques that make the ROI discussions more effective/successful

Information Management Solutions developer

• Challenge:  Machine learning and AI for smarter performance
• Results:  Specific approaches for:
  • How organizations can leverage ML and AI to make smarter performance decisions
  • Doing so in environment with decrease in both human and technology resources

International office furniture manufacturer

• Challenge:  Where to start in employing artificial intelligence and machine learning
• Results:  Developed several success stories regarding AI including:
  • Where to start
  • Providing training to senior leadership
  • Setting appropriate expectations
  • Defining organizational changes for rollout

Fortune 50 multi-national consumer goods corporation

• Challenge:  Automating internal financial controls
• Results:  Developed approaches for moving from manual to automated processes including:
  • Mitigating human error and false positives
  • Methods for rolling out these new processes
  • Identifying ways to make the cultural shift to continuous and automated control
• Challenge:  Building a toolkit for business analysts
• Results:  Strategies for incorporating commercial and open source tools for data science teams including:
  • Being adaptable to rapidly changing toolsets while establishing standards across teams
  • Leveraging innovation while mitigating risks associated with open source languages and libraries

Fortune 100 American petroleum refining company

• Challenge:  Keeping up to speed on the latest AI and data science technologies
• Results:  Roadmap for supporting and enhancing analytics team capabilities including:
  • Prerequisites for application of AI
  • Measurements for success for AI solutions
  • Skillsets and approaches to keep team advancing and adaptable to evolving marketplace

New Zealand-based software company

• Challenge:  Gaining fresh ideas and insights regarding data science best practices
• Results:  Strategy for attracting members to a data science advisory board

Fortune 100 multinational conglomerate

• Challenge:  Identifying best areas for analytics investment
• Results:  Strategies for determining return on investment including:
  • How to develop strong partnership with business stakeholders
  • Prioritizing projects
  • Focusing on stakeholder champions, quick wins, and success stories to secure greater adoption

Major US-based international pulp and paper company

• Challenge:  How to leverage cloud computing to support analytics development
• Results:  Approaches for enabling teams with latest tools including:
  • Being adaptable to rapidly changing toolsets, such as open source, while establishing standards across teams

Telecommunications optical transmission equipment manufacturer

• Challenge:  Improve alert analytics capability to predict network equipment failure more accurately
• Results:  Demonstrated predictive network intelligence capability including:
  • Identifying potential equipment failures, laying groundwork for smart and self-healing networks
  • Creating metrics predicting probability of failure for each network component

American regional banking firm

• Challenge:  Identify sources of banking systems leading to inaccurate assessment of user fees
• Results:  Conducted thorough code assessment, identifying gaps and recommendations for upgrades

Top multinational payment processor

• Challenge:  Ensure alignment of AML and fraud detection policies with state-of-the-art and regulatory expectations
• Results:  Developed program for program assessment and provided improvement recommendations for AML and fraud reduction

Institutionally-backed fintech startup

• Challenge:  Allow end-user data analyst teams to shortcut much of the data wrangling steps usually required in data science and analytics projects
• Results: Helped team stand up a data refinery platform, which included:
  • Ingesting data in raw form and in multiple, disparate formats
  • Building automated, easy-to-use functionality to wrangle, curate, enhance and make ready for use by end-user analysts