Accelerate your business with intelligent, predictive solutions generated from your data.


Deepen consumer relationships and improve CX through targeting, personalization and automation


Improve clinical trials and research, enable earlier diagnosis and enhance treatment

Nonprofits & Associations

Yield a more engaged member base and more productive development efforts through better knowledge of donors and members

Financial Services & Insurance

Enable claims forecasting, predictive modeling, fraud detection, portfolio management, and product development

Our Machine Learning Proof of Concepts Create Algorithms and Models to Help You Better Understand, Predict, Strategize and Operationalize.

Machine Learning Enables Faster Decision Making and Improved Applicant Experience for Insurer

A large insurer utilized cumbersome processes for reviewing, analyzing and passing determination on applicants seeking insurance coverage. As a result, the decision-making process and turnaround time on applications were lengthy. Underwriting staff were overwhelmed by their caseloadsIn addition to having an impact on employee engagement and creating a negative experience for customers, the company found it was losing business to competitors who were able to respond more quickly. The organization sought to remedy the issue by automating some of the review process.  

Over the course of its history, the company had collected a significant amount of data from its applicants and subsequent claims data and had specific outcomes associated with its dataset. This presented an opportunity to utilize machine learning through the development of a set of algorithms and its application to future data. This model would generate outcomes using a “stoplight process” to quickly determine applicant viability, whereby Green results were pushed through and deemed as suitable applications with no human intervention, Yellow required additional review by the underwriting staff and red were denied and sent to affiliates and third-party insurers for consideration.  

As a result of the machine learning initiative, underwriters and additional resources saved an estimated 66% of their time in the review process, yielding valuable cost-savings to the company and increasing employee engagement. Applicants received timely responses to their applications and benefitted from an improved experience.  

Our machine learning proof of concept approach:

Data Analysis

Ensure data quality, identify opportunities to enrich dataset, then structure and integrate your data for the ML process

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POC Development

Identify an ML algorithm and approach for your data, and build POC

Model Development

Your POC is formalized into a repeatable process; further cycles with additional data will improve the model while subsequent models can be created to compare differing results

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Application of the model through integration with existing processes and systems

As a result of the machine learning initiative, underwriters and additional resources saved an estimated 66% of their time in the review process.

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Learn how your data can help you predict, strategize and operationalize for the future.