Distilled Analytics Releases the Distilled IMPACT Behavioral Analytics Model

Solution employs computational behavioral models derived from big data refined by machine learning systems.

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Distilled Analytics has released Distilled IMPACT, an innovative approach to providing quantitative measurement of nonfinancial factors associated with for-profit investment that uses advanced behavioral analytics supported by artificial intelligence.

The rapidly growing field of impact investing is facing a spiraling need for better tools to measure and manage the nonfinancial factors that accompany investments. “Efforts to rationalize impact have been going on for more than a decade with limited success, in part because of subjectivity, statistically imprecise techniques, and a reliance on incomplete data,” said Distilled Analytics founder and chief executive David Shrier.

Distilled IMPACT provides a granular assessment of impact, tackling the hard-to-measure human factors, and provides a numerical assessment. In the past, investors had to rely on surveys, opinion, and other qualitative, subjective approaches.

Distilled Analytics offers a suite of tools focused on predictive models that can provide deep insight for financial professionals. Its artificial intelligence platform taps machine learning technologies to ingest unstructured and structured data. It analyzes complex patterns to calculate outcomes in areas as diverse as economic development, public health, and crime reduction.

The proprietary and transparent Distilled IMPACT platform quantifies nonfinancial activities using discrete measures, particularly around human factors, to enable asset growth for impact investing by providing greater trust and transparency. It helps organizations understand impact by analyzing patterns of movement from aggregated and third-party data sources, revealing fundamental insight into human behavior.

Distilled Analytics solutions transform financial services with behavioral analytics. The company builds on years of research from MIT, University of Oxford, and Imperial College London to address some of the biggest challenges facing the financial industry today, providing improved credit risk prediction for consumers and businesses, more efficient anti-money laundering and know-your-customer compliance, and quantified effects of social capital. The innovative Distilled Analytics platform offers AI-driven data science that delivers more accurate and timely risk assessments to expand lending portfolios, much higher resolution identity resolution and predictive models focusing on money laundering, and the ability to increase assets under management for impact investing. 

To learn more about Distilled Analytics, visit


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