Thoughtful AI for Financial Services

AI is poised to overhaul financial services, in many ways for the better. But such sweeping changes create potentially serious risks - to customers, to institutions, and to the health of the financial system.
Lucid's Keyur Patel & Marshall Lincoln consult with industry leaders, challengers and regulators to investigate these risks: how they arise, their potential consequences, and how they might be managed. Coming September 2019.

Published by:
​CSFI

Supported by:
​Swiss Re

Supported by:
​Endava
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Thoughtful AI
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Recent Articles
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Risks in finance
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Data Lab
The Lucid Analytics Project is an impact research firm which delivers reports, presentations, and consulting services.

​We focus on innovation in the domains we believe will make the most important contributions to sustainable development.

Impact Research

The Lucid Analytics Project is an impact research consultancy. Our primary focus is on technologies with the potential to advance sustainable development.

Areas of Focus

We focus on innovation in the domains we believe will make the most important contributions to sustainable human development.

Our Approach

We are investigative data journalists. Our reputation is built upon honest, objective, evidence-driven analysis.
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Data Science

We bring together the skills of data science practitioners and journalists, to deliver clear and lucid insights into this complex domain.​

Recent Articles

Is Human Talent the Limiting Factor? Financial Inclusion, New Data, and AI
​   Published by CFI Accion
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IMPACT - Part 2: Be a problem solver first, an engineer second.
   Published by Data Science Central

How AI can help solve some of humanity's greatest challenges - and why we might fail
   Published by KDnuggets

Our Founders' Research

CSFI reports, by Keyur Patel

Data science lab, by Marshall Lincoln

Impact Research
The Lucid Analytics Project is an impact research consultancy. Our primary focus is on technologies with the potential to advance sustainable development.
We call what we do ‘‘impact research’ for two reasons:
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  1. ​We investigate how innovation can help us confront the greatest challenges facing humanity - such as achieving the UN’s Sustainable Development Goals by 2030.
  2. We transform data around global trends into lucid, incisive, and actionable insights - to drive impact through our research.​
At the heart of our work is the principle that technologies are not synonymous with solutions.

​We believe that the greatest obstacles to tackling the world's most urgent challenges is not an inability to conceive ingenious technologies, but to create incentive structures that enable them to make a global impact. We are obsessive about how innovative ideas can be transformed into scalable business models based on a triple bottom line: financial, environmental, and social considerations.

Our Approach to Impact Research Brings Together 3 Domains

Context​

Comprehensive research which combines original insights with contextual understanding

Intelligent Analytics

The creative application of data science methodologies, such as predictive statistics, machine learning, and natural language processing.

Clarity

Clear and engaging writing, which narrates the evidence in lively and concise prose​
​Our reputation is built upon honest, objective, evidence-driven analysis.

Data Science
Data Science is central to our work in two ways:
Focused Research: We research and write about data science and the effect it can have on human development. Advances in the analysis and application of data are driving innovation across nearly every industry

Data Science is often poorly understood and badly misrepresented in the mainstream media. Machine learning, for example, remains a black box to nearly everybody who doesn’t actually know how to code. It is often the case that those who understand it don’t write about it - and those who write about it don’t have experience in the field.

We are both practitioners in the field and journalists with the skill set to deliver clear and lucid insights into this complex domain.
Applied Methodologies: We apply data science methodologies to uncover hidden insights, ensure our work is statistically rigorous, and to illuminate our research through data visualizations.

Our team is familiar with a wide range of techniques, including applied machine learning, natural language processing, statistical methodologies, and data visualization. Our experience in the field ranges from hands-on application, to the management of technical teams, to strategy and leadership in the boardroom.

​Contact Us
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