AI • Model Validation • Governance • Strategic Analytics

Build models that survive contact with reality.

Conquer Risk helps institutions turn AI, data and quantitative capability into systems that can be validated, governed, explained and used in high-stakes decisions. Our work spans finance, healthcare, telecommunications, manufacturing, technology and the public sector.

20+years in applied AI and model governance
1,000+ML, DL, AI and quantitative models built, validated or governed
~70institutional engagements
60+countries
$25Mcompetitive tenders led and won

From technical capability to accountable decisions.

The strongest model is not simply the one with the highest score. It is the one whose claim is clear, whose data support that claim, whose failure conditions are understood, and whose use can be governed in the real operating environment.

01

AI & Model Strategy

ML, deep learning and AI use-case design, model architecture review, comparative evaluation, deployment strategy and executive translation.

02

Model Validation & Assurance

Independent validation, calibration, bias and subgroup analysis, explainability, drift, monitoring, control design and challenge of model assumptions.

03

Data Strategy & Governance

Data lineage, decision frameworks, governance architecture, regulated data environments, operating controls and defensible external data sharing.

04

Clinical & Healthcare AI

Clinical AI, longitudinal and multimodal data, decision support, intervention-aware modeling, responsible deployment and healthcare interoperability.

05

Commercialization & Partnerships

Market propositions, technical proposals, competitive tenders, institutional partnerships, data products, IP strategy and translation of analytics into commercial value.

06

Team & Capability Building

Recruiting, training and leading quantitative, data, risk and AI teams; establishing operating standards and connecting technical teams to senior decision-makers.

Leadership

M. Antony Ewing, PhD

Conquer Risk was founded by M. Antony Ewing, a Princeton-trained quantitative economist, AI and data executive, former Group Chief Risk Officer and Chief Data Scientist, board-level technology executive, and current Professor of Research at the University of Illinois Chicago.

Across roughly 70 institutional engagements in more than 60 countries, he has built, validated and governed more than 1,000 ML, DL, AI and quantitative models and advised on more than $6 billion in model-dependent decisions. He led the technical proposals for and won approximately $25 million in competitive tenders.

Team leadership has been characteristic throughout his career. He has directly led more than 400 risk and data professionals, held broader executive responsibility for approximately 1,500 staff, and built and trained more than a dozen data-science teams.

AI and quantitative systems

20+ years across regulated and high-stakes environments, from enterprise model governance to current clinical AI and medical-data research.

Executive leadership

Former Group Chief Risk Officer and Chief Data Scientist; Executive Director and board member; founder and managing director of data and AI businesses.

Academic and research background

PhD and MA, Princeton University; BA with Honors in Economics and Mathematics, Northwestern University; former HKUST faculty member and Federal Reserve Bank of New York researcher.

Current medical AI work

Professor of Research at UIC and founder of Conquer Medical Health, with work spanning oncology, critical care, surgery, Alzheimer disease, ALS trials, imaging and population health.

Selected work.

The examples below preserve the substance of Conquer Risk's existing project history while presenting it in the language of AI, analytics, governance and enterprise transformation.

Digital Strategy • China

Digital-bank and fintech architecture for major state institutions

Advised large Chinese financial institutions responding to fintech and platform disruption, including digital-bank architecture, mobile ecosystems, underwriting, risk management and strategic situation-room design.

Technology Governance • Europe

Enterprise technology-risk framework

Performed gap analysis, benchmarking and framework design for a major Central and Eastern European institution, connecting technology risk, regulation, governance and senior management oversight.

Model Validation • Scandinavia

Model assurance and data-science team development

Trained and led quantitative and data-science teams in model validation, calibration, challenge and the communication of model implications to executives and boards.

Predictive Analytics • Africa & Asia

Mobile lending and multi-channel decision systems

Recruited and led data-science teams developing predictive analytics, underwriting and decision architecture for mobile savings, lending and digital-channel systems at national scale.

Worked alongside leading institutions and advisory firms.

Conquer Risk engagements have involved senior executives, boards, regulators, data scientists and operating teams across global institutions. Competitive work has included engagements delivered with major strategy and professional-services firms.

Goldman Sachs McKinsey & Company Boston Consulting Group PwC KPMG EY IBM Microsoft Oracle Birlasoft AXA / AXA Rosenberg

These names reflect expert-advisory work and successful bids in which M. Antony Ewing participated; they are not presented here as a single category of direct Conquer Risk clients.

Contact

Bring the model, the data, and the decision into the same room.

For executive advisory, AI and model validation, governance, data strategy, technical proposal support, clinical AI, or institutional capability building, contact M. Antony Ewing.

maewing@alumni.princeton.edu