In its infancy, Actuarial Science operated at the leading edge of contemporary analytic capabilities and could be easily said to be employing “advanced analytics.” Over the past 50 years, however, relentless data and technology breakthroughs have created modern analytic capabilities that far outstrip many of our traditional actuarial pricing and reserving methodologies. The role of “data scientist” has emerged as the holistic practitioner in advanced analytics. The Casualty Actuarial Society (CAS) has begun to address the need to update our methodologies with recent predictive modeling additions to the syllabus, but to function as data scientists, we still need additional data and technology capabilities as well.
Preface, pages 1-4
Data Science and Analytics, pages 5-24
Business Intelligence Technology and Tools: A Primer for Actuaries, pages 25-35
Data Quality Overview Actuarial Concepts in Data Quality, pages 37-54
Databases, pages 55-66
Keywords: data management and information; data analysis; predictive modeling
