Life Insurance Risk Assessment


The traditional underwriting process used in life insurance is based on manually examining an applicant’s health, behavioral, and financial profile. The existence of large historical data sets provides an unprecedented opportunity for artificial intelligence and machine learning to transform underwriting in the life insurance industry. We present an overview of how a rich application data set and survival modeling were combined to develop a state of the art life score that is inpretable by consumers and carriers alike. Through a novel evaluation framework, we show that the score outperforms traditional underwriting by 6% on the basis of claims.

Publications & Talks

Improving the Accuracy and Transparency of Underwriting with AI to Transform the Life Insurance Industry

A.I. Magazine, Sept. 2020

M. Maier, H. Carlotto, S. Saperstein, F. Sanchez, S. Balogun and S. Merritt

Transforming Underwriting in the Life Insurance Industry

AAAI Innovative Applications of Artificial Intelligence, Jan. 2019.

M. Maier, H. Carlotto, F. Sanchez, S. Balogun and S. Merritt

Career Paths and Occupation Networks


Using data from nearly 1,000,000 publicly available resumes, I am constructed a network of occupations. Using the ordered sequences of occupations contained in the resumes, I created a probabilistic model of career path dynamics that connected the network structure with workers' career path decisions. The goal of this research was to uncover relationships between the structure of occupation networks and the dynamics of career paths.

Publications & Talks

Occupation networks: career path dynamics and poverty traps

Computer Science Department, University of Colorado (Oct., 2013)


PathOp: Find your path

Career Path Planning, Optimized

Scoring Dynamics in Professional Sports


Using data from the last decade, I conducted a statistical analysis on millions of scoring events from four different professional sports: basketball, hockey, soccer, and American football. I studied inter-arrival times and correlations between events as well as distributions of streaks and final scores, among other statistical properties. This research developed tools for the analysis and modeling of scoring dynamics and shed new light on the existence of universal properties of scoring dynamics in sports.

Publications & Talks

Scoring dynamics across professional team sports: tempo, balance and predictability

EPJ Data Science, Feb. 2014.

S. Merritt, A. Clauset

Scoring dynamics in professional sports: tempo, balance and predictability

Computer Science Department, University of Colorado (Sep., 2013)


On The Spot Sports

Real-Time Scoring Dynamics Prediction

Structure and Dynamics in Competitive Online Games


Competition is ubiquitous in complex social systems, from informal online environments to professional sports, to economic interactions between firms. Traditional studies of competition use theory and small-scale controlled experiments to study the outcomes of competition, not the dynamics that occur within them. Here we have analyzed the dynamics of competition using a rich and vast data set from the video game Halo: Reach, using novel quantitative methods and big data processing systems. There are two goals of this research. The first is to produce data-driven mathematical models that contribute to a general understanding of the interactions between participants and the environment. The second is designing new algorithms and tools that have the ability to predict, influence, and control the dynamics in these systems. These results will produce an ability to systematically design competitive social systems to the preferences of participants.

Publications & Talks

Social Network Dynamics in a Massive Online Game: Network Turnover, Non-densification, and Team Engagement in Halo Reach

Knowledge Discovering and Data Mining (KDD) Workshop on Mining and Learning with Graphs (MLG), Aug. 2013.

S. Merritt, A. Clauset

Environmental structure and competitive scoring advantages in team competitions

Nature Scientific Reports, Oct. 2013.

S. Merritt, A. Clauset

Detecting friendship within dynamic online interaction networks

International Conference on Weblogs and Social Media (ICWSM), Jul. 2013.

S. Merritt, A. Jacobs, W. Mason, A. Clauset

Inferring massive dynamic social networks from ad hoc human competitions

NetSci, Jun. 2012. (abstract and poster)

S. Merritt, A. Jacobs, A. Clauset

Internet Resource Allocation Dynamics


How do competing TCP connections interact with one another when transiting a common bottleneck asymmetric link? This is an old problem that still remains unsolved because the fundamental interactions between link speed, buffer sizing, and TCP's congestion control algorithm are not precisely understood. This research describes the interactions in a new way and turns this new understanding into a practical solution.

Publications & Talks

Two-way TCP connections: old problem, new insight

ACM SIGCOMM Computer Communication Review, Vol. 41, No. 2, Apr. 2011.

M. Heusse, S. Merritt, T. Brown, and A. Duda