Spatial risk diffusion Predicting the

propagation of risk

inked to human

behaviour

Competing with digital disrupters

Traditional Insurance

Carriers:

• Cannot rely on only usual analytics methods, internal data

• Must adopt modern risk-assessment methods

Those that do not move out of their comfort zones will be left behind by their competitors

Digital Disrupters

exploit data to:

• Run efficient, agile, profitable operations

• Take marketplace leadership positions

They will use data from the digitalization of our lives to maximize their risk-assessment capabilities

The Spatial Risk Diffusion Model

Does not assess risk just as it relates to past events

Is unlike generalized linear modeling

Is a sophisticated predictive human behavioral model

Examines risk as a function of:

• Customers’ individual and collective behavior

• Linkages, influences of behavior across customer segments

The Spatial Risk Diffusion Model

At the heart of the model—the theory of risk as a social construct:

Societal norms are formed through social network interactions and influence risk-taking by individuals in the group

The Spatial Risk Diffusion Model

Scientific support: Peer-reviewed medical studies on smoking cessation, obesity by:

• Harvard Medical School • University of California – San Diego

At the heart of the model—the theory of risk as a social construct:

Societal norms are formed through social network interactions and influence risk-taking by individuals in the group

The Spatial Risk Diffusion Model

Our theory:

Applied to various behavior-driven risks, insurers

could understand the propagation of risk trends

throughout the population and predict:

• Which groups will influence

other groups’ behavior

• How long behavior will

take to spread

The Spatial Risk Diffusion Model

In partnership with researchers at

Stevens Institute of Technology

12-week research study tested:

• Theoretical foundation of the

model

• Our more expansive application

of the theory

• Predictive capabilities

of the model

The Spatial Risk Diffusion Model

The study:

Examined 12 years of NHTSA data on teen driving

Applied the model to teen driving behavior

Accurately predicted changes in driving behavior

Identified leaders, laggards in behavior among population groups

Population

data (Census)

Time series

analysis

Significantly correlated

Not significantly correlated

Pair-wise cross correlations and time lags between crash data time-series of states

Highly correlated

The Spatial Risk Diffusion Model

US

States

AL AK AZ AR CA CO CT DE FL GA HI Etc

AL 0 -3 0 0 0 0 0 0 0 0 0

AK 3 0 6 2 2 3 1 4 3 1 0

AZ 0 -6 0 0 0 -2 0 2 0 -1 -2

AR 0 -2 0 0 0 0 0 -2 -1 -1 -2

CA 0 -2 0 0 0 0 0 0 0 0 -2

CO 0 -3 2 0 0 0 0 1 0 0 0

CT 0 -1 0 0 0 0 0 0 0 0 0

DE 0 -4 2 2 2 0 -1 0 0 1 0

FL 0 -3 0 1 0 0 0 0 0 0 0

GA 0 -1 1 1 0 0 0 -1 0 0 0 Arizona lags Colorado by two years

HI 0 0 2 2 2 0 0 0 0 0 0 (Correlation 0.727)

Etc Colour represents correlation

Number shows lag time in years

(2000-2012, Age 15-19)

Fatal crashes

(NHSTA)

The Spatial Risk Diffusion Model

Significant potential impact on insurers’

financial performance

Teen risk attitudes becoming more conservative by

about 4% annually

Insurers could improve loss ratios by 60 to 100 basis points by

accounting for risk diffusion effects gleaned from state-level data

Loss-savings opportunity could be larger as analyses refined to

more granular zip code or county level

For example, in U.S. auto market:

The Spatial Risk Diffusion Model

Insurable behavior-driven risks that could

be better assessed include:

Workers compensation

Automobile

Burglary

Employers liability

Health

The Spatial Risk Diffusion Model

Loss reserving

Marketing

Public policy campaigns

Other areas the model can help:

Build behavioral-assessment capabilities needed to apply

spatial risk diffusion concept within regulatory framework:

The Spatial Risk Diffusion Model

Identify data points of most value, with highest predictive potential

Incentivize customers to share personal data to gain behavioral insights

Consider partnering opportunities

Conclusion

The Spatial Risk Diffusion Model would help insurers gain a competitive

advantage in risk assessment by allowing them to identify the population

groups whose behavior influences other groups. It also would enable insurers

to track how long that behavior takes to propagate throughout society.

They would become the industry’s

disrupters, rather than the disrupted.

With this advanced understanding of risk

diffusion, insurers would improve their

positioning against competitors—including

the industry’s digital disrupters—while

growing their business.

For more information and to

download the full report visit:

www.accenture.com/us-en/insight-spatial-risk-diffusion