36 O Hasu and T-K Lehtonen
to market fluctuations. Our analysis contends that, as a technology for considering environmental risks, index insurance follows a logic in which the
objectivity of risk modelling is grounded in the instrument’s capability to
establish formal conditions for market operations. For these purposes, the
operationalisation of environmental data plays only a minor role in orienting the model’s anticipation of future uncertainties; weather phenomena
are simply treated as predetermined variables in probabilistic simulations.
Thus, environmental data ends up being operationally more important for
transferring risks to the global financial markets than it is for gaining a
dynamic view of ecological reality.
The choice to model payout ratios but not the environment or temporal
change is presented by RM as a necessary control mechanism for approximating short-term risks. The resulting index is a form of information that
enables financial services to operate by creating expectations about the
future. In mediating economic processes, index insurance is an infrastructure that makes risk taking possible because it allows creditors to price the
risks of capital; simultaneously, it creates a distribution channel for financial services. These financial services, for their part, are able to price the
risk of capital and thus support the expansion of financial markets.
What makes the form of index insurance advanced by RM problematic
is that the instrument’s models are presented as objective representations
of ecological risks, while the mathematical language of probabilistic simulations obscures the process through which the risks are constructed
and shaped into social relations. That financial instruments do not merely
describe the world but also generate social organisations (LiPuma 2017)
is related to the constitution of objects of governance being contingent on
infrastructural, political, and cultural configurations (Easterling 2016).
The normative design RM presents for index insurance development has
the potential downside of eliminating the forms of information that would
recognise interdependences between social and ecological processes in
how risks are shaped. While not recommending it, the guide does raise the
question of whether finance-based governance should include environmental data as a factor that structurally orients the model’s anticipation of the
future. Such modelling techniques might aid understanding how risk technologies are not only managing the soil’s risks but also shaping them. This
is a point of view that climate change makes all the more important, given
the feedback loops between economic processes and ecological systems (e.g.
Goodman & Anderson 2020; Moore 2015).
To sum up, it is simply astounding that the index insurance programme
does not use environmental data either to predict dynamic changes or to
consider underlying uncertainties; this is especially surprising as the programme is highlighted as technologically innovative in the discourse of
GIIF, the project out of which RM arose. In this regard, the methods used
for abstracting weather-related risks from their material reality question the
ability of index insurance to respond accurately to climate change. Behind
to market fluctuations. Our analysis contends that, as a technology for considering environmental risks, index insurance follows a logic in which the
objectivity of risk modelling is grounded in the instrument’s capability to
establish formal conditions for market operations. For these purposes, the
operationalisation of environmental data plays only a minor role in orienting the model’s anticipation of future uncertainties; weather phenomena
are simply treated as predetermined variables in probabilistic simulations.
Thus, environmental data ends up being operationally more important for
transferring risks to the global financial markets than it is for gaining a
dynamic view of ecological reality.
The choice to model payout ratios but not the environment or temporal
change is presented by RM as a necessary control mechanism for approximating short-term risks. The resulting index is a form of information that
enables financial services to operate by creating expectations about the
future. In mediating economic processes, index insurance is an infrastructure that makes risk taking possible because it allows creditors to price the
risks of capital; simultaneously, it creates a distribution channel for financial services. These financial services, for their part, are able to price the
risk of capital and thus support the expansion of financial markets.
What makes the form of index insurance advanced by RM problematic
is that the instrument’s models are presented as objective representations
of ecological risks, while the mathematical language of probabilistic simulations obscures the process through which the risks are constructed
and shaped into social relations. That financial instruments do not merely
describe the world but also generate social organisations (LiPuma 2017)
is related to the constitution of objects of governance being contingent on
infrastructural, political, and cultural configurations (Easterling 2016).
The normative design RM presents for index insurance development has
the potential downside of eliminating the forms of information that would
recognise interdependences between social and ecological processes in
how risks are shaped. While not recommending it, the guide does raise the
question of whether finance-based governance should include environmental data as a factor that structurally orients the model’s anticipation of the
future. Such modelling techniques might aid understanding how risk technologies are not only managing the soil’s risks but also shaping them. This
is a point of view that climate change makes all the more important, given
the feedback loops between economic processes and ecological systems (e.g.
Goodman & Anderson 2020; Moore 2015).
To sum up, it is simply astounding that the index insurance programme
does not use environmental data either to predict dynamic changes or to
consider underlying uncertainties; this is especially surprising as the programme is highlighted as technologically innovative in the discourse of
GIIF, the project out of which RM arose. In this regard, the methods used
for abstracting weather-related risks from their material reality question the
ability of index insurance to respond accurately to climate change. Behind