Insurance Networking News

“There are so many things that are interconnected
that you have to have a holistic view of the
business, and you have to have it heavily
supported by technology.”
— Ross Bowen, Allianz Life Insurance Co.

need for reinsurance. “You have to think about what a major natural disaster would do to the financial markets right now,” Gallant says.

Bowen notes that the push toward greater use of stochastic modeling predates the crisis.

“We’ve had to develop tools to do more so-
phisticated modeling to manage our profitability
and risk,” he says. “We need the ability to value
liabilities every day. There are so many things that
are interconnected that you must have a holistic
view of the business, and have it heavily support-
ed by technology.”
The rise of modeling has paralleled advances
in computing power and modeling software. In-
expensive distributed computing options means
that complex, Monte Carlo simulations can now
be run in just a fraction of the time required just
a few years ago.

“Since the global financial crisis, we have six
times the computing capacity that we had before,
and we’ve increased staff,” Bowen adds. “We’re
not just throwing computers at the problem—
we’re also working smarter.”
Likewise, New York Life’s Pell is quick to point out
that while modeling imparts a degree of precision,
you have to apply common sense. Advances in com-
puting power may have improved the speed of sto-
chastic modeling, but while getting the answers
quicker is helpful, it doesn’t replace the inherent
need to ask the right questions. “Risk management is
more than just the model,” he says. “You can’t auto-
mate it. Making the right decisions is very dependent
on the judgment of the people reviewing the model
results in combination with other factors.”
Indeed, one of the charges leveled in the wake of
the financial crisis is that financial services firms
used sophisticated risk management systems as an
excuse for taking more risks. Pell says understand-
ing what’s driving the results the models spit out is
paramount. Further, you have to take a step back
and ask whether the assumptions on which the
model is based make sense. “Risk modeling in itself
is not sufficient,” he says. “You need to apply judg-
ment and question your assumptions.”
Pell says a new worry is that risk modeling has be-
come so discredited that people will not rely on their
models enough. “We have to be careful we don’t go to
the other extreme,” he says. “You need sophisticated
tools in order to understand the behaviors of instru-
ments and policyholders in different environments. But
you need to understand the limitations of those models.
You need to do sensitivity analysis on the assumptions
and the data that goes into it.”

New Rules

Rating agencies
and regulators increasingly
are demanding greater
transparency. solvency ii, the
forthcoming regulatory
requirement for insurers
domiciled in the european
Union, is another reason
insurers are implementing new
financial asset management
technology. Once enacted,
solvency ii will impose re-
quirements around insurers’
capital levels, governance,
risk management and disclo-
sure and practices. conse-
quently, carriers will be
required to “show their work”
more than ever before.
stateside, the american
academy of actuaries Life
capital adequacy subcom-
mittee (Lcas) and Variable
annuity Reserve Work group
(VaRWg) have been leaders
in the c3 Phase ii project,
which is part of a broader
academy initiative on risk-
based capital and principle-
based reserving. “the industry
is moving away from a formu-
la-based approach to reserv-
ing to one that’s principles-
based,” Bowen says. “that’s
been going on for several
years.”
another regulatory shift for
which financial risk regulators
will need to account is the
coming convergence of
accounting rules. the melding
of the generally accepted
accounting principles (gaaP)
of the U.s.-based Financial
accounting standards Board
and the international financial
reporting standards (iFRs)
issued by the international
accounting standards Board
will present challenges for
financial risk managers.

TRANSPARENCY

The scope and complexity of the information that financial risk managers must wade through to make determinations highlights the need for carriers to rethink how they aggregate and reconcile financial data. Just as successful modeling requires a synthesis between modeler and machine, there are other toolsets that aim to make the stewards of a company’s financial portfolio more effective by freeing them of previously manual duties. Some such progress is being made in the areas of accounting risk and compliance reporting for institutional investors.