Tags » Operational Risk

What are difference between Business Risk and Financial Risk

The risk is the possibility of loss or danger. The equity shareholders have to go through with two types of risk, i.e. Business Risk, and  673 more words

Business Risk

Modeling Generalized Poisson Regression with NLMIXED Procedure

The Generalized Poisson (GP) regression is a very flexible statistical model for count outcomes in that it can accommodate both over-dispersion and under-dispersion, which makes it a very practical modeling approach in real-world problems and is considered a serious contender for the Quasi-Poisson regression. 531 more words

Statistical Models

Bob Shaw Talks T+2 with Fund Technology

By Jennifer Molgano

Following Europe’s lead, the U.S. and Canada have been moving from T+3 toward T+2 settlement cycles, putting the pressure on middle- and back-office operations that facilitate trade confirmation. 442 more words

Risk.net presents the top 10 operational risks of 2017, as chosen by risk practitioners.

In a series of interviews that took place in November and December 2016, Risk.net spoke to chief risk officers, heads of operational risk and other op risk practitioners at financial services firms, including banks, insurers and asset managers. 195 more words


Estimate Regression with (Type-I) Pareto Response

The Type-I Pareto distribution has a probability function shown as below

f(y; a, k) = k * (a ^ k) / (y ^ (k + 1))
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Statistical Models

More about Flexible Frequency Models

Modeling the frequency is one of the most important aspects in operational risk models. In the previous post (https://statcompute.wordpress.com/2016/05/13/more-flexible-approaches-to-model-frequency), the importance of flexible modeling approaches for both under-dispersion and over-dispersion has been discussed. 311 more words

Statistical Models

Modified Park Test in SAS

The severity measure in operational loss models has an empirical distribution with positive values and a long tail to the far right. To estimate regression models for severity measures with such data characteristics, we can consider several candidate distributions, such as Lognormal, Gamma, inverse Gaussian, and so on. 412 more words

Statistical Models