Tags » Operational Risk

OMI Risk – Where Operational, Model and Investment Risks Come Together

By: Jim Ramenda

When asked about risk, insurers generally identify operational, model, and investment risks among their greatest concerns. As the leading provider of insurance financial reporting and risk software and services, SS&C would agree. 356 more words

Alternative Investments

New From Credit Suisse: Bonds for Self-Inflicted Catastrophes

Sagacious LLC will help customize a similar program to save op risk regulatory capital at your institution. 

By ANUPREETA DAS and LESLIE SCISM
May 16, 2016 1:21 p.m. 771 more words

Banks

More Flexible Approaches to Model Frequency

(The post below is motivated by my friend Matt Flynn https://www.linkedin.com/in/matthew-flynn-1b443b11)

In the context of operational loss forecast models, the standard Poisson regression is the most popular way to model frequency measures. 558 more words

Statistical Models

IT Audit Benchmarking Webinar: David Brand and Robert Kress Answer Your Questions

By David Brand
IT Audit Global Practice Leader, Protiviti
and
Robert E. Kress
Managing Director, IT, Financial and Operational Audit, Accenture

It has been a few months since the release of Protiviti’s   1,040 more words

Internal Audit

Time for bold moves.

I am continuing my series on operational risk. Here’s a link to the point of view I co-authored with Sulabh Agarwal, on how to manage operational risks in the payments world and create efficiencies in processes.

Managing Operational risk in Payments

Operational Risk

Are you in Control?

The global financial services regulatory landscape is continuing to evolve. With demands for increased regulatory oversight, greater transparency and improved internal controls, it has never been more important to ensure an institutions’ risk control environment is robust, scalable and flexible, and is able to monitor and detect issues in a timely manner. 98 more words

Private Equity

Prediction Intervals for Poisson Regression

Different from the confidence interval that is to address the uncertainty related to the conditional mean, the prediction interval is to accommodate the additional uncertainty associated with prediction errors. 696 more words

Statistical Models