The Knowledge Exchange / Risk Management / Waynette Tubbs, Managing Editor / Page 3

Predicting motor vehicle insurance claims fraud

Cyber-security

Mark Schneider and Chase Zieman work with the Highway Safety Committee at Louisiana State University. They won the Analytics 2012 poster contest by demonstating how to predict insurance claims fraud.

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Four key benefits of high-performance analytics

data visualization

Are you struggling to pull all of the risk data for your regulatory calculations? Do you need to do a better job of predicting loan deposits earlier in the cycle? Take a look at how high-performance analytics can help you solve these problems.

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Wells Fargo gains agile analytics and reporting for risk

picture of people walking

At Wells Fargo, the rapidly changing business environment demands more accurate information, more quickly, and in more detail to help manage risk. Here’s a little insight into what Andy Mumma will be presenting at the Premier Business Leadership Series. Mumma is Vice President of Consumer Credit Solutions Risk Management at Wells Fargo.

Reducing the pitfalls of M-payments

Money launderng(1)

John Cassara, Former Senior Special Agent, US Department of the Treasury, and Dennis M. Lormel, President and CEO, DML Associates LLC and former Special Agent of the FBI, give two ideas that law enforcement, government and banks could use to come together to disrupt and prevent the flow of terrorist funding.

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A high-performance sandbox for risk management

Tham Ming Soong, former United Overseas Bank Chief Risk Officer

Former CRO of United Overseas Bank Ming Soong talks about the value of a high-performance analytics sandbox for risk management.

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Turning regulatory challenges into opportunities

Tham Ming Soong, former United Overseas Bank Chief Risk Officer

Ming Soong, former CRO for United Overseas Bank, says that a monthly or weekly report may be enough for regulatory compliance, but the same information could mean so much more to the organization. Take the challenge.

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The data challenge

big_data

The Solvency II directive is the first insurance regulation to introduce strict requirements for data management; it also represents an opportunity for many organizations. Effective data management results in better risk decisions, reduced likelihood of regulatory-imposed capital add-ons, increased return on capital, higher return on marketing campaigns and better fraud detection.

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Trends in risk management

FT video image

Al Sim, Senior Director at SAS, talks with Silvia Pavoni, Investment Editor for “The Banker,” about risk management best practices and trends that were uncovered during the 2011-2012 joint Financial Times/SAS enterprise risk management thought leadership program.

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Big data improves speed, accuracy and automation for credit lenders

Data for risk management - 2012

Credit lending is a fast-paced business that relies on large amounts of customer and transaction data. Rex Pruitt, Premier Bankcard, discusses how high-performance analytics can help meet the challenges of today’s lender.

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A better way to manage risk

A Better Way to Manage Risk

In this webinar, Harvard Business School professors Robert S. Kaplan (co-creator of the Balanced Scorecard management system) and Anette Mikes describe a new approach to manage organizational risks.

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