Clarity Insights Blog

What we can learn from Capital One anti-money laundering probe

on Aug 14, 2017 11:20:54 AM By | Mark Lewis | 0 Comments | Financial Services fraud Risk Management Big Data Advanced Analytics
Of all the pressing concerns facing the financial services industry today, fraud prevention may be the most difficult to get right. As technology gets more advanced, fraudsters become more sophisticated, taking advantage of new weaknesses and scamming financial firms and their customers for massive sums of money. On average, organizations lose five percent of their annual revenue due to fraud each year, according to the Association of Certified Fraud Examiners.
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Take fraud prevention to the next level with advanced analytics

on Aug 7, 2017 6:17:00 AM By | Mark Lewis | 0 Comments | fraud Advanced Analytics Insurance Financial Services Risk Management
Fraud continues to be a thorn in the sides of banks, financial firms and insurance companies everywhere. As technology becomes more advanced, fraudsters grow more sophisticated right along with it.
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What you need to know about stress testing in the energy sector

on Jul 17, 2017 6:30:00 AM By | Mark Lewis | 0 Comments | stress testing Industrial Risk Management
When properly conducted, stress testing offers unparalleled insight into the potential threats facing business operability. While stress testing is most commonly associated with the financial service community, the energy sector has leaned on the technique for decades to get a better understanding of where vulnerabilities lie and where more resources should be allocated.
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3 misconceptions hurting operational risk modeling (and what you can do about it)

on Jul 10, 2017 6:30:00 AM By | Mark Lewis | 0 Comments | Risk Management Financial Services Operational Risk Analytics
Operational risk is a fact of life for financial services firms, but it doesn't have to be the major source of anxiety it often becomes. Big data and advanced analytics can help organizations improve their risk management practices with precise modeling that identifies potential risks before disaster strikes.
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