financial risk analytics

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By: IBM     Published Date: Sep 02, 2014
In today’s stringent financial services regulatory environment with exponential growth of data and dynamic business requirements, Risk Analytics has become integral to businesses. IBM Algorithmics provides very sophisticated analyses for a wide range of economic scenarios that better quantify risk for multiple departments within a firm, or across the enterprise. With Algorithmics, firms have a better handle on their financial exposure and credit risks before they finalize real-time transactions. But this requires the performance and agility of a scalable infrastructure; driving up IT risk and complexity. The IBM Application Ready Solution for Algorithmics provides an agile, reliable and high-performance infrastructure to deliver trusted risk insights for sustained growth and profitability. This integrated offering with a validated reference architecture delivers the right risk insights at the right time while lowering the total cost of ownership.
Tags : ibm, it risk, financial risk analytics
     IBM
By: IBM     Published Date: Sep 16, 2015
The impact of the 2008 financial crisis affects not only Sell Side firms - the focus of discussions - but Buy Side and Insurance firms. Dodd Frank Act targets all systemically important firms. This study conducted in partnership with Waters Technology, an Incisive Media publication, focuses these firms. The report finds that they are facing intense pressure on multiple fronts including stricter liquidity and solvency risk regulations, and changing market conditions. Like Sell Side firms, they require more innovative business models and analytics to meet these challenges and to deliver growth and performance.
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     IBM
By: Alteryx, Inc.     Published Date: Apr 21, 2017
As a financial services provider, you have probably invested hundreds of thousands, if not millions of dollars, in building an analytic infrastructure. But, do your line-of-business analysts and managers have access to the data and insights they need, when they need them? Three ways Alteryx can help you improve customer experience, manage risk and increase operational efficiency Case studies on how your peer financial services companies are using self-service data analytics for a competitive edge
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     Alteryx, Inc.
By: IBM     Published Date: Aug 22, 2014
The ongoing processes of managing collateral, loan covenants and monitoring borrowers' financial condition are key to ensuring that banks are in the best position to minimize loss.
Tags : credit risk management, managing collateral, financial monitoring, risk analytics
     IBM
By: SAS     Published Date: Mar 06, 2018
With decisions riding on the timeliness and quality of analytics, business stakeholders are less patient with delays in the development of new applications that provide reports, analysis, and access to diverse data itself. Executives, managers, and frontline personnel fear that decisions based on old and incomplete data or formulated using slow, outmoded, and limited reporting functionality will be bad decisions. A deficient information supply chain hinders quick responses to shifting situations and increases exposure to financial and regulatory risk—putting a business at a competitive disadvantage. Stakeholders are demanding better access to data, faster development of business intelligence (BI) and analytics applications, and agile solutions in sync with requirements.
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     SAS
By: SAS     Published Date: Mar 06, 2018
These emerging technologies and solutions certainly are not unique to financial services. But Stewart, a business director of security intelligence solutions within the SAS Security Intelligence Practice, sees particular interest and application in AML circles. "There remain a good number of manual processes within financial crimes departments in financial institutions, and AI can help automate some of those rote tasks such as document review or alert triage," he says. "Due to investments in technology, there is a lower barrier of entry for midsized institutions. "And finally, there's this anxiety over the unknown - those risks they are not able to detect, that may be hidden using traditional techniques - so they're hoping that more advanced, unsupervised learning techniques can be used to identify those edge cases or behaviors that are out of norm." In an interview about analytics and the AML paradigm shift, Stewart discusses: • The new industry intrigue with artificial intelligence a
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     SAS
By: SAS     Published Date: Mar 01, 2012
Learn what criteria distinguished certain companies as top performers within the SMB sector, the factors to consider when assessing your organization's BI competency and the required actions to achieve best-in-class performance.
Tags : sas, analytics, business analytics, business intelligence, customer intelligence, data management, fraud & financial crimes, high-performance analytics, it management, ondemand solutions, performance management, risk management, sas® 9.3, supply chain intelligence, sustainability management, business intelligence, michael lock, predictive analytics, business insight, business visibility
     SAS
By: IBM     Published Date: Oct 10, 2013
The growth of cloud, mobility, social business and big data mean that botnets, credit card theft, cyber criminals and other external threats pose increasing risk to business continuity, financial stability and brand reputation. Read the white paper, “Preventing security risks in real time,” to learn how this new reality is forcing the evolution of organizations’ defenses to become more intelligent—using global analytics to scale visibility across broad data sets, both diverse and complementary, in real time.
Tags : ibm, cloud, mobility, social business, data, big dta, theft, cyber theft, cyber criminals, security, security risks, global analytics, visibility, data sets, protection, external threats, risk, risk management, finanical stability
     IBM
By: SAS     Published Date: Oct 03, 2018
Risks have intensified as retailers and financial organizations embrace new technologies to meet customer demands for convenience. The rise of mobile and online transactions introduces new risks – and with that, new requirements for fraud mitigation. This paper discusses key steps for fighting back against fraud risk by establishing appropriate and accurate data, analytics and alert management.
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     SAS
By: SAS     Published Date: Oct 03, 2018
Fraudsters are only becoming smarter. How is your organization keeping pace and staying ahead of fraud schemes and regulatory mandates to monitor for them? Technology is redefining what’s possible in fighting fraud and financial crimes, and SAS is at the forefront, offering solutions to: • Protect from reputational, regulatory and financial risks. • Reduce the cost of fraud and financial crimes prevention. • Gain a holistic view of risk across functions. • Include cyber events in regulatory report filings. In this e-book, learn the basics in how to prevent fraud, achieve compliance and preserve security. SAS fraud solutions use advanced analytics and artificial intelligence to help your organization better detect and prevent fraud. By applying analytics and powerful machine learning on a unifying platform, SAS helps organizations around the globe detect more financial offenses, reduce false positives and run more efficient investigations.
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     SAS
By: IBM     Published Date: Oct 10, 2013
The growth of cloud, mobility, social business and big data mean that botnets, credit card theft, cyber criminals and other external threats pose increasing risk to business continuity, financial stability and brand reputation. Read the white paper, “Preventing security risks in real time,” to learn how this new reality is forcing the evolution of organizations’ defenses to become more intelligent—using global analytics to scale visibility across broad data sets, both diverse and complementary, in real time.
Tags : cloud, mobility, social business, big data, external threats, business risks, business continuity, financial stability, brand reputation, protecting reputation, prevent theft, organizational defenses, global analytics, broad data, real time data, security risks, prevent risks, security
     IBM
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