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- White Paper The Escalation of Digital FraudThis Javelin Research report is based on 120 independent interviews of payment and security executives in 20 countries and delivers a clear picture of how digital fraud has changed the global operating environment for financial institutions.
- Analyst Report SAS is a Leader in The Forrester Wave™: Real-Time Interaction Management, Q4 2020Forrester names SAS a Leader in The Forrester Wave™: Real-Time Interaction Management, Q4 2020.
Managing Fraud Risk in the Digital Age
The rise of mobile and online transactions introduces new fraud risks. Retailers and payment processors must adapt their anti-fraud defenses, augmenting them with stronger, analytics-driven authentication, proactive detection and mitigation tools.
- Customer Story Managing risk to move faster in the marketplaceBendigo and Adelaide Bank better positioned to manage risk using SAS® Credit Risk Management solutions.
Risk-Aware Finance and the Changing Nature of Credit
New research by Chartis and SAS highlights how financial institutions must align finance and risk departments to accurately assess future risks and bolster budgeting and forecasting capabilities. This paper explores how risk-aware finance is becoming essential to meeting future regulatory and competitive demands.
- White Paper The Evolution of AnalyticsLearn about modern applications for machine learning, including recommendation systems, streaming analytics, deep learning and cognitive computing. And learn from the experiences of two companies that have successfully navigated organizational and technological challenges to adopt machine learning and embark on their own analytics evolution.
- Customer Story Analytics powers anti-money laundering effortsSAS helps Landsbankinn reduce false positives and streamline investigation.
- White Paper Understanding Data Streams in IoTThis paper explains how streaming analytics helps you acquire, understand and use real-time, streaming data to make fact-based, automated decisions – and instantaneously react to new information.
- White Paper Artificial Intelligence in Banking and Risk ManagementGlobal Association of Risk Professionals (GARP) and SAS survey drew more than 2,000 responses from across the financial services industry to answer questions about the current and future state of AI in risk.
- White Paper What is next-generation AML? The fight against financial crime fortified with robotics, semantic analysis and artificial intelligence
Balancing Fraud Detection and the Customer Experience
Customers of a digital business create an intricate online footprint as they transact online. Businesses that capture and truly understand a complete identity based on online and offline attributes can seamlessly authenticate good customers and reliably spot the fraudulent or hijacked identities – in real time.
Leveraging Analytics to Combat Digital Fraud in Financial Organizations
International Institute for Analytics summarizes key questions and answers about financial fraud in the digital age.
- Customer Story Accelerating the evolution of risk analyticsRaiffeisenlandesbank Niederösterreich-Wien AG gains speed and accuracy with SAS High-Performance Risk.
BCBS 239: A Path to Good Risk Taking
In the face of all the challenges and potential opportunity, BCBS 239 principles provide a solid foundation for data and analytics. And implementing them should be seen as a strategic investment.
- White Paper Stress Testing 2.0: Better Informed Decisions Through Expanded Scenario-Based Risk ManagementA road map for those who are starting to build – or are rethinking their approach to – their stress testing infrastructure and strategy.
Analytics Platform and Program: Keys to Success for Regulatory Compliance in Financial Services
Advanced analytics is at the heart of regulatory compliance processes in financial services.
Detecting and Preventing Banking Application Fraud
Since credit fraud often starts with a falsified application, it makes sense to have strong tools to monitor loans and credit lines from that point onward. This paper discusses analytics-driven methods for validating applications and spotting trouble multiple stages.
- Customer Story Making faster, better lending decisionsLocal Government Federal Credit Union sees efficiency gains with SAS.
- Customer Story Thai bank safeguards customers while managing fraud detection in real timeKrungsri Consumer uses SAS® Fraud Management to find fraud faster and reduce revenue losses.
- White Paper Building Artificial Intelligence in Credit Risk: A Commercial Lending PerspectiveWhat will it take for banks to trust artificial intelligence (AI) and machine learning (ML) with judgments about data accuracy and leverage it for commercial lending process automation?
- Customer Story Financial lender cuts third-party fraud by more than 80% with layered detectionAxcess Financial uses SAS Identity 360 to dramatically reduce fraud losses and boost customer satisfaction.
- Analyst Report SAS Is Helping Standard Chartered Comply with IFRS 9 Quickly and Cost Effectively
- Customer Story A new banking philosophy for enhanced customer loyaltyData-driven decisions help Royal Bank of Scotland transform its organizational processes, improve employee engagement and deliver excellent customer service.
- Article Should banks adopt regulations as best practices?The regulatory tsunami isn't letting up, but is there value to be gained in adopting, for instance, BCBS 239 principles?
- Article CECL: Are US banks and credit unions ready?CECL, current expected credit loss, is an accounting standard that requires US banking institutions and credit unions to estimate life-of-loan losses at origination or purchase.
Digital Intelligence: The Heart of Successful Digital Transformation
This paper explores how digital transformation is changing marketing and customer experience throughout industries, including banking, retail and telecommunications. It also covers the importance of data in digital intelligence and discusses strategic ways to build a digital intelligence platform.
- Customer Story CGC refines and enhances risk managementA single version of data across systems helps better manage credit and operational risk, as well as govern and plan with minimized risks and improved judgment.
- Article From lab to lifeOnce you've created your analytical model, you need to put it to use. Here are tips from finance industry experts to get your models in the hands of users.
- Article AI in banking: Survey reveals factors for successWhat do banking executives report about their experiences with AI? Where are they focusing today? What’s working? What are their plans for the future?
- White Paper Managing Models and Their RisksComputational and technological challenges present opportunities for a fast-evolving risk management discipline.
- Customer Story Fast analytical defenseDeutsche Kreditbank AG combats fraud and money laundering with SAS.
CECL: Don't Neglect the Fundamentals
Firms that proactively implement a CECL process that is controlled, efficient, collaborative and sustainable will find themselves with a competitive advantage over time. This paper discusses the long-term benefits of this holistic approach.
- Analyst Report Chartis RiskTech Quadrant for Model Risk Governance Solutions, 2019
Firmwide Scenario Analysis and Stress Testing
This paper explores the two most commonly used firmwide scenario model approaches for stress testing, firmwide risk capital measures and how regulatory stress testing is different from the firmwide risk capital approach mandated by CCAR and EBA.
Fighting Insurance Application Fraud
Learn about the advantages of using analytics-driven methods for authenticating applicants to reveal customer gaming, agent gaming and potential future claims fraud.
- Article Four focus areas for successful stress testingStress testing is not new to the risk world. But the increased complexity, expected frequency and firm-wide nature of scenarios present new challenges. That being said, to deliver a successful stress testing program, there are four key areas you should address.
- Video People, process, culture – and technologyData governance requires measurement and constant improvements of data quality. That’s a mountain of a job without clearly defined roles and responsibilities. Peyman Mestchian, Managing Partner at Chartis Research, and Tom Kimner, Head of Americas Risk at SAS, talk about data governance and the need for specialized departments, technology and skills.
Text Analytics for Executives
This paper looks at how organizations in banking, health care and life sciences, manufacturing and government are using SAS text analytics to drive better customer experiences, reduce fraud and improve society.
- Analyst Report Chartis RiskTech 100 2020SAS is named the winner of Chartis RiskTech 100 2020 for risk and finance integration, IFRS 9 and model risk management.
- Article Detect and prevent banking application fraudSince credit fraud often starts with a falsified application, it makes sense to have analytics-driven tools in place to detect fraud from the earliest point and across the life of the account.
Machine Learning Use Cases in Financial Crimes
Learn 10 proven ways machine learning can boost the efficiency and effectiveness of fraud and financial crimes teams – from data collection to detection to investigation and reporting.
- White Paper Scenario-Based Risk Management: Overcoming the ChallengesAs regulatory stress test regimes mature, financial institutions are looking for ways to harness investments they made in stress testing programs to gain additional business value.
- Case Study Thwarting disruption with strategic investments in innovationNational Australia Bank turns to innovative strategies, like hackathons, to find new solutions to emerging challenges.
The Analytics Mandate: Generating profits in difficult economic and regulatory times
Learn how and why banks need to apply more analytics for real-time decision making and multichannel marketing as consumers continue to migrate to digital channels and generate more data.
- E-Book Customer experience - now and into the futureExperience 2030: Research reveals 5 key themes driving customer experience. Build a forward-looking customer experience framework.
- Article Reducing the CCAR pain Theoretically, CCAR submissions can be developed and submitted using your existing risk and finance infrastructure. But there are some challenges to that approach. An analytic solution that is built to facilitate collaboration between risk and finance can produce some significant technical and business benefits.
AI Is at the Forefront of Reducing Money Laundering and Combating the Financing of Terrorism
See how artificial intelligence (AI), machine learning (ML) and robotic process automation (RPA) are helping firms overcome the challenges, improve results and make AML/CFT programs more efficient and effective.
- White Paper Fighting Money Laundering with Intelligent AutomationThe world of money laundering and other financial crimes is changing rapidly. This International Institute for Analytics research brief shows how fraudsters and money launderers keep getting more sophisticated.
- White Paper Payments Without BordersMitigating fraud risks in cashless payments by holistically understanding your customers across all channels.
- Article Managing fraud risk: 10 trends you need to watchSynthetic identities, credit washing and income misrepresentation – these are just some of the trends to watch if you’re trying to understand how to manage fraud risk. Find out what’s on the top 10 list of trends according to experts like Frank McKenna and Mary Ann Miller.
- Executive Brief Climate RiskA collection of articles from Risk.net on the impact of climate change on banks. SAS provides some key ideas for companies performing a self-assessment of their maturity in climate risk management.
- Article IFRS 9 and CECL: The challenges of loss accounting standardsThe loss accounting standards, CECL and IFRS 9, change how credit losses are recognized and reported by financial institutions. Although there are key differences in the standards for CECL (US) and IFRS 9 (international), both require a more forward-looking approach to credit loss estimation.
The Future of Risk Modeling
Explore the future of risk modeling with a comprehensive offering that covers data management, modeling, governance, reporting, batch execution, real-time scoring and decisioning with a platform designed for all types of risk models.
- White Paper Banking Application Fraud: Enemy at the GatesFind out how you can connect the dots from day one by creating multiple levels of detection that use different analytical techniques to identify both known and unknown patterns, yet one that can evolve and adapt with time.
- Interview Data visualization: A wise investment in your big data futureData visualization technologies can help the practice of data-driven decision making really take hold. But putting data visualization software in the hands of business users? Is it crazy – or crazy smart?
- Analyst Report Chartis FinTech Quadrant for CECL Technology Solutions 2018This Chartis research paper covers the FinTech Quadrant for CECL Technology Solutions for 2018.
- Customer Story Nationwide reduces fraud losses by 75%The world's largest building society chose SAS to lower its fraud losses - it realized a reduction of 75%.
- Article Retail cyber risk toleranceManage your data assets just as you would any of your physical assets by putting security plans in place for any and all contingencies.
SAS Grid Computing – What They Didn’t Tell You
Join Austria’s Erste Group Bank on their journey from a monolithic SAS processing environment to a more flexible infrastructure using SAS Grid Manager software.
How Any Size Organization Can Supersize Results With Data Visualization
Everyone makes better decisions with easy access to powerful, interactive analytics – no matter the size of the business. This e-book profiles six organizations that are using self-service data visualization and exploration to make big improvements in the way they work.
Data, analytics and machine learning: The new frontier of fraud prevention
The Economist explores how global financial institutions are using advanced technologies such as machine learning to support fraud and security intelligence.
- Customer Story Fast-growing bank wins market share with cloud solutionICA Banken cut marketing campaign design from six weeks to one day and increased conversions tenfold.
- Article Are you good at scoring?Credit scoring is the foundation for evaluating clients who apply for a loan (or other types of exposure for the bank). It is not unusual for it to take up to 12 months to build and deploy a new credit scoring model. Reforming the process will help minimize losses, increase earnings and reduce operational risk.
- White Paper Using Hybrid Cloud Capabilities for True Omnichannel MarketingSeamless, agile customer interactions require a marketing system that can collect data about a customer’s interactions and behavior across all touch points, regardless of underlying technology. Learn how SAS Customer Intelligence 360 lets you use both cloud and on-site channels and data to create an omnichannel marketing solution.
- White Paper Compete and win with better model risk managementModels can degrade over time, and sound model risk management (MRM) is the key to managing this risk.
- White Paper Rethinking customer due diligenceHelp evaluate your organization's CDD processes and technology relative to current industry risks and regulatory requirements.
- Article Model risk management: Vital to regulatory and business sustainabilitySloppy model risk management can lead to failure to gain regulatory approval for capital plans, financial loss, damage to a bank's reputation and loss of shareholder value. Learn how to improve model risk management by establishing controls and guidelines to measure and address model risk at every stage of the life cycle.
- Analyst Report Standard Chartered Bank: Turning Stress Testing from Compliance Tool to Competitive AdvantagePartnering with SAS, Standard Chartered Bank built a robust stress testing platform. It started out as a tool for regulatory compliance and was expanded for assessing the effect of crisis scenarios on its future P&L and balance sheet. The bank has migrated this Scenario-based Analytics Platform to a centralized and more powerful second generation, and SAS is a key technology component in the solution.
- Analyst Report SAS named Best in Class in Aite Matrix: Case Management to Combat Global Fraud and Money LaunderingAite names SAS Best in Class in Aite Matrix: Case Management to Combat Global Fraud and Money Laundering.
- Article Under siege: Improving customer experience in bankingBanks are ranking low in customer satisfaction, but improvement is possible says Digital Banking Report owner and publisher Jim Marous.
- Article Mobile payments, smurfs and emerging threatsM-payment remittances are replacing traditional banks and money services that have historically charged high fees for small transfers. Former US Treasury Special Agent John Cassara maps what he sees in the road ahead and gives advice for protecting your firm.
- Article Strengthen your payment fraud defenses with stronger authenticationThe rapid growth of digital wallets and payment applications has ushered in new payment fraud threats to consumers and organizations. Find out how the use of innovative technologies to combat payment fraud is a viable and effective solution with additional benefits.
Stress and Strategy: A C-Suite Guide to Scenario-Based Risk Management
This e-book from SAS and Argyle explores some of the ways that top-performing organizations are undertaking scenario-based risk assessment to develop and manage their business strategies.
BCBS 239: Meeting Regulatory Obligations While Optimizing Cost Reductions
Explore how forward-looking finance executives are using high-performance technologies to create fundamentally superior, compliant risk reporting processes – and ultimately help executives realize the goal of sustainable profitability
- Customer Story Preventing crime and ensuring compliance at 120 Nordic banksSDC enables small and medium financial institutions in four Nordic countries to stay compliant.
- Analyst Report Chartis RiskTech Quadrant: Technology Solutions for Credit Risk 2.0 (Banking Book)This research paper is based on material originally published in the Chartis Research report Technology Solutions for Credit Risk 2.0: Vendor Landscape, 2019.
Artificial Intelligence for Executives
This paper outlines the SAS approach to AI and explains key concepts. It also provides process and implementation tips if you are considering adding AI technologies to your business and analytical strategies.
Making Sense of AI
This e-book explores the current boundaries of AI, as well as the many ways that modern AI applications can improve our understanding of the world and enable us to make better, faster decisions.
Seven trends that will transform banking
Advanced analytics and big data are enabling smarter decisions and more efficient processes, from credit to compliance and risk management.
Tackle the Complexity of IFRS 9 and CECL Standards
The US standard for CECL increases the complexity of the allowance estimation process. Outside the US, IFRS 9 is having the same effect. This paper presents a high-level view of best practices for getting this right, including recommendations for organizational structure, data management, model development and management, systems and processes, governance and controls, reports and documentation.
The Future of Model Risk Management for Financial Services Firms
Banks have been using credit scoring models for decades, but since the financial crisis of 2008, regulators have formalized the discipline of model risk management (MRM), driving the need for more rigorous, enterprise-level model information management. Regulators now want to evaluate bank models to access their trustworthiness – not blindly accept the numbers they generate.
How AI and Machine Learning Are Redefining Anti-Money Laundering
Machine learning can play a big role in the defense against money laundering, either to automate tasks that formerly required human intervention, such as managing the data to train models, or detect more financial crimes risk that rules and more basic analytic techniques might miss.
- Customer Story Modernizing consumer lending in VietnamVietCredit aims to revolutionize the consumer finance market with SAS.
- E-Book Fight money laundering with these 5 game changers from SASEffectively battling dynamic financial crime threats requires new capabilities for AML defense – such as artificial intelligence, machine learning, intelligent automation and advanced visualization.
- E-Book Becoming a data-driven organizationLearn about the three foundations of becoming data-driven – data management, analytics and visualization – and how they can increase profitability, boost performance, raise market share and improve operations.
- Article Marketing optimization: Five lessons learned at a major US bankHow does a bank know what you need when you visit its website, open the mobile banking app or walk into the branch? For one of the largest banks in the US, the answer is marketing optimization. Here are five lessons they’ve learned.
As criminals find new ways to exploit technology and target potential victims, anti-fraud professionals must adopt new technologies to effectively navigate the evolving threat landscape.
- Article How to uncover common point of purchaseBanks that want to stay ahead of CPP and contain the costs of fraud need to implement advanced anti-fraud techniques.
- Customer Story Finding your best customers with machine learningSeacoast Bank enhances customer value using AI and SAS Visual Analytics on SAS Viya.
- E-Book Adapting to the New Age of Risk AnalyticsRapid advancements in technology are leading to a new age of risk analytics. The availability of commercial and open source software – coupled with significantly improved integration using industry standard tools – has made analytics more user friendly, expanding its reach to a broader range of business professionals.
- E-Book Fearless Decision? The most successful banks of the future will be those who can see their customers as individuals, appreciate their unique journeys and make decisions accordingly — across all associated business functions.
- Article Situational awareness guides our responses – routine to crisisMany circumstances call for situational awareness – that is, being mindful of what’s present and happening around you. The COVID-19 pandemic heightened this need, as leaders across industries used analytics and visualization to gain real-time situational awareness and respond with fast, critical decisions.
Detect and Prevent Identity Theft
The explosion in e-commerce and online account opening has created new convenience and choice for consumers. At the same time, large-scale data breaches have created new opportunities for fraudsters, fueling an 8-percent increase in identity theft in a single year. Find out how to fight back, without hindering your good customers.
- White Paper Machine Learning Model GovernanceBanks are rapidly expanding their use of machine learning-enabled (ML) models, because they can provide step-level improvements in accuracy. But ML models need even more rigorous governance than traditional models. This paper explores what's required to implement effective ML model governance.
Six Keys to Credit Risk Modeling for the Digital Age
Modernizing and automating the end-to-end process for origination and servicing – from data management to model development to credit decisions – can reduce credit losses and boost performance. This paper explores how infusing machine learning into this process supports more effective credit decisions for individuals, products or portfolios.
Designing the Infrastructure for Credit Risk Model Development
Explore the most common problems organizations face when setting up infrastructure for analytics – and credit risk modeling specifically – and learn about ways to increase productivity and reduce problems through better planning and design.
Using SAS Marketing Optimization to improve credit-line optimization
Learn how SAS Marketing Optimization enables credit line optimization to balance the needs of managing risk exposure and achieving an acceptable rate of return at the portfolio level, as well as to devise a structured approach and advanced methodology that supports credit line strategy.