SAS® Insights
News and views from the analytics experts
Most recent articles
-
- Select a topic
- Analytics
- Artificial Intelligence
- Business Intelligence
- Cloud
- Data for Good
- Data Management
- Fraud
- IoT
- Machine Learning and Deep Learning
- Marketing
- Risk Management
-
What is synthetic data? And how can you use it to fuel AI breakthroughs?There's no shortage of data in today's world, but it can be difficult, slow and costly to access sufficient high-quality data that’s suitable for training AI models. Learn why synthetic data is so vital for data-hungry AI initiatives, how businesses can use it to unlock growth, and how it can help address ethical challenges.
-
Unlocking a strategic approach to data and AIAI is only as good as the data that powers it – this is a fundamental truth about data and AI that defines the limits of what’s possible with artificial intelligence. It may seem surprising, but it's rarely a bad algorithm or a bad learning model that causes AI failures. It's not the math or the science. More often, it's the quality of the data being used to answer the question.
-
AI anxiety: Calm in the face of changeAI anxiety is no joke. Whether you fear jobs becoming obsolete, information being distorted or simply missing out, understanding AI anxiety can help you conquer it.
-
SAS AI Cities Index 2024 - where is the most AI ready in the UK?It’s poised to solve some of the world’s biggest challenges - from a climate change emergency to tackling dementia; boosting GDP, to improving the education system. Artificial intelligence (AI) is reshaping the world as we know it.
-
Fraud detection and machine learning: What you need to knowMachine learning and fraud analytics are critical components of a fraud detection toolkit. Discover what you’ll need to get started defending against fraud – from integrating supervised and unsupervised machine learning in operations to maintaining customer service.
-
6 ways big data analytics can improve insurance claims data processingWhy make analytics a part of your insurance claims data processing? Because adding analytics to the claims life cycle can deliver a measurable ROI.
-
What are AI hallucinations?Separating fact from AI-generated fiction can be hard. Learn how large language models can fail and lead to AI hallucinations – and discover how to use GenAI responsibly.
-
What are chatbots?Chatbots are a form of conversational AI designed to simplify human interaction with computers. Learn how chatbots are used in business and how they can be incorporated into analytics applications.
-
Bank Closures: Which areas are likely to be ‘bankless’ by 2024? The way that we bank has significantly changed in recent years, as banks respond to the needs of many businesses and consumers who choose to do their banking online, rather than visit the local branch.
-
A data scientist’s views on data literacyData literacy is a social imperative – and understanding data and data analysis is critical for being a responsible citizen. Get a data scientist and teacher's perspective on the value of having foundational knowledge so you can more easily tell data facts from data fiction.
-
How AI and advanced analytics are impacting the financial services industryTop SAS experts weigh in on topics that keep financial leaders up at night – like real-time payments and digital identity. See how advanced analytics and AI can help.
-
How data visualisation helps crack down on crimeAcross the world, law enforcement agencies are making more intensive use of data visualisation technologies. They gain a real-time view of locations, layered with crime, traffic, geospatial, weather and other data. This means decisions are based on solid, robust data and resources allocated to guide intervention and crime prevention. Data visualisation can make this possible for you too.
-
Shut the front door on insurance application fraud!Fraudsters love the ease of plying their trade over digital channels. Smart insurance companies are using data from those channels (device fingerprint, IP address, geolocation, etc.) coupled with analytics and machine learning to detect insurance application fraud perpetrated by agents, customers and fraud rings.
-
4 strategies that will change your approach to fraud detectionAs fraudulent activity grows and fighting fraud becomes more costly, financial institutions are turning to anti-fraud technology to build better arsenals for fraud detection. Discover four ways to improve your organization's risk posture.
-
Modern manufacturing's triple play: Digital twins, analytics & IoT IoT-powered digital twins revolutionize manufacturing with real-time data analysis, predictive maintenance and optimized production. Discover their transformational impact.
-
FRAUD IN THE UK: WHAT IS THE SCALE OF THE PROBLEM ACROSS THE COUNTRY?Fraud cases in the UK have increased substantially over the last two years. Scamming techniques used by perpetrators are constantly evolving, meaning they’re becoming more sophisticated, and, as a result, can be more difficult for businesses to contain.
-
Why banks need to evolve their approach to climate and ESG riskManaging environmental, social and governance (ESG) risk is important to banks, regulators, investors and consumers – yet there are many interpretations of how to do it. To thrive, organisations must evolve their risk management practices – including those affected by ESG risk.
-
Analytics leads to lifesaving cancer therapiesA long-shot treatment offers hope to 10-year-old Harrison after he learns the DNA profile of his cancer is resistant to chemo. Find out how data and analytics play a role in cancer research and cancer treatments that are saving lives.
-
Know your blind spots in tax fraud preventionTo find out more about where traditional tax fraud prevention and detection falls short, and what tax agencies should be doing about it.
-
Are you covering who you think you’re covering? Payers often don't focus enough on healthcare beneficiary fraud in public and private healthcare plans. Before paying a claim, payers need to ensure beneficiaries are eligible. Advanced analytics applied to a broad range of data can help them accurately detect and prevent beneficiary fraud.
-
Containing health care costs: Analytics paves the way to payment integrityTo ensure payment integrity, health care organisations must uncover a broad range of fraud, waste and abuse in claims processing. Data-driven analytics – along with rapid evolutions in the use of computer vision, document vision and text analytics – are making it possible.
-
Key questions to kick off your data analytics projectsThere’s no single blueprint for starting a data analytics project. Technology expert Phil Simon suggests these 10 questions as a guide.
-
Analytics tackles the scourge of human traffickingVictims of human trafficking are all around us. From forced labour to sex work, modern-day slavery thrives in the shadows. Learn why organisations are turning to AI and big data analytics to unveil these crimes and change future trajectories.
-
10 ways analytics can make your city smarter From child welfare to transportation, read 10 examples of analytics being used to solve problems or simplify tasks for government organizations.
-
Risk data infrastructure: Staying afloat on the regulatory floodWhat are the challenges of a risk data infrastructure and how can they be addressed? Here's what you need to know to build an effective enterprise risk and finance reporting warehouse that will effectively address compliance requirements.
-
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 minimise losses, increase earnings and reduce operational risk.
-
Analytics: A must-have tool for leading the fight on prescription and illicit drug addictionStates and MFCUs now have the analytics tools they need to change the trajectory of the opioid crisis by analysing data and predicting trouble spots – whether in patients, prescribers, distributors or manufacturers. The OIG Toolkit with free SAS® programming code makes that possible.
-
Viking transforms its analytics strategy using SAS® Viya® on AzureViking is going all-in on cloud-based analytics to stay competitive and meet customer needs. The retailer's digital transformation are designed to optimize processes and boost customer loyalty and revenue across channels.
-
Top prepaid card fraud scamsThe margin for prepaid cards is slim, so it's particularly important to root out the scams. Here are some tips for combating and mitigating prepaid card fraud.
-
Understanding capital requirements in light of Basel IVMany financial firms are already using a popular 2012 PIT-ness methodology for internal ratings-based models. This article examines eight ways the industry is successfully using the methodology – and why this approach can bring synergies for banks, value for regulators, and major competitive advantages.
-
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.
-
Detect and prevent banking application fraudCredit fraud often starts with a falsified application. That’s why it’s important to use analytics starting at the entrance point. Learn how analytics and machine learning can detect fraud at the point of application by recognising the biggest challenge – synthetic identities.
Send SAS Insights straight to your inbox