Tag: synthetic data

Artificial Intelligence | Fraud & Security Intelligence | Innovation
Seema Rathor 0
Synthetic data for next-generation fraud detection in banking

Financial fraud is a high-stakes issue in banking, where schemes are becoming increasingly sophisticated and costly. As a result, detecting anomalies quickly and accurately is a top priority. But traditional data-driven fraud detection models face challenges such as data scarcity, privacy constraints, and model bias. This is where synthetic data

Artificial Intelligence
David Shannon 0
Trust in the process: Hyperautomation for drug development accelerates time-to-market

AI and automation – often referred to as hyperautomation – are evolving rapidly with industry experts emphasizing their increasing ability to operate independently and make intelligent decisions. By combining powerful generative AI with business expertise, organizations can accelerate and streamline their processes like never before. I recently sat down with Mayank

Analytics | Data Management | Predictions
Stu Bradley 0
Data privacy perspectives: How financial services firms can foster trust in the AI age

Every year, as Data Privacy Week sharpens the focus on protecting personal information, I’m reminded of a customer event a major North American bank hosted at SAS world headquarters. The bank’s chief data officer led a roundtable discussion on generative AI (GenAI) with a group of esteemed data and AI experts. The

Advanced Analytics | Artificial Intelligence | Innovation
Brett Wujek 0
Working with synthetic data? Ask these 6 questions first

Synthetic data has emerged as a powerful tool for overcoming the limitations of real-world data. The future holds great promise for accelerated innovation. With synthetic data, companies can now generate financial transactions, medical records or customer behavior patterns that maintain statistical relevance like real data. This emerging technology can help

Advanced Analytics | Artificial Intelligence | Innovation
Gavin Day 0
How generative AI can futureproof your workforce and build resilience

Major global elections, volatile financial markets, extreme weather events, and sophisticated and costly cyberattacks are increasing operational risks across every industry. Generative AI (GenAI) is redefining how industries navigate this uncertainty and transforming potential risks into powerful opportunities. Organizations across industries are increasingly invested in GenAI – for instance, last

Fraud & Security Intelligence | Predictions
Teya Dyan 0
Fraudulent facades: The upward trend of business entity fraud

Fraudsters are relentless but tax agencies are tenacious in their pursuit of illicit acts. In recent years, synthetic identity fraud has emerged as a significant threat to businesses and tax agencies. Unlike traditional identity theft, where criminals steal real personal information, synthetic identity fraud involves creating entirely new identities by

Advanced Analytics | Analytics | Artificial Intelligence
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L'essor des données synthétiques et leur impact sur l'intelligence artificielle

Dans le paysage technologique actuel, les données synthétiques, nouveau sous ensemble de l’IA générative, apportent de nouvelles pistes de réflexion pour la création des modèles d'intelligence artificielle.   Contrairement aux données traditionnelles, pouvant être limitées par des contraintes de biais, de quantité, ou encore des contraintes de confidentialité et de conformité,

Advanced Analytics | Artificial Intelligence
3 ways generative AI can assist in criminal investigations

Across the world, investigators and law enforcement officers are tackling a rapidly evolving and expanding workload fueled by an increase in complex modern-day crimes. As technology alters the type and methodology of the crime itself – the evasion of tax payments, theft of public funds, erroneous disbursement of benefits, gaming

Artificial Intelligence
John Gottula 0
3 strategies for effective data anonymization for governments

The ancients’ practice of publicizing set-in-stone personal records would run anathema to modern data privacy laws. These days, in lieu of using contemporary personally identifiable records, I anonymized a 4,000-year-old tax record from ancient Babylon to describe three principles for effective data anonymization at scale: Embracing rare attributes: values and

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