Tag: fraud detection
Leveraging GenAI and LLMs in Financial Services
Data and large language models (LLMs) can save banks and other financial services millions by enhancing automation, efficiency, accuracy, and more. McKinsey reports that the productivity lift from generative AI can lead Read more…
Aerospike Is Now a Graph Database, Too
Aerospike this week rolled out new graph database offering that leverages open source components, including the TinkerPop graph engine and the Gremlin graph query language. The NoSQL company foresees the new property gra Read more…
Rockset Says It’s Ready for Real-Time AI
Shrinking decision windows and faster data generation set the table for the rise of real-time analytics as a product category. And now with large language models and vector databases paving the path toward enterprise AI, Read more…
Quantexa to Boost AI and Analytics Investment with Series E Round
Quantexa, a UK-based company that develops a decision intelligence platform designed to help banks, telecommunication providers, and government agencies uncover risks and opportunities hidden in their data, this week ann Read more…
Databricks Brings ML Serving into the Lakehouse
Databricks customers can now run their machine learning models directly from the vendor’s platform, eliminating the need to manage and maintain separate infrastructure for ML workloads like product recommendations, fra Read more…
Three Ways Next Generation Graph Technologies Are Transforming the Banking Industry
For today’s modern bank, the ability to access and analyze data in real time is almost as important as its access to capital. However, the banking industry is facing a big “big data” problem: an enormous amount of Read more…
Using AI to Automate, Orchestrate, and Accelerate Fraud Prevention
As fraud, waste, and abuse (FWA) cost government agencies and private companies billions each year, artificial intelligence (AI) has transformed how organizations prevent, monitor, and respond to FWA activity, powering a Read more…
TigerGraph Bolsters Scalability with Graph Database Update
TigerGraph today announced that the latest release of its parallel graph database can be fully controlled with Kubernetes. With version 3.2, the company also added the ability to scale the database up and down as needed, Read more…
Machine Learning-Based Real-Time Threat Detection for Banks
The business impact of the COVID-19 pandemic continues to unfold worldwide for the financial services industry. The “new normal” has not only given rise to unprecedented operational challenges, but also provided fert Read more…
For ‘Open Banking,’ Data is a Person
The pandemic has accelerated the shift to digital financial services such as “open banking.” That has resulted in increased fraud, up an estimated 11 percent since the novel coronavirus hit. What’s more, industr Read more…
Neo4j Going Distributed with Graph Database
Neo4j is the leader in the burgeoning graph database market, with 17 years in development and thousands of open source users. But the database has a hard limit in terms of scalability, since it essentially was restricted Read more…
Cassandra, Kafka Help Scale Anomaly Detection
The scaling of open-source platforms continues apace with the demonstration of an anomaly detection application capable of processing tens of billions of events per day using Apache Cassandra and Apache Kafka running on Read more…
TigerGraph Serves Collaboration and Security with Multi-Graph
The capability to share data insights with other people or departments is instrumental to collaboration, and yet it's also the source of real security concerns in today's dangerous world. Graph database startup TigerGrap Read more…
Data Wrangling Enlisted to Fight Black Friday Fraud
Black Friday and Cyber Monday are coming, and the fraudsters are ready. With a growing percentage of mobile applications and app stores listed as malicious in the run up to Black Friday (Nov. 24) and Cyber Monday (Nov Read more…
Achieve Business Value with Machine Learning
With major companies battling constant cyberattacks and advanced persistent threats from cyber attackers, larger dedicated staffs are currently required to handle cyber espionage issues. Right now, a common problem acros Read more…
Retailers Find Further Reason for Real-Time
Retailers use streams of data from registers, social media, call centers, return and invoicing centers and various other places to piece together competitive elements of their business. But big data in retail doesn’t end there. Loss prevention and real-time fraud... Read more…
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