Online Shopping Surges
With the worldwide pandemic, consumer behavior has shifted significantly. There has been substantially less travel — employees haven’t been driving to the office, flying on planes, or taking cruises. Many have gone out less, stopped going to movies, and don’t hang out on Friday night after work.
This has caused a major disruption in the financial flow. To survive, many businesses — small and large —have pivoted to bring and scale their businesses online. The result is a tremendous surge in online shopping. Experts suggest that e-commerce has been accelerated on the order of three to five years.
And these changes aren’t expected to go away. While buying everyday necessities like groceries online has been a safety strategy for many consumers, the convenience of online shopping is compelling enough for many to continue. At the same time, with the greater number of online transactions, fraud becomes an increasingly more expensive problem.
Scaling Transaction Processing to Fight Fraud
The amount of money lost to card-not-present fraud in 2020 was six times greater than what merchants lost in 2019, according to the Nilson Report. That wasn’t a fluke either, as the 2019 numbers were four times higher than 2018. That means companies need to be able to process more transactions faster with greater accuracy. Mastercard, for example, manages more than two billion cards and processes 165 million transactions per hour across 210 countries and territories.
‘Processes’ is an understatement. Using artificial intelligence (AI) and machine learning, more than 1.9 million rules are applied to each transaction to assess its risk. And this process needs to be completed in milliseconds.
High performance computing (HPC) is the only way to stay ahead of fraud as new schemes are devised and security vulnerabilities are discovered. HPC is also the foundation for evolving AI technologies. The more use cases AI must accommodate, the more data is involved and the more complex the data pipeline can become.
Today, 10% of data is processed outside of the data center and that figure is expected to rise to 75% by 2025. At the same time, to minimize response time, AI needs to be implemented closer to the edge. However, as new data is uncovered and algorithms adapt, these changes will also need to be able to scale back out to deploy throughout the worldwide network.
Deploy Adaptive AI at Scale
Consider evaluating the risk of accepting payments from a new merchant will little to no history. An initial assessment must be made quickly and accurately. However, given the ability of defrauders to operate anywhere in the world, data useful in identifying fraud could be available and leveraged anywhere in the global system.
AI and HPC are key to gathering valuable data, generating analytics, and dynamically adapting algorithms that identify fraud as quickly as possible anywhere at any time. Dell Technologies offers a wide range of customizable solutions to match the requirements of financial institutions of all types that need to process data quickly, accurately and securely. These solutions are designed to scale as a company grows.
Dell Technologies is also supported by a wide ecosystem of partners to assist FinTech companies of all natures with their individual needs. Converge Technologies, for example, is a Top 50 CRN Solution Provider that helps organizations find the right infrastructure to support leading-edge AI technology. Their solutions include Dell PowerEdge servers with Intel® Xeon® Scalable processors and Intel Optane™ memory, PowerSwitch networking and PowerScale storage for fast data processing, movement and storage.Scaling doesn’t have to be challenging. With the right technologies and partners, financial companies can expand their operations and successfully combat fraud. Learn more about new types of HPC/AI scalability for financial markets at HPC & AI on Wall Street.
Intel® Technologies Move Analytics Forward
Data analytics is the key to unlocking the most value you can extract from data across your organization. To create a productive, cost-effective analytics strategy that gets results, you need high performance hardware that’s optimized to work with the software you use.
Modern data analytics spans a range of technologies, from dedicated analytics platforms and databases to deep learning and artificial intelligence (AI). Just starting out with analytics? Ready to evolve your analytics strategy or improve your data quality? There’s always room to grow, and Intel is ready to help. With a deep ecosystem of analytics technologies and partners, Intel accelerates the efforts of data scientists, analysts, and developers in every industry. Find out more about Intel advanced analytics.