Cookies help us display personalized product recommendations and ensure you have great shopping experience.

By using this site, you agree to the Privacy Policy and Terms of Use.
Accept
SmartData CollectiveSmartData Collective
  • Analytics
    AnalyticsShow More
    data analytics and truck accident claims
    How Data Analytics Reduces Truck Accidents and Speeds Up Claims
    7 Min Read
    predictive analytics for interior designers
    Interior Designers Boost Profits with Predictive Analytics
    8 Min Read
    image fx (67)
    Improving LinkedIn Ad Strategies with Data Analytics
    9 Min Read
    big data and remote work
    Data Helps Speech-Language Pathologists Deliver Better Results
    6 Min Read
    data driven insights
    How Data-Driven Insights Are Addressing Gaps in Patient Communication and Equity
    8 Min Read
  • Big Data
  • BI
  • Exclusive
  • IT
  • Marketing
  • Software
Search
© 2008-25 SmartData Collective. All Rights Reserved.
Reading: 3 Ways GPU Databases are Transforming Financial Services
Share
Notification
Font ResizerAa
SmartData CollectiveSmartData Collective
Font ResizerAa
Search
  • About
  • Help
  • Privacy
Follow US
© 2008-23 SmartData Collective. All Rights Reserved.
SmartData Collective > Big Data > Data Warehousing > 3 Ways GPU Databases are Transforming Financial Services
AnalyticsComputingData ManagementData WarehousingHardwareIT

3 Ways GPU Databases are Transforming Financial Services

Mark Johnson
Mark Johnson
4 Min Read
GPU databases
SHARE

In the financial services industry, there’s no such thing as too fast.

Contents
1. Risk Assessment2. Fraud Reduction3. Faster, Better Trades

With the performance-doubling pace of Moore’s law finally coming to an end, graphical processing unit coprocessors are stepping in to deliver the boost that financial professionals need to handle ever more complex operations. GPU-accelerated computers are now being built with thousands of coprocessors, enabling multiple tasks to be executed simultaneously. These have transformative applications in the demanding worlds of trading, risk assessment, and portfolio analysis. Here are three ways GPU-accelerated processors and databases are changing the financial services industry.

1. Risk Assessment

Calculating risk is at the heart of every financial services business, from stock trading to insurance. The task of calculating risk scores involves large data sets and complex algorithms. It’s so CPU-intensive that risk assessment is typically done in batch overnight.

GPU databases cut risk aggregation times from hours to seconds. Datasets can be shared and processed in parallel, with the results combined at the CPU level. This enables insurance companies to quote rates instantly over the phone rather than the next day. Portfolio analysts can assess the risk of a basket of stocks while sitting across the table from the customer instead of scheduling another meeting. Traders can assess the impact of a news event on stock prices and move ahead of the market. Any financial services organization that relies upon speed will see competitive advantage from faster calculation of risk.

More Read

Artificial Intelligence
How Artificial Intelligence is Transforming the Corporate World
Data Analytics Optimizes Shipping through KPI Tracking
USAF Prevents Insomnia with Geospatial
Going Big – Teradata to Acquire Aster Data
US computer scientists have found that random networks – the…

2. Fraud Reduction

Credit card fraud is a $16.3 billion problem annually in the United States. Harder to quantify is the loss merchants take by declining transactions that should be approved. Some GPU databases can dramatically reduce the scope of both problems.

One of the principal drivers behind credit card fraud is that banks and merchants are under pressure to make split-second decisions in order to minimize customer wait times. However, the diverse and high-cardinality datasets typically needed to assess risk are hard to index and be processed in real-time.

GPU databases provide enough brute force that indexing is less important. They can distribute algorithms across multiple nodes and processors to find anomalies faster and to deliver more reliable decisions in the same or less time. Because the parallelized processing architecture enables near-linear scalability, the quality of decision improves when GPUs are applied to the task. Machine learning algorithms make computers “smarter” the more transactions they process, further trimming response times.

3. Faster, Better Trades

In stock trading, milliseconds count. Decisions hinge upon computers combing through vast amounts of historical data and applying mathematical models to compare past trends to current pricing patterns. With GPU in-memory databases, trading companies can load all their historical data into memory and process it in parallel. Some GPU databases are optimized for machine learning, which enables algorithms to detect patterns in data that humans wouldn’t see. They’re also ideally suited to processing streaming data. The combination of these features enables traders to apply calculations to live pricing information, resulting in near-real-time decision-making and more confident trades.

GPU databases combine the power of machine learning, real-time data ingestion, parallel processing, and nearly unlimited scalability to change the rules of financial services.

TAGGED:data analysisGPU database
Share This Article
Facebook Pinterest LinkedIn
Share

Follow us on Facebook

Latest News

data analytics and truck accident claims
How Data Analytics Reduces Truck Accidents and Speeds Up Claims
Analytics Big Data Exclusive
predictive analytics for interior designers
Interior Designers Boost Profits with Predictive Analytics
Analytics Exclusive Predictive Analytics
big data and cybercrime
Stopping Lateral Movement in a Data-Heavy, Edge-First World
Big Data Exclusive
AI and data mining
What the Rise of AI Web Scrapers Means for Data Teams
Artificial Intelligence Big Data Exclusive

Stay Connected

1.2kFollowersLike
33.7kFollowersFollow
222FollowersPin

You Might also Like

Tufte Shares Wisdom for Data Presenters

4 Min Read
Big Data Solutions
AnalyticsBig DataBusiness IntelligenceData ManagementData Warehousing

Big Data Solutions in the AWS Platform

4 Min Read
Real Estate
Big DataBusiness Intelligence

Why Real Estate Should Utilize Big Data

5 Min Read

Keeping count of people (and things)

3 Min Read

SmartData Collective is one of the largest & trusted community covering technical content about Big Data, BI, Cloud, Analytics, Artificial Intelligence, IoT & more.

ai is improving the safety of cars
From Bolts to Bots: How AI Is Fortifying the Automotive Industry
Artificial Intelligence
AI chatbots
AI Chatbots Can Help Retailers Convert Live Broadcast Viewers into Sales!
Chatbots

Quick Link

  • About
  • Contact
  • Privacy
Follow US
© 2008-25 SmartData Collective. All Rights Reserved.
Go to mobile version
Welcome Back!

Sign in to your account

Username or Email Address
Password

Lost your password?