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
    warehouse accidents
    Data Analytics and the Future of Warehouse Safety
    10 Min Read
    stock investing and data analytics
    How Data Analytics Supports Smarter Stock Trading Strategies
    4 Min Read
    predictive analytics risk management
    How Predictive Analytics Is Redefining Risk Management Across Industries
    7 Min Read
    data analytics and gold trading
    Data Analytics and the New Era of Gold Trading
    9 Min Read
    composable analytics
    How Composable Analytics Unlocks Modular Agility for Data Teams
    9 Min Read
  • Big Data
  • BI
  • Exclusive
  • IT
  • Marketing
  • Software
Search
© 2008-25 SmartData Collective. All Rights Reserved.
Reading: Financial Fraud Detection & Prevention Analytics Strategies
Share
Notification
Font ResizerAa
SmartData CollectiveSmartData Collective
Font ResizerAa
Search
  • About
  • Help
  • Privacy
Follow US
© 2008-23 SmartData Collective. All Rights Reserved.
SmartData Collective > IT > Security > Financial Fraud Detection & Prevention Analytics Strategies
AnalyticsCommentarySecurity

Financial Fraud Detection & Prevention Analytics Strategies

Sandeep Raut
Sandeep Raut
3 Min Read
SHARE
Financial industry is facing the fiercest competition in current time after the economic meltdown. Banks are using all avenues to grow their customer base considering the survival aspect. This has led to tremendous volume growth in banking accounts applications, credit card applications, and financial transactions. Obviously, as a consequence, the number of fraudulent applications and transactions is also rapidly growing.
Financial industry is facing the fiercest competition in current time after the economic meltdown. Banks are using all avenues to grow their customer base considering the survival aspect. This has led to tremendous volume growth in banking accounts applications, credit card applications, and financial transactions. Obviously, as a consequence, the number of fraudulent applications and transactions is also rapidly growing.

With new payment channels like prepaid cards, e-payments & now mobile-payments, fresh opportunities for frauds are emerging.

Some of the industry research shows that:

  • Credit card frauds losses over 8 billion USD per year
  • Insurance policy holders have to pay higher premium up to 5%
  • Total fraud Losses are estimated over 30 billion USD per year

Frauds cane be classified into various categories as below:

  • Credit/Debit/Charge card fraud
  • Check fraud
  • Internet transaction / wire transfer fraud –
  • Insurance or healthcare or warranty claim fraud – over payments, false claims
  • Subscription fraud – use of telecom services with false credentials
  • Money laundering
  • Identity theft or account takeover

Analytics approaches to detect & prevent Frauds:

  • Combine historical fraud data with industry knowledge & external market data
  • Create a proof of concept to test the history data to determine fraud cases
  • If historical data is not available then anomaly detection or outlier detection is used
  • Apply the statistical model for fraud detection
  • Models are based on past spending patterns, demographic information
  • Further text mining & link analysis for probable associations to find deeper frauds
Benefits:
  • Increased number of identification of fraud cases
  • Dollar savings from fraud prevention adds to bottom line
  • Protect the customer base from financial loss or identity theft
  • Improvement in service helps to differentiate in highly competitive market
How companies are using it:
  • Financial institutions using it to identify frauds in leasing contracts
  • Banks are using it to detect credit card, wire transfers, check frauds
  • Insurers are using it to detect fraudulent claims to save the losses
  • Healthcare provider can optimize the medical loss ratio by detecting claims frauds
Share This Article
Facebook Pinterest LinkedIn
Share
BySandeep Raut
Follow:
Founder & CEO at Going Digital - Digital Transformation, Data Science, BigData Analytics, IoT Evangelist

Follow us on Facebook

Latest News

ai and satelite technology
How Machine Learning Improves Satellite Object Tracking
Exclusive Machine Learning
Diverse Research Datasets
The 5 Best Platforms Offering the Most Diverse Research Datasets in 2026
Big Data Exclusive
macro intelligence and ai
How Permutable AI is Advancing Macro Intelligence for Complex Global Markets
Artificial Intelligence Exclusive
warehouse accidents
Data Analytics and the Future of Warehouse Safety
Analytics Commentary Exclusive

Stay Connected

1.2KFollowersLike
33.7KFollowersFollow
222FollowersPin

You Might also Like

email marketing with data analytics
Analytics

Mini Guide to Utilizing Data Analytics in Email Marketing

9 Min Read
Image
ITSecurity

DHS wants to stop the rise of large-scale DDoS attacks

2 Min Read

All-Channel Marketing Is NOT Omni-Channel Marketing

6 Min Read
Big Data - Bruno Aziza
AnalyticsBest PracticesBig DataBusiness IntelligenceCloud ComputingCulture/LeadershipData MiningData VisualizationDecision ManagementExclusiveKnowledge ManagementSocial DataSoftware

5 Steps To Winning with Analytics: Have a plan

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.

data-driven web design
5 Great Tips for Using Data Analytics for Website UX
Big Data
AI and chatbots
Chatbots and SEO: How Can Chatbots Improve Your SEO Ranking?
Artificial Intelligence Chatbots Exclusive

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?