Digit
headset_mic account_circle
mail
Sign In
  • Products

    Motor

    • Car Insurance
    • Two Wheeler/Bike Insurance
    • Commercial Vehicle Insurance
    • Taxi/Cab Insurance
    • Auto Rickshaw Insurance
    • Truck Insurance

    Health

    • Health Insurance
    • Super Top-up Health Insurance
    • Arogya Sanjeevani Policy
    • Corporate Health Insurance
    • Health Insurance Portability

    Other

    • International Travel Insurance
    • Flight Delay
    • Shop Insurance
    • Home Insurance
  • Claims

    • File a Claim
    • File Health Claim
    • File Motor Claim for Garages
    • COVID-19 Assistance
    • Claim Status
  • Renewals
  • Become an Agent
  • Digit Products

    Motor Insurance

    • Car Insurance 25% OFF
    • Two Wheeler/Bike Insurance
    • Commercial Vehicle Insurance
    • Taxi/Cab Insurance 15% OFF
    • Auto Rickshaw Insurance
    • Truck Insurance

    Health Insurance

    • Health Insurance
    • Super Top-Up Health Insurance
    • OPD Health Insurance
    • Arogya Sanjeevani Policy
    • Personal Accident Insurance
    • Corporate Health Insurance

    Other Insurance

    • International Travel Insurance
    • Flight Delay
    • Shop Insurance
    • Home Insurance
  • Claims

    File a Claim

    File Health Claim

    File Motor Claim for Garages

    COVID-19 Assistance

    Claim Status

  • Renewals

    Become an Agent

  • Support
    Sign In
    • edit Edit Policy
    • download Download Policy
    • person_pin My Service Requests
    • check Check Policy Status
    call 1800-258-5956 mail_outline hello@godigit.com whatsapp 70260 61234

    Our WhatsApp number cannot be used for calls. This is a chat only number.

  • My Account
    account_circle
    • autorenew Renew My Policy
    • download Download My Policy
    logout SIGN OUT
    call 1800-258-5956 mail_outline hello@godigit.com whatsapp 70260 61234

    Our WhatsApp number cannot be used for calls. This is a chat only number.

  • login
  • about
  • contact
  • careers
More Products

Motor

  • Car Insurance
  • Two Wheeler/Bike Insurance
  • Commercial Vehicle Insurance
  • Taxi/Cab Insurance
  • Auto Rickshaw Insurance
  • Truck Insurance

Health

  • Health Insurance
  • Super Top-up Health Insurance
  • Arogya Sanjeevani Policy
  • Corporate Health Insurance
  • Health Insurance Portability

Other

  • International Travel Insurance
  • Flight Delay
  • Shop Insurance
  • Home Insurance

Support

close
account_circle
  • edit Edit Policy
  • download Download Policy
  • person_pin My Service Requests
  • check Check Policy Status
  • autorenew Renew My Policy
  • download Download My Policy
logout SIGN OUT
call 1800-258-5956 mail_outline hello@godigit.com whatsapp 70260 61234

Our WhatsApp number cannot be used for calls. This is a chat only number.

Do the Digit Insurance

Trusted by 3 Crore+ Indians

  • Health
    Health
  • Pay as you Drive
    Car Side View
    Car
  • trending icon

    Third-party premium has changed from 1st June. Renew now

    Motorcycle Side View
    Bike
  • auto rikshaw
    Commercial
  • Covers COVID-19
    Travel Airplane
    Travel
  • More products
    More
ENTER YOUR CAR NUMBER
keyboard_arrow_right
DON'T KNOW YOUR CAR NUMBER?
keyboard_arrow_right
renew digit policy keyboard_arrow_right

I agree to the  Terms & Conditions

{{(!carWheelerCtrl.registrationNumberCardShow || carWheelerCtrl.localStorageValues.vehicle.isVehicleNew) ? 'I know my Reg num' : 'Don’t have Reg num?'}}
keyboard_arrow_right
It’s a brand new Car
keyboard_arrow_right
renew digit policy keyboard_arrow_right

I agree to the  Terms & Conditions

Terms and conditions

    false false
    Enter valid registration number
    DON'T KNOW REGISTRATION NUMBER?
    keyboard_arrow_right
    I KNOW MY REGISTRATION NUMBER
    keyboard_arrow_right
    IT'S A NEW BIKE
    keyboard_arrow_right
    RENEW DIGIT POLICY
    keyboard_arrow_right

    I agree to the  Terms & Conditions

    Continue with {{bikeCtrl.lastVisitedData.lastVisitedUrl.indexOf('DigitPaymentGateway/payments') !== -1 ? 'payment completion': 'previous choice'}}

    {{bikeCtrl.lastVisitedData.vehicle.makeModel | toTitleCase}} {{bikeCtrl.lastVisitedData.vehicle.variant? (bikeCtrl.lastVisitedData.vehicle.variant|toTitleCase): (bikeCtrl.lastVisitedData.vehicleCharacteristics.vehicleType | toTitleCase)}}

    {{bikeCtrl.lastVisitedData.vehicle.licensePlateNumber}}

    {{bikeCtrl.selectedPlanDisplay[bikeCtrl.lastVisitedData.dropOffSelectedPlan? bikeCtrl.lastVisitedData.dropOffSelectedPlan: bikeCtrl.lastVisitedData.selectedPlan]}}

    -

    ₹{{((bikeCtrl.lastVisitedData.dropOffSelectedPlan ? bikeCtrl.lastVisitedData.dropOffGrossPremium:bikeCtrl.lastVisitedData.chosePlan.grossPremium) .replace('INR ','')).split('.')[0] | rupeeFormatWithComma}} (Incl 18% GST)

    keyboard_arrow_right
    IT'S A NEW BIKE
    keyboard_arrow_right
    RENEW DIGIT POLICY
    keyboard_arrow_right

    I agree to the  Terms & Conditions

    Continue with {{twoWheelerCtrl.lastVisitedData.lastVisitedUrl.indexOf('DigitPaymentGateway/payments') !== -1 ? 'payment completion': 'previous choice'}}

    {{twoWheelerCtrl.lastVisitedData.vehicle.make |toTitleCase}} {{twoWheelerCtrl.lastVisitedData.vehicle.model | toTitleCase}} {{twoWheelerCtrl.lastVisitedData.vehicle.variant? (twoWheelerCtrl.lastVisitedData.vehicle.variant |toTitleCase):''}}

    {{twoWheelerCtrl.lastVisitedData.vehicle.licensePlateNumber}}

    {{twoWheelerCtrl.lastVisitedData.selectedPlan}}

    -

    ₹{{((twoWheelerCtrl.lastVisitedData.quickQuoteResponse.plans[twoWheelerCtrl.lastVisitedData.selectedPlan].resposeBody.grossPremium) .replace('INR ', '')).split('.')[0] | rupeeFormatWithComma}} (Incl 18% GST)

    • Geography
    • Country
    {{geography.name}}

    Popular Countries (You can select more thane one)

    • {{country}}

    DONE
    Please select geography

    I agree to the  Terms & Conditions

    As mandated by Spanish Authorities your travel insurance needs to extend 15 days after your trip ends.
    We will extend your coverage period accordingly.

    false false false false false false false false false false false false

    Port my existing Policy

    keyboard_arrow_right
    or renew digit policy keyboard_arrow_right
    Chat with an expert

    I agree to the  Terms & Conditions

    You can select more than one member

    • -+ Max kids
      (s)
    ENTER YOUR REGISTRATION NUMBER
    keyboard_arrow_right
    DON'T KNOW YOUR REGISTRATION NUMBER
    keyboard_arrow_right
    or renew digit policy keyboard_arrow_right

    I agree to the  Terms & Conditions

    Terms and conditions

    Terms and conditions

    Do the Digit Insurance
    • Health
    • Car
    • Bike
    • Commercial
    • Travel
    • More Products

    Top 10 Ways to Detect Credit Card Fraud

    credit caed fraud
    (source: medium)

    A growing focus is evident on technology in the current world, especially regarding financial transactions. While this can be a more convenient and easier way of operations, it can also result in fraudulent activities. 

    You might unknowingly let hackers into your financial activities, which can cause major losses.  Wondering about the detection of credit card frauds? This article will give you a comprehensive guide regarding the same

    What Is Credit Card Fraud Detection?

    Credit card fraud has been on the rise in recent times. In most cases, the fraud is done online. A fraud tries to hack into your system and steal your credit card details to use it. In case of offline fraud, your card gets stolen physically when you submit it for any reason in a busy area. If there is falsified information in credit card applications, it is considered identity fraud. 

    There are two ways to detect credit card fraud. The Data Science Team comes together to reveal and prevent fraudulent transactions through technology. It helps to reveal transaction details such as Date, User Zone, Amount, Provider, Product Category, etc. There is also the conventional way, which helps to detect some obvious frauds without much use of technology.

    What Are the Best Ways to Detect Credit Card Frauds?

    detect credit card
    (source: futurecdn)

    Now, if you are wondering how to detect credit card fraud, there can be multiple ways to do so. Here are some of the best and most convenient methods experts use for detecting such frauds. 

    1. Decision Tree

    This type of detection works in the same logic as the similarity tree. It is outlined with leaves and nodes, which include attributes and factors. This method helps to define ratios in terms of transactions, satisfying certain conditions. Most experts prefer this detection method since it is easily comprehended and displayed.

    Experts must start by entering the decisions in the node boxes and then list their options. They use connectors to analyse the best option for a problem. While this method can be effective, it can be time-consuming as they need to check every transaction individually.

    2. Predictive Analytics and Algorithms

    Organisations usually collect a vast amount of data while doing business, which they can use to detect fraud patterns and possibilities. While predictive analysis cannot detect the exact type of fraud, it helps to identify a possibility of what might happen in future with a degree of reliability. Here, algorithms can be effective for fraud detection of credit cards. 

    Algorithms are mainly used to set rules based on logic. As a result, it helps to categorise the data into either suspicious or non-suspicious activities. It is mainly useful for home insurance data. Moreover, it uses an array of methods that point out suspicious transactions. This way, experts can predict frauds on your credit card and alert you against the same.

    3. Clustering Techniques

    Such techniques are used for identifying behavioural fraud. The Peer Group Analysis is a popular clustering method for detecting credit card frauds. It identifies credit card accounts behaving strangely towards other accounts. When experts notice such activities, they flag this account. They then contact the account holder to discuss the issues with the account. 

    Once they discuss with the customers, experts better understand the issues. For instance, a customer might be sending high-amount transactions to another account. However, they are used to making smaller transactions. 

    If they are genuinely making these transactions, there will be no need to continue with the flagging. Otherwise, the customer can take legal steps to identify the fraud.

    4. K-Nearest Neighbour Algorithms

    This technique is another useful one when it comes to the detection of credit card fraud. It uses the available instances and classifies new ones based on similarities and patterns. It has been one of the most popular conventional methods of detecting credit card fraud, used since the 1970s. 

    KNN is an effective learning method based on instance that helps experts analyse frauds from credit card transactions. It starts with an original set of instances and then compares new ones with the former. 

    This allows the experts to identify if there are any possibilities of unusual patterns. However, it has a few irrelevant attributes, which might lead to impracticalities in this process.

    5. Neural Networks

    If you are wondering how to detect fraud in credit cards, neural networks can be an effective answer. Here, the experts consider a dataset containing credit card transactions. In most cases, they are likely to use numerical variables and principal components. 

    They usually consider features like time and amount in the dataset to analyse the time lapse between two transactions. 

    According to a study, 3-Layer Neural Network can effectively predict normal credit card fraud cases with 99% accuracy. However, this method might have a drawback since it uses data clustering. Experts can only collate it by account type.

    6. Naive Bayes Classifiers

    John and Langley came up with the technique of Naive Bayes Classifiers in 1995. It can also be effective for detecting and identifying frauds in credit card transactions. While using this technique, experts take the help of a dataset. With this, they target the classes that can predict future instances. 

    This technique is beneficial for helping experts with genuine and effective fraud detection. While it can be slightly complicated and time-consuming, it can be used for getting accurate results. The use of the databases can also predict future instances of similar fraud.

    7. Support Vector Machines (SVMs)

    The SVM is another statistical learning method effective for detecting credit card fraud. It is a classification technique predicting patterns into either fraud or legitimate class. In most cases, experts use this technique for binary classifications. This method effectively identifies patterns, including face recognition, bioinformatics, and text categorisations. 

    If the experts find the test instance to be within the learned region, they will classify it as normal. However, outside the learned region, it will be anomalous. This system can give a basic idea regarding the possibility of fraud in credit card transactions.

    8. Bagging Ensemble Classifier

    Leo Breiman came up with this technique in 1994. It has opened doors for improvement regarding machine learning algorithms. Recently, it has been popular among experts for detecting credit card frauds with maximum accuracy. Moreover, this method is simple and can be completed in a shorter time. 

    Experts often prefer this technique as it does not require a comprehensive dataset. It is a fast method and can analyse large databases in a comparatively lower period. This makes it easier to scan credit card transactions and identify fraud.

    9. Outlier Models

    The use of outlier models can also be useful for detecting fraud patterns in credit card transactions. It allows the detection solution to adjust dynamically with the data stream since the fraud pattern might not always be linear. These models can assist the experts in detecting fraud in emerging markets, where there is insufficient data to make proper predictions. 

    Outlier models are useful for tracking transactions and identifying unusual activities. For instance, if a high-amount transaction on an account is used for much lower transactions, outlier models will flag the card. It requires less data and can easily adjust in real-time based on the transaction system.

    10. Global Profiling

    This method can help identify fraud trends initiated across other countries. One can use the data collected through profiling to identify the emerging trends and latest fraud schemes. The latest applications and software allow financial institutions to set protection tool sets and expand the possibilities of avoiding fraud based on trends and patterns.

    How Can Machine Learning Help With Fraud Detection?

    Machine learning is currently the most effective means of detecting credit card fraud. This process includes deploying an ML model and example datasets of credit card transactions. It helps to train the model in recognising fraud patterns and possibilities. As this model is self-learning, it can adopt the latest trends and patterns of credit card fraud. 

    ML is the science of certain and applying algorithms, which assists the models in learning from the past. It helps to identify fraud from credit card transactions without raising suspicions of the fraudsters. It has the following benefits, making it one of the most sought-after means of credit card fraud detection. 

    • More Effective than Humans: ML models create algorithms based on the assumptions of fraudulent transactions. These algorithms work more effectively than humans. They do not miss out on any suspicious activity even from extensive datasets. They are, therefore, capable of determining the stealthiest fraudulent patterns. 
    • Handles Overload: Online fraud of credit cards have become quite common recently. Fraudsters and hackers use the most advanced technologies for their activities. Even data scientists might not be capable of predicting the moves of the fraudsters in this scenario. ML models can come to the rescue. The algorithms work all day to identify such patterns. 
    • Better than Traditional Systems: The traditional fraud detection system is much more static and rule-based. It is hardly capable of adapting to the current changes in technology. Moreover, it relies heavily on human labour. 

    ML models can beat this system in terms of speed, quality and cost-effectiveness. It helps to detect fraud much faster without making mistakes. 

    The algorithms of ML models come under the following types.

    • Supervised learning
    • Unsupervised learning
    • Semi-supervised learning
    • Reinforcement learning

    With these systems, ML makes detecting credit card fraud much easier and faster. It has made this system preferable and popular for most experts. It is less expensive, and the workload is also much lower considering the efficiency of the algorithms. 

    Hence, as you can see, the detection of credit card fraud can be an essential process in recent times. There has been a growing trend toward fraud and hacking of credit cards. As this article pointed out, there can be various ways to detect such frauds. However, technological ways, especially machine learning methods, can be more effective than traditional ones.

    Frequently Asked Questions

    Which tools are used to protect credit cards from fraud?

    If you use your credit card regularly for business purposes, you must protect it properly. Address Verification Service (AVS) is a common tool for fraud prevention concerning card-not-present (CNP) transactions. It compares the billing address used in transactions with the bank’s actual address to identify fraud.

    If you use your credit card regularly for business purposes, you must protect it properly. Address Verification Service (AVS) is a common tool for fraud prevention concerning card-not-present (CNP) transactions. It compares the billing address used in transactions with the bank’s actual address to identify fraud.

    How can I identify fraudulent activities on my credit card?

    You need to constantly monitor your transactions to identify any unusual patterns. It might indicate fraud if you notice strange purchases, small charges, or unfamiliar company names on your bank statements. Moreover, payments made in other locations or diminishing credit scores might indicate the same.

    You need to constantly monitor your transactions to identify any unusual patterns. It might indicate fraud if you notice strange purchases, small charges, or unfamiliar company names on your bank statements. Moreover, payments made in other locations or diminishing credit scores might indicate the same.

    Please try one more time!

    Request URL:
    Status Code:
    Request Payload:
    Response Data:

    Important Articles related to Finance

    Employee Provident Fund

    EPF Registration Process

    How to Withdraw EPF Online

    Atal Pension Yojana Calculator

    How to Change Details in Atal Pension Yojana Scheme

    How to get Atal Pension Yojana Statement

    How to Close Atal Pension Yojana Account

    Sukanya Samriddhi Yojana

    How to Open Sukanya Samriddhi Yojana Account

    Sukanya Samriddhi Yojana Calculator

    What is Public Provident Fund?

    How to Open PPF Account?

    How to Check PPF Account Balance?

    Eligibility Criteria to Open PPF Account

    Types of PPF Forms

    How to Withdraw PPF Online?

    How to Invest in PPF?

    Financial Planning for Salaried Employees

    Importance of Financial Planning

    Financial Planning Tips for Women

    How to Apply for Atal Pension Yojana?

    What is UAN Number?

    How to check EPF Balance

    KVP Calculator

    Voluntary Provident Fund

    Difference between EPF and EPS

    How to Check Sukanya Samriddhi Account Balance?

    Investment Planning Guides

    Professional Tax in India

    Show more

    Disclaimer: This information is added only for informative purposes and collected from different sources across the Internet. Digit Insurance is not promoting or recommending anything here. Please verify the information before making any decisions.

    Download Digit App

    close
    1. Digit Insurance
    2. Finance
    3. Identity Theft and Fraud
    4. Credit Card Fraud Detection

    Last updated: 2023-03-23

    Digit
    • about
    • contact
    • career
    Products
    • Car Insurance
    • Bike Insurance
    • Travel Insurance
    • Health Insurance
    • Property Insurance
    • Shop Insurance
    • Group Health Insurance
    • Arogya Sanjeevani Policy
    • Commercial Vehicle Insurance
    • Super Top-up Health Insurance
    • Flight Delay
    Resources
    • Blog
    • Press
    • Download Policy
    • Grievance Redressal Procedure
    • Cancel e-Mandate
    Agent & Partnerships
    • Become an Agent
    • Become Digit POSP
    • Garages claim intimation
    Services
    • Claims
    • Renewals
    • Digit Cashless Garages
    • Digit Cashless Hospitals
    Get our app
    Download man
    App Store Google Play

    Other Products
    • Fire Insurance
    • Burglary Insurance
    • Building Insurance
    • Bus Insurance
    • Tractor Insurance
    • Commercial Van Insurance
    • Passenger Carrying Vehicle Insurance
    • Heavy Vehicle Insurance
    • Goods Carrying Vehicle Insurance
    • Activa Insurance
    • Jupiter Insurance
    • Bullet Insurance
    • Student Travel Insurance
    • Schengen Visa Travel Insurance
    Health Insurance Guides
    • Individual Health Insurance
    • Family Health Insurance
    • Health Insurance for Parents
    • Health Insurance Premium Calculator
    • Compare Health Insurance
    • Health Insurance for Senior Citizens
    • Health Insurance with Maternity Cover
    • Corona Kavach Policy
    • Corona Rakshak Policy
    • हेल्थ इन्शुरन्स
    • फैमिली हेल्थ इन्शुरन्स
    Car Insurance Guides
    • Third Party Car Insurance
    • Comprehensive Car Insurance
    • Zero Depreciation Car Insurance
    • NCB in Car Insurance
    • IDV Calculator for Car
    • Bumper to Bumper Car Insurance
    • Car Insurance Calculator
    • Own Damage Car Insurance
    • Comprehensive vs Third Party Insurance
    • Compare Car Insurance
    • Find Vehicle Registration Details Online
    Bike Insurance Guides
    • Third Party Bike Insurance
    • Comprehensive Bike Insurance
    • Zero Depreciation Bike Insurance
    • NCB in Two Wheeler Insurance
    • IDV Value Calculator for Bike
    • Add-on Cover in Bike Insurance
    • Bike Insurance Calculator
    • Own Damage Bike Insurance
    • Comprehensive vs Third Party Bike Insurance
    • Compare Bike Insurance
    • Royal Enfield Insurance
    • TVS Insurance
    • Hero Bike Insurance
    Other Guides
    • Types of Insurance
    • Types of General Insurance
    • Types of Motor Insurance
    • International Driving License
    • Visa on Arrival for Indians
    • Visa Free Countries for Indians
    • Comprehensive vs Zero Depreciation
    • Coronavirus Health Insurance
    • Coronavirus Symptoms Checker
    • Indian Passport Rank
    • Digit Illness Group Insurance
    • Hero Splendor Insurance
    • Access Insurance
    • Scooty Insurance
    Calculators
    • SME Buddy Calculator
    • Home Loan EMI Calculator
    • Bike Loan EMI Calculator
    • Car Loan EMI Calculator
    • HRA Exemption Calculator
    • Sukanya Samriddhi Yojana Calculator
    • SIP Calculator
    • RD Calculator
    • SWP Calculator
    • GST Calculator
    • PPF Calculator
    • Personal Loan EMI Calculator
    • EMI Calculator
    • Individual Income Tax Slab
    • Tax Saving Options other than 80C
    Finance Guides
    • What is Credit Score
    • Public Provident Fund
    • How to Open PPF Account?
    • How to open Sukanya Samriddhi Account
    • What is GST?
    • GST Registration in India
    • PAN Card
    • Aadhaar Card
    • Property Tax
    • Road Tax
    • Passport Process
    • Income Tax Slabs
    • How to Save Income Tax in India
    • Tax Deductions under Section 80C
    Traffic Rules
    • PUC Certificate
    • Vehicle Registration Certificate
    • New Traffic Fines
    • Fine for Driving without Helmet
    • Types of Driving Licence in India
    • Driving Licence in Delhi
    • Driving Licence in Bangalore
    • Driving Licence in Jaipur
    • Bangalore Traffic Fines
    • Pune RTO Fine
    • Own Damage Insurance
    Business Products
    • Business Insurance
    • Management Liability Insurance
    • General Liability Insurance
    • Workmen Compensation Insurance
    • Fidelity Insurance
    • Professional Liability Insurance
    • Money Insurance Policy
    • Sign Board Insurance
    • Plate Glass Insurance
    • Erection All Risk Insurance
    • Contractors' All Risks Insurance
    • Directors and Officers Liability Insurance
    • Marine Cargo Insurance
    • Contractors Plant and Machinery Insurance
    RTO Offices in India
    • RTO Office
    • RTO Pune
    • RTO Ahmedabad
    • RTO Bangalore
    • RTO Mumbai
    • RTO Delhi
    • RTO Lucknow
    • RTO Thane
    • RTO Chennai
    Important Links
    • Digit Insurance Reviews
    • Car Insurance Reviews
    • Bike Insurance Reviews
    • Commercial Vehicle Insurance Reviews
    • Travel Insurance Reviews
    • Health Insurance Reviews
    • Mobile Insurance Reviews
    • Become a Digit Partner
    • General Insurance Agent
    • Health Insurance Agent
    • Motor Insurance Agent
    Car Brands & Models
    • Maruti Insurance
    • Toyota Car Insurance
    • Tata Car Insurance
    • Hyundai Car Insurance
    • Kia Car Insurance
    • Mahindra Car Insurance
    • Tata Tiago Insurance
    • Tata Nexon Insurance
    • Hyundai i20 Insurance
    • Creta Insurance
    • Baleno Insurance
    Downloads Do Not Disturb (DND) Public Disclosures Investor Relations Stewardship Policy IRDAI Privacy Policy

    CIN: U66010PN2016PLC167410, IRDAI Reg. No. 158.

    Go Digit General Insurance Limited (formerly known as Oben General Insurance Ltd.) - Registered Office Address - 1 to 6 floors, Ananta One (AR One), Pride Hotel Lane, Narveer Tanaji Wadi, City Survey No.1579, Shivaji Nagar, Pune-411005, Maharashtra | Corporate Office Address - Atlantis, 95, 4th B Cross Road, Koramangala Industrial Layout, 5th Block, Bengaluru-560095, Karnataka | Trade logo of Go Digit General Insurance Ltd. displayed above belongs to Go Digit lnfoworks Services Private Limited and is provided and used by Go Digit General Insurance Ltd. under license.