PaymentsJournal
SUBSCRIBE
  • Analysts Coverage
  • Truth In Data
  • Podcasts
  • Videos
  • Industry Opinions
  • News
  • Resources
No Result
View All Result
PaymentsJournal
  • Analysts Coverage
  • Truth In Data
  • Podcasts
  • Videos
  • Industry Opinions
  • News
  • Resources
No Result
View All Result
PaymentsJournal
No Result
View All Result

The High Cost of Fraud: Why Companies Should Use AI to Protect their Bottom Line

Ido Lustig by Ido Lustig
April 20, 2023
in Featured Content, Fraud, Industry Opinions
0
fraud

Businessman in shirt working on his laptop in an office. Open space office

0
SHARES
0
VIEWS
Share on FacebookShare on TwitterShare on LinkedIn

With the fragile macroeconomic environment, growing cost-of-living crisis and rising inflation rates pressuring the top and bottom line, businesses face challenging times. In response, business leaders must double down on margin, real revenue, and financial performance to guide their businesses forward. To achieve these ambitions, leaders must prioritize areas within their control. Fraud prevention is one of these areas and one that drives better revenue outcomes and delivers a better customer experience.

Fraud is already a pervasive issue for many businesses, and studies have shown that fraudsters are more likely to strike during slower economic periods. Checkout.com research has shown that a quarter of merchants have reported a significant uptick in fraud over the past year. In real terms, e-commerce fraud is projected to cost merchants more than $48 billion globally this year. Furthermore, fraud can be costly from a reputational and legal standpoint, impacting short- and long-term financial performance.

The Changing Face of Fraud

Compounding the challenge is the increasingly sophisticated and evolving nature of fraud. In recent years, the barrier to entry for fraudsters has decreased, making it easier for them to target businesses with a range of malicious attacks. This trend will likely accelerate in the coming years.

One type that has seen dramatic growth is synthetic fraud, which is now one of the fastest-growing forms of financial crime. Unlike traditional identity theft, where the victim’s financial identity is taken over to deplete existing accounts of funds or establish new accounts, synthetic identities are created by combining real and fake information.

Social engineering is another threat that many businesses have already encountered. With technological developments, the bar has been lowered dramatically for criminals, allowing them to carry out sophisticated social engineering attacks with little to no technical skills or capabilities.

Other attacks, such as credential stuffing, account takeovers, fake accounts, false advertising, order cancellations and fake buyer/seller closed-loops are also currently prominent, impacting all industry verticals from ecommerce and airline ticketing to money transfer and banking services.

The lesson here is that no business can choose to ignore the changing face of fraud. The threats are too acute, and their impact on the bottom line is too significant.

Dynamically Fighting with AI and Machine Learning

In managing such dynamic threats, businesses can no longer rely on a rigid, one-size-fits-all approach to fraud prevention. Nor can they rely on a solution that doesn’t utilize the latest technology to identify and stop fraud.

For these reasons, the most sophisticated and inventive merchants continuously focus on their fraud prevention strategies. Central to their plans is unlocking data that gives them unique and real-time insights into customer behavior, purchase history, or browsing patterns to provide warning signs and prevent fraud.

These businesses are also adopting solutions that utilize the latest AI and machine learning technology. This allows them to take the data they’re collecting and build robust fraud prevention strategies tailored to their risk appetite and customer experience. And, as important, they’re providing advanced capabilities and flexibility, allowing merchants to quickly identify new threats and tailor their strategies accordingly.

Here’s how these businesses are benefiting:

  • Detect patterns and anomalies that humans might miss. Traditional detection methods, such as manual audits and rule-based systems, may not be sufficient to detect new forms of fraud. AI is trained on billions of global transactions and benefits from a global network effect that allows it to analyze vast amounts of data to detect patterns, anomalies, and emerging fraud. A fraud solution with AI and ML capabilities is constantly adapting and training itself to draw inferences from patterns in the data and detect fraud early.
  • Automate and scale fraud prevention. Manual fraud detection and prevention can be time-consuming and expensive. AI can automate many of these processes, reducing the time and resources required to detect and prevent fraud. ML is also infinitely scalable, paving a frictionless path to more transactions without compromising customer experience.
  • Improve accuracy and reduce false positives. Traditional fraud detection methods can generate many false positives, which can be time-consuming to investigate and ultimately result in lost revenue. AI can improve accuracy and reduce false positives by analyzing data more accurately and identifying potential fraud more precisely.
  • Get real-time alerts. AI can provide real-time alerts when potential fraud is detected. This can enable companies to respond quickly and prevent fraud from causing significant financial losses. ML can also identify fraudulent trends in real-time compared to rules-based systems. Real-time alerts help companies identify potential fraudsters and take action to prevent them from causing further harm. With AI and ML, businesses can respond to an attack as it happens, not after the fact.
  • Unlock valuable insights. As AI constantly runs—and learns—on a growing set of data points, it can provide unique insights into fraud trends and patterns. This can help companies identify potential vulnerabilities in their systems/processes and take steps to address them. Businesses can also use these valuable insights to develop more effective fraud prevention strategies and improve overall business operations.

Now is a critical time for businesses to identify areas in their fraud-fighting solutions that are weak and susceptible to attacks from ever-evolving fraudsters. By identifying these areas and building a more robust, bespoke anti-fraud solution that relies on technology like AI and machine learning, businesses can not only ensure that they’re capturing the revenue on the table, but they can also ensure they’re doing so without exposing themselves to undue risk. In short, investing in advanced fraud prevention technologies is not just a smart business decision but an essential one in today’s increasingly risky business environment.

Tags: AIfraudFraud PreventionMachine Learningsynthetic fraud
0
SHARES
0
VIEWS
Share on FacebookShare on TwitterShare on LinkedIn

    Analyst Coverage, Payments Data, and News Delivered Daily

    Sign up for the PaymentsJournal Newsletter to get exclusive insight and data from Javelin Strategy & Research analysts and industry professionals.

    Must Reads

    Google Wallet Expands Features

    Google Wallet Continues to Bet on Digital with Expanded Features

    June 2, 2023
    digital value

    How Embracing Digital Value Can Help Solve the B2C Payments Conundrum

    June 1, 2023
    instant payments, real-time payments, RTP

    Banks Developing Instant Payments Products in the U.S. Should Focus on Billers to Generate New Revenue Streams  

    May 31, 2023
    Digital Wallet Use Delivers on Convenience and Security

    Digital Wallet Use Delivers on Convenience and Security

    May 30, 2023
    5 Ways to Protect Your Financial Institution from a Cyberattack

    5 Ways to Protect Your Financial Institution from a Cyberattack

    May 26, 2023
    traditional banks

    How Traditional Banks Can Modernize Without Risk

    May 25, 2023
    identity fraud

    Javelin’s Identity Fraud Study Highlights the Changing Nature of Fraud

    May 24, 2023
    SASE, security-as-a-service

    Security-as-a-Service Secures
    Distributed IT Models

    May 23, 2023

    Linkedin-in Twitter

    Advertise With Us | About Us | Terms of Use | Privacy Policy | Subscribe
    ©2023 PaymentsJournal.com

    • Analysts Coverage
    • Truth In Data
    • Podcasts
    • Videos
    Menu
    • Analysts Coverage
    • Truth In Data
    • Podcasts
    • Videos
    • Industry Opinions
    • Recent News
    • Resources
    Menu
    • Industry Opinions
    • Recent News
    • Resources
    • Analysts Coverage
    • Truth In Data
    • Podcasts
    • Industry Opinions
    • Faster Payments
    • News
    • Jobs
    • Events
    No Result
    View All Result