Digital Technology

Optimizing the Tenant Selection Process to Protect Against Fraud

To protect themselves against fraudulent applicants, apartment owners and operators need to leverage advanced screening tools and technologies.

Published: August 23, 2023 by Manjit Sohal
Reduce Online Customer Application Friction with Automation

Financial institutions need an automated, data-driven solution to simplify and streamline the online form completion process.

Published: August 22, 2023 by Theresa Nguyen
The Three C’s of a Successful Collections Strategy

Discover how to create a successful collections strategy to maximize recovery rates through communication, choice, and control.

Published: August 9, 2023 by Stefani Wendel
Fraud Detection in Banking

More than half of U.S. businesses say they discuss fraud management often, making fraud detection in banking top-of-mind. Banking fraud prevention can seem daunting, but with the proper tools, banks, credit unions, fintechs, and other financial institutions can frustrate and root out fraudsters while maintaining a positive experience for good customers. What is banking fraud? Banking fraud is a type of financial crime that uses illegal means to obtain money, assets, or other property owned or held by a bank, other financial institution, or customers of the bank. This type of fraud can be difficult to detect when misclassified as credit risk or written off as a loss rather than investigated and prevented in the future. Fraud that impacts financial institutions consists of small-scale one-off events or larger efforts perpetrated by fraud rings. Not long ago, many of the techniques utilized by fraudsters required in-person or phone-based activities. Now, many of these activities are online, making it easier for fraudsters to disguise their intent and perpetrate multiple attacks at once or in sequence. Banking fraud can include: Identity theft: When a bad actor steals a consumer’s personal information and uses it to take money, open credit accounts, make purchases, and more. Check fraud: This type of fraud occurs when a fraudster writes a bad check, forges information, or steals and alters someone else’s check. Credit card fraud: A form of identity theft where a bad actor makes purchases or gets a cash advance in the name of an unsuspecting consumer. The fraudster may takeover an existing account by gaining access to account numbers online, steal a physical card, or open a new account in someone else’s name.  Phishing: These malicious efforts allow scammers to steal personal and account information through use of email, or in the case of smishing, through text messages. The fraudster often sends a link to the consumer that looks legitimate but is designed to steal login information, personally identifiable information, and more. Direct deposit account fraud: Also known as DDA fraud, criminals monetize stolen information to open new accounts and divert funds from payroll, assistance programs, and more. Unfortunately, this type of fraud doesn’t just lead to lost funds – it also exposes consumer data, impacts banks’ reputations, and has larger implications for the financial system. Today, top concerns for banks include generative AI (GenAI) fraud, peer-to-peer (P2P) payment scams, identity theft and transaction fraud. Without the proper detection and prevention techniques, it’s difficult for banks to keep fraudsters perpetrating these schemes out. What is banking fraud prevention? Detecting and preventing banking fraud consists of a set of techniques and tasks that help protect customers, assets and systems from those with malicious intent. Risk management solutions for banks identify fraudulent access attempts, suspicious transfer requests, signs of false identities, and more. The financial industry is constantly evolving, and so are fraudsters. As a result, it’s important for organizations to stay ahead of the curve by investing in new fraud prevention technologies. Depending on the size and sophistication of your institution, the tools and techniques that comprise your banking fraud prevention solutions may look different. However, every strategy should include multiple layers of friction designed to trip up fraudsters enough to abandon their efforts, and include flags for suspicious activity and other indicators that a user or transaction requires further scrutiny.   Some of the emerging trends in banking fraud prevention include: Use of artificial intelligence (AI) and machine learning (ML). While these technologies aren’t new, they are finding footing across industries as they can be used to identify patterns consistent with fraudulent activity – some of which are difficult or time-consuming to detect with traditional methods. Behavioral analytics and biometrics. By noting standard customer behaviors — e.g., which devices they use and when — and how they use those devices — looking for markers of human behavior vs. bot or fraud ring activity — organizations can flag riskier users for additional authentication and verification. Leveraging additional data sources. By looking beyond standard credit reports when opening credit accounts, organizations can better detect signs of identity theft, synthetic identities, and even potential first-party fraud.     With real-time fraud detection tools in place, financial institutions can more easily identify good consumers and allow them to complete their requests while applying the right amount and type of friction to detect and prevent fraud.   How to prevent and detect banking fraud In order to be successful in the fight against fraud and keep yourself and your customers safe, financial institutions of all sizes and types must: Balance risk mitigation with the customer experience Ensure seamless interactions across platforms for known consumers who present little to no risk Leverage proper identity resolution and verification tools Recognize good consumers and apply the proper fraud mitigation techniques to riskier scenarios With Experian’s interconnected approach to fraud detection in banking, incorporating data, analytics, fraud risk scores, device intelligence, and more, you can track and assess various activities and determine where additional authentication, friction, or human intervention is required. Learn more

Published: July 19, 2023 by Guest Contributor
Experian’s 2023 Identity and Fraud Report

Experian's identity and fraud report explores the evolving fraud landscape and influence on identity, the consumer experience, and business strategies.

Published: July 5, 2023 by Guest Contributor
Navigating the End of the Student Loan Payment Holidays

Student loan borrowers may face new challenges and fears once payments resume. Learn about the implications and how loan servicers and lenders can respond.

Published: June 20, 2023 by Theresa Nguyen
Amid Banking Uncertainty, Fraudsters Strike

By leveraging an array of tools and technologies, businesses can tailor their fraud prevention strategies to suit the specific needs of their customers.

Published: June 13, 2023 by Guest Contributor
Experian CrossCore® Recognized as an Overall Leader by KuppingerCole

CrossCore named Overall Leader, Product Leader in Fraud Reduction Intelligence Platforms, Innovation Leader and Market Leader in Fraud Reduction..

Published: May 26, 2023 by Guest Contributor
The Importance of Identity Resolution for Credit Marketing

Explore what identity resolution for credit marketing is and how it enables lenders to create more cohesive and personalized customer interactions.

Published: May 25, 2023 by Theresa Nguyen
What Is Predictive Analytics: A Comprehensive Guide

Business leaders accross industries are using predictive analytics to make informed decisions.

Published: April 27, 2023 by Julie.JLee@experian.com
Gen Z Banking: How Financial Institutions Can Win Over the Next Generation

For banks, remaining competitive doesn’t just involve enhancing their processes — it requires investing in the future of their business: Gen Z.

Published: April 24, 2023 by Theresa Nguyen
Case Study: Accelerating Lending Decisions with Digital Prequalification

Learn how Washington State Employees Credit Union increased their revenue and member satisfaction by implementing a digital prequalification process.

Published: April 18, 2023 by Laura Burrows
Make Smarter, Faster Decisions with a Custom Machine Learning Model

With predictive custom machine learning models, lenders can target the right audience, score applicants more accurately, and mitigate credit risk.

Published: March 6, 2023 by Theresa Nguyen
Optimize Your Customer Acquisition Process

To increase efficiency and digital customer acquisition, forward-thinking lenders are seeking flexible technologies that enable automated decisioning.

Published: February 28, 2023 by Theresa Nguyen

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