How to Prevent Banking Fraud: Solution to Effective Fraud Management

Banking fraud turned into one of the major issues for financial institutions in 2023. Both service providers and their clients were involved in different kinds of threats usually associated with suspicious activities. According to recent fraud analytics, the banking industry lost around $5.8 billion because of a lack of effective fraud prevention means.

More than 3 million financial fraud reports were sent from consumers. So, the main mission for the business is not only to reduce losses but also to protect customers to ensure better digital onboarding and exceptional user experience. This is where the integration of banking fraud prevention tolls might be a good solution.

Importance of Fraud Detection in Banking

Banking systems quickly adopts digital trends while moving online. We now see enhanced integration of crypto infrastructure alongside traditional financial services and banking products. It appears that fraudsters also develop their techniques to compromise digital banking networks.

Meanwhile, fraud monitoring and analysis show that 96% of all consumers consider online safety a major point when selecting a banking app or service. This is why fraud prevention appears to be a major concern for business owners.

To learn what particular types of banking fraud detection to apply, we need to clarify what we are dealing with today. The most common banking fraud types involve phishing, account takeovers, credit card fraud, credential/identity theft, money laundering, wire fraud, and more.

On the one hand, financial institutions now have up-to-date fraud prevention means thanks to device fingerprinting, MFA, and biometry. However, fraudsters utilize advanced means to steal customer information:

• Biometry spoofing. Biometric authentication proved to be an effective banking fraud detection tool. On the other hand, hackers learned how to steal not only bank account info but also other types of personal information (photos, videos, or even fingerprints). The stolen content is used for spoofing the victim’s identity and applying for banking products.
• Fraud as a Service. Fraudulent activity is not delivered as a kind of service. Users may come across fraudulent marketplaces. There, people buy stolen credentials or special tools to develop malicious software on their own.

It increases the risk of banking fraud. What’s more, banks are put under pressure because of growing responsibility not only for their own revenue and infrastructure but also for their clients.

Major Fraud Challenges for Banks

Businesses have no other choice but to utilize advanced banking fraud prevention tools. With these means, they get a chance to fight fraudsters back within the digital ecosystem. The main mission for organizations is to secure and grow client loyalty, ensure safe customer onboarding, and handle other crucial challenges.

Account Opening Fraud

While checking the IDs of every new customer costs billions, banks prefer using simplified approval methods. On the one hand, they are fast and let users quickly integrate with the banking ecosystem. On the other hand, it reserves enough space for hackers to open bank accounts with fake or stolen IDs.

Account Takeovers

Account takeover is another common threat. Fraudsters use special techniques to acquire user’s access data. They gain login and password to enter the banking application and perform fraudulent activities on the victim’s behalf (mainly, applying for credit cards, quick cash, or loans). Account protection is another great issue for any financial institution.

Fraudulent Transactions

Once the account has been compromised or broken, hackers can use stolen data to complete different financial transactions (for example, fake bank statements). They can buy something or transfer funds to their own accounts. This is why transaction monitoring is a crucial part of the entire digital risk management strategy every bank is supposed to have.

Juicyscore Solution Against Fraud in Banking

JuicyScore solution comes as an ultimate banking fraud protection toolkit. It was designed to help businesses combat fraudsters in their own game. By utilizing AI and ML-based technologies, our team created up-to-date software to oppose brick-and-mortar check fraud monitoring engines and approaches.

Here are the ways banks can benefit from our approach to banking fraud:

• Fraud Identification Systems. We employ over 30 different device authentication approaches to generate an accurate end-user linkage based on a variety of behavioral biometric data attributes.
• Fraud Risk Reduction. The system automatically pinpoints a number of risk factors. They include the quality of the network infrastructure, Internet connection, and other technical parameters analyzed and evaluated alongside 200+ configurations, attributes, and device-assisted markers.

In the end, financial institutions can benefit from safe customer onboarding, secured client data, and overall enhanced client experience.

Leveraging Machine Learning

Major banks generally used traditional rule-based engines for banking fraud monitoring. While fraudulent techniques evolve, these technologies no longer make sense., The key problem is that they cannot detect and fight fraud in real time and combat them in the future.

JuicyScore solution relies on advanced machine-learning technologies. It does not just protect banks from fraud. It actually learns from users’ behavioral parameters to detect potential mismatches and anomalies. When the abnormality is spotted, the system considers it a red flag. The software uses a powerful data vector letting banks ensure better decision-making with minimum risks.

Real-Time Fraud Prevention

Banking fraud prevention in real-time uses monitoring instruments that process massive data quantities at a time. Banks deal with millions of transactions daily. All of them must be tracked and evaluated in real-time. This is where our scoring model will help. The data vector uses 65,000+ parameters to analyze technical and behavioral factors in real time.

In contrast to brick-and-mortar rule-based engines, our software lets banks easily customize their risk management systems thanks to high adaptability. It generates accurate digital profiles and examines rare events and conditions to detect the slightest risk of fraud.

Key Features

The software creates the end-user digital profile using behavioral biometry and device configuration indicators. It assists financial institutions in locating various forms of fraudulent activity by generating data related to end-user devices featuring such technical parameters as apps installed, software settings, and other relevant details. It ensures the accuracy and trustworthiness of the fraud risk estimation model brought by our solution.

The software analyzes thousands to identify the slightest anomaly. Put another way, the solution monitors several technological and behavioral aspects. Red flags or alerts are generated by the system when a device operation mismatch is spotted.

Device Fingerprinting

Imagine a fraudster, who stole credentials with the aim of applying for a banking product. A hacker will use a different device that is not similar to the victim’s gadget. Thesis where our solution examines a range of device-assisted parameters to identify if the given smartphone or tablet really belongs to a user or if it is a fraud.
The system processes a variety of secondary banking fraud risk criteria in addition to baseline parameters. The monitoring of gadget properties is the principle behind the approach. In order to accurately perform device fingerprinting, our technologies are able to identify the type of carrier (tablet, desktop, laptop, or mobile), screen size, display quality, RAM, and other essential characteristics.

Behavioral Analysis

Here is another scenario for consideration. Let’s say, a fraudster uses device randomizers or controls the victim’s device remotely. Various apps help hackers manipulate other user’s gadgets and personal data.
However, the way a fraudster engages with the device differs from its real owner. So, the idea is to find such mismatches by analyzing a set of behavioral parameters (the speed of typing, apps installed, dwell and flight session time, reading speed, etc.). Our service consequently spots abnormalities. These could indicate device cloning or randomization, remote access, different routing indications, and more.

Data Enrichment Solutions

In order to provide superior real-time anti-fraud banking safeguards, our system examines various factors:

• Behavioral Parameters. They cover the kinds and quantity of installed apps throughout a specified period of time. In the event of a mismatch, it assists in identifying possible anomalies and locates false or stolen identities.
• Technical Parameters. These include software and hardware configurations, Internet connection quality and setup, type of mobile carrier, installed browser or utilized OS, etc.
• Additional Parameters. Our advanced data vector considers a set of extra stop-factors. They also help to reveal randomizers, remote control applications, and other tools that hackers employ to perform identity thefts.

With the improved anti-fraud toolkit, banks will keep their customers and infrastructure safe.

How It Works

JuicyScore gives banks the ability to evaluate each user who accesses their financial products. The solution expands the internal risk management system and enhances the banking risk prevention model delivering higher informative value. In the end, businesses may develop a low-cost risk-assessment approach that lowers operational costs and improves customer onboarding process

Device and User Authentication

We managed to create a niche-specific scoring model that works for different financial institutions and banks in particular. The idea is to evaluate a set of technical and behavioral parameters to generate the overall attribute value. This value indicates the potential risk of fraud. Businesses get a tool that enhances the decision-making process based on an advanced data vector.

The solution comes with an integrated state-of-the-art device authentication system. When paired with accurate, timely device fingerprinting, it reduces the possibility of fraud. Our technology makes it far more difficult for fraudsters to exploit financial services by utilizing numerous authentication mechanisms.

Assessing Risk Level

We managed to create a niche-specific scoring model that works for different financial institutions and banks in particular. The idea is to evaluate a set of technical and behavioral parameters to generate the overall attribute value. This value indicates the potential risk of fraud. Businesses get a tool that enhances the decision-making process based on an advanced data vector. Book a demo with us to learn more!

FAQs

Why Is Fraud Detection Important in Banking?

Traditional rule-engine fraud monitoring solutions are no longer effective. Fraudsters develop their methodologies. They perform more attacks than ever before, which leads to billions of dollars lost by banks. Besides, banking fraud makes customer onboarding more challenging.

What Are the Red Flags of Fraud in Banking?

The most common signs of banking fraud involve identity thefts, account manipulations, numerous transactions taking place simultaneously, and internal fraud when banking employees team up to overcome internal controls and still funds.

What Data Is Needed for Fraud Detection?

Generally, hackers do not need much for fraud. Banks require only baseline personal data that is easy to steal or even buy on fraudulent marketplaces. Besides, hackers can steal different content needed for biometric ID confirmation (photos or even fingerprints). This is why advanced banking fraud protection is a must.