Detecting and Preventing Fintech Fraud with the Power of AI

The Fintech industry evolves with the evolution of the digital age and big data. Fraud prevention became one of the major issues for the entire sector. On the one hand, customers benefit from more accessibility and financial flexibility. On the other hand, it becomes harder for Fintech companies to identify fraud.

Fraudulent methods are experiencing consistent innovations with online businesses becoming the primary objective for hackers. Account takeovers, social engineering, synthetic identity thefts and other approaches put companies at ever-growing threat. To keep both customers and organizations protected, it is important to work out effective Fintech fraud prevention strategies.

Fintech and Fraud

The researches reveal tremendous losses resulting from Fintech frauds. Malicious activities make businesses lose around $51 million per year. However, fraud risks exceed just monetary problems. Growing clients’ friction, lost trust and loyalty are among major issues service providers have to face today.

Businesses go online to rely on enhanced digital experience and micro services. Meanwhile, fraudsters develop new methodologies to reveal weak spots and exploit companies’ digital vulnerabilities. To oppose the fraud risks, enterprises need to adopt innovative fraud prevention solutions. And the first step is to understand how major types of fraud work in the online financial ecosystem:

• Social engineering. Generally, it happens when a fraudster gains access to the victim’s account to complete transactions or transfer funds. This particular type of attack is the toughest one to recover.
• Synthetic Identity Fraud. It represents a combination of stolen data (like social security number) with fake information (date of birth or name). The data is used to create a new synthetic user identity to verify transactions or checkout.
• Account Takeover. The idea is to steal financial account information via password/email change or surfing. Sometimes, fraudsters apply bots able to try thousands of combinations to change user’s [password or email in seconds.
• Presentation attack. A hacker uses physical data to verify an underlying operation via fake photos, fingerprints, and other types of biometric data. Let’s say, an application relies on facial recognition to confirm transactions. A fraudster applies deep fake innovations or stolen photos to link a fake identity with a real user.

Any of the above-mentioned threats can have a great impact on both Fintech companies and their clients. Without having effective fraud prevention tools, businesses may lose not only money but also trust, loyalty, and customers.

The Impact of Fintech Fraud

Fintech fraud can damage any company despite the size. Of course, the impact varies. For instance, smaller companies are more prone to suffer from lost revenues as a result of fraudulent activities. The same applies to mid-size firms. Generally, they lose around 2.2% of their revenue. However, it does not mean large service providers can feel safe.

Financial losses are not the major issue. Fraudsters pose huge reputational risks, which can result in lost trust and customers’ loyalty. What’s more, we should consider potential legal and recovering costs, penalties and other challenges that make business operation more complex and turbulent. That might be a problem for businesses of any size.

Customers’ Losses

One being compromised, a client will hardly ever use the same service again. Some of the fraud types are extremely hard to recover, especially when it comes to stolen financial data or credentials. Getting one’s money back is a question of time and effort.

So, users are mainly looking for safer ways to take advantage of financial services. They need to be 100% sure their information is secure. Otherwise, they will look for a better place to benefit from Fintech product providers. This might be an issue, as analytics predict the identity thefts to see the record growth in the near future.

Trust Issues

Customers’ trust and loyalty cost more than any financial loss. Reputational risks are always to the detriment of stable revenue and the ability to scale business. Without effective fraud prevention means, smaller companies are often treated like scams – the bad stamp that is pretty hard to recover from. Trust defines the financial service success. No trust, no customers, no revenues. It’s that simple.

JuicyScore Fintech Protection Solution

The JuicyScore solution is a comprehensive toolkit for preventing Fintech fraud. Developed to assist companies in taking on fraudsters head-on, the software exploits AI and ML-based technologies to ensure innovative protection methods on different industry levels.

Our anti-fraud solution for the Fintech sector contains:

• Systems for Identifying Different Fraud Types. Based on a range of behavioral data attributes, the software builds an accurate end-user linkage by utilizing 30+ distinct device authentication algorithms.
• Mechanisms to Reduce Fraud Risk. Potential threats are identified on autopilot. The system uses 214 configurations, qualities, and device-assisted markers to technical metrics. They cover the Internet connection, network infrastructure quality, and other aspects thoroughly examined and assessed.

Advanced technologies are the core of our high-end data vector.

AI-Powered Fraud Detection

With the evolution of big data, neobanking, and digital currencies, the majority of financial services have gone online reserving more blind spots for fraudsters. AI-based fraud-detection tools help accelerate the process of evaluating new customers, processing massive volumes of data in real-time, and lessening the chances of human error.

Relying on Artificial Intelligence, our tools are trained to recognize different technological and behavioral trends and to conduct technical analysis and evaluate the risk of fraud. As part of a specific pattern, the system monitors thousands of different characteristics.

Artificial intelligence employs a variety of behavioral analysis techniques to identify anomalies, suspicious activity, and other abnormalities that counteract the user's normal behavior.

Leverage Broad Vector of Data

We consequently develop a customizable evaluation model based on the advanced JuicyScore data vector. Designed for improving the decision-making process, it assists Fintech companies in obtaining sufficient information to determine a client's account credibility and transactions safety.

The software comes as a digital safety adviser. It generates values based on scoring models as a part of the bigger anti-fraud prevention toolkit that involves instruments to detect device manipulation and randomization. The system automatically conducts thorough tracking with the use of authentication instruments. They are able to recognize fraudulent attempts of multi-accounting, device virtualization, data randomization, and other fraudulent methodologies.

Key Features

Our mission is to reduce the risk of presentation attacks, account takeovers, and other types of fraud by performing real-time data validation. We utilize instruments to safeguard customers’ data via multi-factor authentication and enhanced encryption.

Our solution helps to mitigate fraud risks by utilizing multiple data sources. It generates essential technical and behavioral parameters needed to create a detailed digital profile with potential risks automatically evaluated. JuicyScore needs seconds to predict a potentially fraudulent transaction. It generates alerts and “red flags” whenever anomaly is spotted to ensure enhanced decision-making for Fintech companies.

Device Fingerprinting Feature

The system processes a variety of primary and secondary Fintech fraud risk criteria. It monitors gadget properties, which is the principle behind our solution. To accurately perform device fingerprinting, JuicyScore data vector identifies the type of carrier (tablet, desktop, laptop, or mobile), screen size, display quality, RAM, and other essential characteristics.

The system consequently reveals abnormalities or mismatches. These could indicate device cloning or randomization, remote access, various routing approaches, and more.

Fraud Risk Behavioral Analysis

The system examines different parameters by combining a variety of aggregated variables. These consist of the quantity of apps utilized on the same device in a certain time frame, duplicated or randomly chosen devices, analyzed online sessions, dwell/flight times, the average typing or content reading speeds, and other crucial behavioral metrics.

The data vector comes with a solid background made up of many integrated markers. Together, they serve as a single tool to assist Fintech businesses in identifying potentially fraudulent consumer segments.

How It Works

By utilizing filters, the system divides high-risk flows into niche-specific groups based on device attributes (OS, browser version, Internet connection quality, behavioral aspects, etc.).

JuicyScore gives companies the ability to evaluate each user who tries to complete a specific transaction. Eventually, organizations come up with an enhanced financial risk model with high informative value. In the end, businesses may develop a low-cost risk-assessment approach that lowers operational costs, increases clients’ inflow and develops trust.

Users' Accounts Protection

When paired with accurate, timely device fingerprinting, our advanced toolkit reduces the risk of Fintech fraud and keeps user’s accounts well-protected. Thanks to various authentication mechanism, fraudsters will find it far more complex to exploit financial services or compromise sensitive data.

With MFA, Fintech organizations can build a more powerful defense line. It ensures their clients’ data is safe from any type of digital threat.

Transaction Monitoring

The system can spot abnormal operations and send alerts whenever anomalies take place. For instance, it is common for fraudsters to perform multiple transactions at a time, which is a signof an identity theft. In this case, our software analyzes thousands of technical and behavioral factors to either confirm a fraud or inform of its safety.

What’s more, the toolkit can be used to sort our generated data by segments. With flow segmentation, it is possible to divide information into customizable groups and categories.

The software tracks and detects different device manipulation methods, assesses the network and application quality, identifies potentially fraudulent sessions. In simpler words, businesses can work out their own fraud prevention model with our advanced data vector under the hood.

Get Started with JuicyScore Today

We guarantee seamless integration in just a few steps. Our solution is mobile and desktop-compatible. To start protecting your business and customers, you only need to have the JavaScript or SDK installed on the app.
Our team guarantees full-scale support at any level. Book a demo and try our high-end Fintech anti-fraud solution!

FAQs

What Is the Fraud Rate for Fintech?

The latest stats show that Fintech companies lose around 2.2% of their annual revenue. For smaller and mid-size businesses, it accounts for more than $200,000 per year. Besides, businesses should take into account extra costs involving regulatory penalties, recovering expenses, and lost trust.

How to Detect Fraud in Fintech?

Transaction screening and monitoring along with secure onboarding are the prior ways to detect and prevent Fintech fraud. However, fraudsters gradually develop their approaches like synthetic identities, account takeovers, presentation frauds and more. Some of them are very hard to detect without advanced anti-fraud toolkit.

How Can Fintech Fraud Be Prevented?

Multi-factor authentication, device fingerprinting, customer account protection are among the most effective ways to prevent Fintech fraud. A blend of several features will enhance safety for both clients and Fintech companies.