By: Kevin McWey, Chief Revenue Officer, DataVisor
Fintechs are facing new challenges as fraud grows more pervasive and sophisticated, with each fintech losing an average of $51 million each year to fraud. To protect themselves and their customers, fintechs must approach fraud prevention from every angle. One key component of a comprehensive strategy is to leverage data from fraud consortiums. These collaborative networks allow fintechs to share fraud-related data and insights, giving them a more expansive view of emerging fraud.
However, fraudsters are also forming their own networks, or fraud rings, to share data and strengthen their attacks. By participating in fraud consortiums, fintechs can collaborate to help level the playing field. Traditionally, fraud consortiums were exclusive to large banks, which put fintechs at a disadvantage. But today, fintechs have access to a wide variety of fraud consortiums, which presents both opportunities and challenges. Fintechs must be aware of these limitations in order to best leverage consortium data in the fight against fraud.
Understanding the limitations of fraud consortiums
Data sharing is important, and fraud consortiums offer many valuable benefits to fintechs, but they are not a silver bullet solution. Challenges arise when fintechs subscribe to many different consortiums but aren’t equipped to orchestrate all the data. Because there is no one-size-fits-all fraud consortium, and there are many different types of scams and attacks, many fintechs subscribe to a variety of consortiums, sometimes receiving 30 or 40 different data signals. This contributes to three key challenges:
- Data relevance concerns: Not all data shared through consortiums will be relevant to a fintech’s specific use cases. Fintechs may also encounter messy, inconsistent, or irrelevant data, which can introduce biases or even generate false positives if applied incorrectly. At the end of the day, each fintech has a very specific product, customer segment, and market in which they operate. They need to be careful about what data they are using as comparison points.
- Overwhelming volumes of data: Although more data can lead to better fraud detection, it becomes problematic for fintechs that lack the resources or specialized teams to sift through and analyze it. The challenge lies in filtering out irrelevant information, identifying actionable insights and thoroughly testing the data to ensure that it is applied correctly. Many fintechs simply aren’t equipped for this and end up inundated with data that they can’t put to good use.
- Cost and budget challenges: It’s impossible to find a single consortium that addresses every type of fraud, but the cost of subscribing to many different consortiums can add up quickly. And that’s before factoring in the additional time and resources required to analyze and test the data if the fintech is not properly equipped with robust data orchestration solutions.
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Tips for leveraging data consortiums effectively
Despite these challenges, fraud consortiums are an important fraud prevention tool. With the right approach, fintechs can translate vast amounts of data into actionable insights while maximizing their budget and minimizing the strain on their resources. The following strategies can help fintechs make the most of fraud consortiums:
1. Data relevance: Get the right type of data
As a starting point, fintechs should ensure that the consortiums they subscribe to include like-minded companies so that the data will be relevant to their specific use cases. The best consortiums will use pre-configured fraud signals that have been tested and proven effective within a specific domain, like real-time payments, for example.
Industry collaboration and standardization efforts should also include integration with industry-standard tools, such as SMS verification, and take an “ecosystem” approach to fraud prevention, allowing for seamless integration of multiple data sources and verification methods.
It’s also essential to have visibility into and validation of the source of truth and the methodology used to label various types of fraud and risk data to avoid ingesting bad data or assumptions into models. This includes verifying that sample data sets are actually representative of production data.
Fintechs can achieve these verifications by employing advanced technology that automates the validation of data sources, methodologies, and sample representativeness in fraud detection.
AI-powered fraud detection supports data integrity by using automated data quality checks to identify anomalies and inconsistencies, as well as automated solutions for validating fraud labeling methodologies. A generative AI solution can also automate rule refinement and suggest new rules, while unsupervised machine learning tools detect new and unknown fraud patterns without relying on historical labels.
But these tools are only as good as their last update. Continuous monitoring and improvement are absolutely imperative. Data orchestration platforms also facilitate ongoing validation through automated feedback loops, real-time monitoring of fraud trends and patterns and AI-driven rule suggestions for false positive reduction.
2. Managing volume: Adopt a holistic approach to data orchestration
Fraudsters are experts at finding gaps in fraud prevention methods, especially when there are vulnerabilities due to siloed data or a lack of real-time detection capabilities. These vulnerabilities leave fintechs susceptible to attacks, underscoring the need for effective data orchestration. This is especially crucial in the context of fraud consortiums.
As discussed earlier, there is no one-size-fits-all fraud consortium, which means fintechs will always require a variety of signals. Not to mention, new types of fraud are constantly emerging, which means additional signals are regularly being introduced.
With robust data orchestration capabilities, fintechs can work smarter, not harder. But they must ensure their data orchestration strategy is ticking a few important boxes. First, they need to be able to process and aggregate large volumes of data from a diverse range of signals, ensuring they are looking at the entire customer life cycle. This needs to happen in real-time, and the data must be analyzed quickly so precise decisions can be made within milliseconds.
To manage the huge volumes of data, real-time processing capabilities are required. Fintechs should look for solutions that handle a large volume of data analysis with the ability to scale.
Machine learning further enables this data analysis by adding the ability to adapt on the fly and derive human consumable actions from large amounts of data. By looking at historical or real-time data streams, the technology can pull out relevant insights. That means quicker responses to new trends and can help fraud prevention teams determine when to loosen or tighten controls for certain segments of risk.
The best data orchestration capabilities also enable fintechs to customize rules according to risk appetite. Ideally, they will have different strategies for different customer profiles and can update those rules when needed. The ability to create and tune rules quickly is a significant advantage in the fight against fraud.
3. Without the right technology, more data isn’t always better: How to control costs, maximize efficiency, and drive results
While having access to multiple data sources is crucial, fintechs need to be cautious—more data doesn’t always translate to better outcomes unless you have the right tools, technology, and resources to effectively analyze and process it.
To avoid wasting resources or missing opportunities, an investment in fraud consortium data must be supported by the necessary technology and team members to maximize the value of the data. There should be a foundational process in place with robust data orchestration capabilities to effectively test and utilize the data. This will save time, money, and generate far better detection results.
In addition, the right tools will empower fraud prevention teams to make more informed decisions about which fraud consortium signals to invest in moving forward. Ultimately, the right data orchestration technology ensures your fraud prevention budget works smarter, not harder.
Fraud consortiums are a powerful tool for fintechs in their fight against fraud, but they are not a standalone solution. By understanding the limitations of fraud consortiums and leveraging strategies like robust data orchestration and machine learning, fintechs can bolster their defenses and contribute to a more secure financial ecosystem.
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