Payment fraud analytics — using data as a distinct business advantage

For online businesses, one of the most valuable insights that good data can provide is how to prevent fraud and otherwise mitigate risk. After all, fraud has direct costs, or at least contributes to higher costs. There are also the fees, interest, replacement and redistribution costs to consider. Card-not-present (CNP) fraud, which includes online transactions, is expected to cost about $130 billion in revenue on fraudulent transactions between 2019 and 2023.

Fraud also contributes to other negatives. There’s the risk of reputational damage for companies that become associated with fraud schemes. There are frustrations and delays for all legitimate parties who get caught up in investigations. Hard-earned trust becomes increasingly fragile, as doubt tries to weave its way into every relationship.

How then can fraudulent patterns be detected in the torrents of data that online businesses collect? How can fraud be spotted more quickly, protecting revenue, reputation and trust?

Gathering data at scale

One optimization truism is “if you don’t measure it, you can’t improve it.” If data doesn’t get collected, it’s difficult (or impossible) to go back and recreate the missing information. Thus, it’s imperative to have proper data collection systems in place prior to any analysis.

From account verification processes to transaction monitoring systems, from checking mobile data to threshold and suspicious activity reports, there are an abundance of RegTech solutions that gather disparate data sources.

Data warehouse projects can streamline all the data collection and make it more manageable. An effective data warehouse operation is core to the success of large-scale data businesses. It’s been said many times before: data is the lifeblood of business. Data provides the numbers that quantify progress and success, demonstrates trends and patterns, and is parsed, filtered and segmented to provide insight for analysis. With the speed and complexity of modern-day organizations, the effective use of data is what keeps business on track.

Unfortunately, speed and complexity also come into play when dealing with how to acquire, manage and analyze data. There is simply too much data being created, making it that much more difficult to gather actionable insights.

With an effective data warehouse strategy and operation, all the different data sources and databases integrate into one database with one data model. There’s a centralized view of all the data, providing more consistent data and better data quality. Database performance is improved. Smart data warehousing allows restructuring of the data to align with business analytics requirements, adds value to business applications and enables better decision queries.

Not magic, data science

Creating, operating and optimizing a data warehouse is the realm of data scientists. It’s not only about running the system; it’s about analyzing and interpreting the results. Harvard Business Review referred to the role of data scientist as “the sexiest job of the 21st century.” It’s no wonder, as these talented individuals need to have skills in a variety of fields: analyzing statistics, programming, understanding business requirements, communicating and interacting with numerous stakeholders and, most interesting of all, spotting patterns.

It’s the ability to look at massive data sets and gather unique insights that provides the most value to organizations. Spotting anomalies or trends can provide new business opportunities, or in the case of fraud prevention, discover questionable transactions.

Marketplace of data

As Trulioo offers a marketplace of identity data and services, data analytics is fundamental to our business. With our network of over 400 disparate data sources from across the globe and providing services to a wide range of clients, including Fortune 500 companies, effective data management is key to what we do. All of our data expertise adds significant value to all our clients.

Case in point: the Trulioo analytics team recently pointed out a series of fraudulent transaction attempts to a large eCommerce client. They were quite happy that we sent them the information and they told us that the GlobalGateway data analytics are very helpful for fraud detection, and that Trulioo is often faster at identifying issues than the client’s own team.

For us, that’s music to the ears. Not only is it validation for all the efforts we’ve made to create an outstanding data marketplace, but it’s helping clients stop fraudsters and protect their good name.

Effective data management and smart data science is key to modern business success. Payment fraud analytics is one example, but there are many others. Is your data strategy ready for the 2020s? As Peter Sondergaard, senior vice president at Gartner, points out, “information is the oil of the 21st century, and analytics is the combustion engine.”