In this second article of our series featuring insights on data access, connectivity and integration for the financial services industry, author Matt Gillespie delves into the critical relationship between data access, connectivity and integration in the field of fraud prevention. Gillespie is a technology writer, research analyst and journalist who writes about cloud, AI, cyber security, software-defined infrastructure and data integration, among other topics.

Fraud costs financial service firms billions of dollars per year, and data-driven prevention measures are the key to reducing those losses. Analysts in the financial services industry have more sophisticated tools than ever to detect attempted fraud, and always-on, high-performance access to data is a prerequisite for their success.

Quite simply, fraud-prevention analytics transform historical and real-time data into insights. Acting on those insights lets financial institutions interfere with potentially fraudulent actions before they create financial damage.

Another way to conceive of that workflow is to say that robust data access is directly correlated to financial benefit. Thus, the data connectors (also known as “drivers”) that enable applications and data sources to communicate effectively have become business-critical.

Rich Data is Critical to Modeling Customer Behavior

Machine-learning and artificial-intelligence algorithms can observe thousands of simultaneous transactions as they happen, all day and all night, and combine that information with historical data to form a picture of what constitutes “normal” customer behaviors. Watching for anomalies in those behaviors can enable fraud-prevention software to provide automated alerts and responses to possible criminal activity.

For example, an unusual credit card purchase could be the basis for blocking the transaction or requiring two-factor authentication for it to continue. These detections and responses must occur within seconds, with no human intervention. As they meet those challenges, solution architects do well to remember the following:

  • AI is not a silver bullet. Although these algorithms are far more adept than humans at sorting through massive real-time data streams, prediction has its limits.
  • False positives have consequences. All that glitters is not fraud, and mistakenly applying countermeasures can frustrate end customers and damage the brand.
  • More data makes AI more capable. Like all machine-learning applications, fraud prevention becomes more accurate with more dependable, higher-performance access to data.

These factors make data connectivity a core architectural consideration for successful fraud prevention. Partnering with Simba can add to the capability and accuracy of your anti-fraud measures by improving your ability to satisfy new usage models and connect to new data sources.

Missed the first post in the series? — Learn about data access for Compliance & Audit

Connecting Anti-Fraud Tools to Data Sources Can Get Complicated

As a fraud-prevention practice matures, it tends to grow and depend on a broadening array of data sources. Establishing and maintaining those data connections can create technical complexity that stretches the capabilities of in-house development teams.

As connectivity becomes more complex, it can quickly become a drag on the agility of anti-fraud measures as they adapt to change, with teams struggling to drive value from both stored and streaming data sources:

  • Historical data tells you what to expect. Using stored data from many sources, algorithms develop hypotheses about what customers do in the course of normal, legitimate transactions. These can run the gamut from the general behaviors of all customers to specific expectations for customer types or even individuals in certain situations.
  • Real-time data tells you what’s happening, as it happens. Gathering and ingesting customer data as it emerges captures key indicators and enables streaming analytics that can offer a curated view of real-time insights about customer intents and behaviors, including the potential for preventing fraudulent activity before it occurs.

Fraud-prevention measures use that combination of streaming and historical data to rate transactions in terms of how likely they are to be nefarious, so that systems can instantly respond with the most informed understanding possible.

The technical complexity of connecting to all those data sources is daunting. And providing the dependability and through put that fraud-prevention algorithms rely on makes it even harder. All that means that you need to put more attention on data access, connectivity and integration than you might think.

Simba specializes in building and maintaining the data connectors (also known as drivers) that ensure that fraud-prevention systems have transparent, high-quality access to all of the data they need from all these historic and streaming data sources.

Put Data Where You Need It:
Off-the-Shelf Connectors Might Not Cut it

Simba offers leadership expertise in all aspects of data connectors and their implementation, from solving individual connectivity challenges to creating an overall strategic approach for making data available wherever it is needed, throughout the enterprise.

By their nature, fraud-prevention tools benefit from being able to connect to a wide variety of data sources, from the most common enterprise platforms to those that are more niche or obscure. Simba provides a flexible range of approaches to meet those needs, including the following:

  • Off-the-shelf data connectors support the majority of cases. For most combinations of applications and data sources, Simba offers world-class, commercially supported, pre-built data connectors.
  • Custom connectors can meet unique needs. Simba also builds custom drivers for cases such as niche data sources or unusual connectivity requirements.
  • We also improve “build your own” models. Organizations that build their own drivers can use the same SDK that Simba’s engineering team uses to develop the company’s commercial drivers.

Simba backs all of its drivers and related tools with industry-leading expertise and enterprise-class support.

Conclusion

In today’s data-driven world, data connectors that enable the vital data flow between data sources and applications can no longer be disregarded as a commodity detail or an afterthought. They have become a business-critical component of solutions such as fraud detection and prevention. Partnering with Simba puts your data where it’s needed to head off fraud before it happens.

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