Technological Thoughts by Jerome Kehrli

(Article initially published on NetGuardians' blog)

NetGuardians overcomes the problems of analyzing billions of pieces of data in real time with a unique combination of technologies to offer unbeatable fraud detection and efficient transaction monitoring without undermining the customer experience or the operational efficiency and security in an enterprise-ready solution.

When it comes to data analytics, the more data the better, right? Not so fast. That’s only true if you can crunch that data in a timely and cost-effective way.

This is the problem facing banks looking to Big Data technology to help them spot and stop fraudulent and/or non-compliant transactions. With a window of no more than a hundredth of a millisecond to assess a transaction and assign a risk score, banks need accurate and robust real-time analytics delivered at an affordable price. Furthermore, they need a scalable system that can score not one but many thousands of transactions within a few seconds and grow with the bank as the industry moves to real-time processing.

AML transaction monitoring might be simple on paper but making it effective and ensuring it doesn’t become a drag on operations has been a big ask. Using artificial intelligence to post-process and analyze alerts as they are thrown up is a game-changing paradigm, delivering a significant reduction in the operational cost of analyzing those alerts. But accurate fraud risk scoring is a much harder game. Some fraud mitigation solutions based on rules engines focus on what the fraudsters do, which entails an endless game of cat and mouse, staying up to date with their latest scams. By definition, this leaves the bank at least one step behind.

At NetGuardians, rather than try to keep up with the fraudsters, we focus on what we know and what changes very little – customers’ behavior and that of bank staff. By learning “normal” behavior, such as typical time of transaction, size, beneficiary, location, device, trades, etc., for each customer and internal user, and comparing each new transaction or activity against those of the past, we can give every transaction a risk score.

Billions of pieces of data

To do this effectively means taking into account thousands of pieces of information every time a customer makes a transaction. Multiply that by the number of customers a bank has on its books, and it quickly gets to billions.

Such high volumes would overwhelm most platforms, slowing the analytics to an unacceptable speed for the demands of real-time banking. At NetGuardians, we have solved this by using a combination of technologies that allows us to regularly batch process all the data for super-accurate models and supplement these batch models in real time by checking and adding smaller data sets as they arrive. This allows our software to accurately assess huge volumes of transactions in real-time.

The technologies we use are:

• Apache Kafka
• Elasticsearch
• Apache Mesos
• Apache Spark

All are open-source and run on our proprietary Lambda architecture-driven platform. Together, they make up a powerful and affordable solution for analyzing every transaction accurately in real time. In fact, our platform catches up to 99% of fraud, with 85 percent fewer false alerts, cutting investigation time by 95 percent compared with alternative rule-based solutions.

While this is key, it’s not the best bit.

At NetGuardians, we help our customers reap the benefits of cutting-edge and state-of-the-art open-source technologies without them suffering any of the drawbacks. We integrate these technologies, fine-tune and secure them and, critically, we implement enterprise-grade requirements on top. This means banks can use our solution out of the box.

Enterprise-Ready Big Data Platform

NetGuardians combines all the appropriate technologies in a way to make them work together 100 percent of the time, perfectly fine-tuned and secure, providing a bank everything it requires for an enterprise environment. This includes high availability, data and communication encryption, disaster recovery processes, state-of-the-art authorization, identification and authentication frameworks, single sign on, backup and restore procedures and much more. In this way, banks using our software enjoy the benefits of open source – easy integration and further development/fine-tuning – with the security and resilience of proprietary software.

With NetGuardians, banking institutions get the best of both worlds. But the cherry on the cake is that our banks don’t have to do anything. The NetGuardians platform takes care of everything and operates itself automatically, benefitting from strong NoSQL and DevOps genes. And that is unique to us.

Should it want to, though, a bank can create its own analytics on top of the open-source components on which the NetGuardians’ platform is built for its own use cases. A bank may want to use our version of Kafka for its own data-streaming use cases, for example, or it can open our 360 vision of the customer and user activities in ElasticSearch and expose that data through a secured API to in-house, third party software. This allows it to use the data for whatever it wants or needs to do - perhaps AML use cases or enriching the CRM application with NetGuardians’ data about customers.

The future of finance is real-time payments

Typically, many banks access the anonymized data we collect and store on our platform as a financial crime data lake to enrich their own customer 360 views in front office applications with risk indicators and a consolidated view of customers’ activities on their account. This is important because real time payments are growing fast. In 2020, 54 percent of consumers had used real-time payment app PayPal https://www.paymentsjournal.com/real-time-payments-everything-you-need-to-know/. Similar apps such as Venmo and Zelle are also growing fast – with the latter claiming 13 percent of consumers using its app in 2020, up from 1 percent in 2017.

While retail payments are important, it’s in business that the big volumes lie and in one survey 80 percent of businesses said they wanted real time banking. Already this is translating into action - in the US, 2020 saw a fivefold increase year on year in financial institutions implementing real-time payments.

Such huge growth means banks, big and small, will need affordable fraud detection in real time that can cope with these volumes. For the big banks, the solution will need to scale fast; for the smaller ones, they need a platform that can deliver accurate real-time risk scoring with smaller data sets. NetGuardians, with its unique combination of proprietary and open-source technologies, satisfies both. That is why banks worldwide – from Tier 1 to credit unions and co-ops – are turning to NetGuardians fraud-mitigation software to keep their customers’ cash safe.

(Article initially published on NetGuardians' blog)