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Defeating latency is at the heart of the AI, fraud and data challenges at banks

Feb 5, 2020 / Technology

There are many examples in modern business where low latency is critical, but perhaps none of them more so than in banking and financial services. For this industry, the speed with which networks relay communications and execute transactions is directly proportional to profitability. Because time is money, the difference between milliseconds and microseconds can mean the difference between big profits or losses.

Competitive organizations are those well-equipped to mitigate the money-draining effects of latency and able to quickly and accurately respond to the changing needs of their business and customer base.

A recent survey conducted by Hazelcast in collaboration with Intel revealed that there is a significant gulf between the innovators and the followers in financial services when it comes to entering the microsecond arena for application performance. According to the survey, fewer than half of IT decision-makers in financial services measure latency in microseconds.

As new and emerging technologies continue to impact and transform the financial world, organizations must address the ever-present forces of latency. Here are three ways where defeating latency can provide concrete benefits for banks and financial institutions.

Identifying new revenue and service opportunities

Financial services organizations that measure latency in microseconds named artificial intelligence and machine learning as the greatest opportunity to unlock profits at their organization, according to the Hazelcast survey.

But to unlock the potential of AI/ML and other technologies (such as blockchain) impacting the financial services industry, organizations have to be able to operate at speeds and scale previously thought impossible. The growing appetite for supporting AI and other compute-intensive applications requires high-performance computing capabilities to perform real-time analysis and train large datasets at scale – a requirement for innovative applications.

Among IT decision-makers who took part in the survey, 40 percent named identifying new revenue and service opportunities as a top priority for reducing latency, as it eliminates the tradeoff between the AI/ML model’s predictive effectiveness and its performance. In the financial industry, AI/ML without speed is like having a car with an engine, but no wheels. Keeping a firm focus on latency while leveraging new intelligence technologies will maximize profit-creating opportunities during this disruptive era.

Prevention of cybercrimes by fraudulent actors

Fraud has grown to epidemic proportions as our digital lives become increasingly interconnected, dependent and exploitable. Digital and mobile card payments have dramatically increased both transaction volumes and attack vectors for fraudulent activity, taxing payment processors to speed up their ability to take anti-fraud measures.

The compound challenge is driven by the speed at which malicious acts can occur. This necessitates fraud detection algorithms that identify suspicious behaviors not in seconds or even milliseconds, but microseconds. That’s why 39 percent of IT decision-makers in the financial services industry named the prevention of cybercrimes a top priority in their efforts to reduce latency. The faster the payment process, the more fraud detection algorithms that can run in the available window of time – this has the potential to dramatically improve fraud prevention and save companies millions of dollars.

For example, a leading U.S. credit card processor was writing off $1.5 billion a year due to missed fraudulent charges. With only 50 milliseconds to execute its detection algorithms, the processor ran into the transaction rate limit of its legacy database architecture, which reduced the number of detection algorithms that could run. A low-latency, scalable, in-memory data store enabled the payment processor to match account information, check available balances, execute fraud detection and render a decision in near real-time.

Quicker data access to inform business decisions

Another top priority of IT decision-makers in the financial services industry is quicker access to data to inform business decisions. However, roughly a quarter of financial organizations surveyed are not tracking costs incurred due to latency. By taking new approaches to the data-processing value chain, firms can get real-time insights into processes and operations and make smarter decisions, which in turn can lead to improved products and services.

Processing new data at the speed in which it is generated will become the new normal as businesses operate in a completely new time scale. As freshly produced datasets get larger and more diverse, minimizing latency in all layers of the software stack can help organizations meet the new demands of innovative applications. Companies need to look at every process and system to determine how best to eliminate the harmful drag latency puts on business progress.

It’s important for business leaders to understand that the fight to reduce latency is never fully won. Businesses should remain vigilant in revisiting their data-processing architectures to take advantage of powerful new and proven technologies and approaches to lean into the latency-busting challenge. There are millions for the taking in the microseconds.


Kelly Herrell is chief executive officer at Hazelcast