Data Analytics

How Does High Performance Computing and AI Help Financial Firms?

IT leaders who combine artificial intelligence with high performance computing are discovering its revolutionary potential.

Autumn Whitefield-Madrano

Autumn is an associate editorial director and a contributor to BizTech Magazine. She covers trends and tech in retail, energy & utilities, financial services and nonprofit sectors.

If artificial intelligence (AI) can supercharge existing technological and human-powered capabilities, think of high performance computing (HPC) as a power booster.

HPC enables data processing and complex calculations at extraordinarily high speeds — up to quadrillions of calculations per second, according to NetApp.

Expected to grow at 7.5 percent annually through 2030, HPC’s role in AI continues to emerge, particularly within finance. In fact, 97 percent of financiers in a NVIDIA survey said they will increase spending on AI infrastructure this year.

One reason for this growth is that the more ambitious the AI project, the more HPC-level power a business needs. With its low latency, parallel processing and immense storage capacity, HPC helps a traditional data center become more powerful.

By adding clusters of graphics processing units, financial institutions can use AI to make more evidence-based decisions, improve customer experience, enhance risk management and operate with greater efficiency. Here are some of the ways that HPC can work with AI to help financial firms.

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HPC Increases Data Processing and Analysis

The financial world generates and relies on a tremendous volume of data from various sources, such as business transactions, customer transactions, market data, currencies and more. HPC systems support AI in efficiently processing and analyzing this data. This helps keep financial institutions competitive and secure.

Financial institutions looking to maximize data processing capabilities will need to find efficient paths toward integrating an HPC infrastructure that supports their AI-enabled data analytics vision. A converged system will grant that processing power along with a strong ROI, according to Intel.

HPC Improves Fraud Detection

“In risk and compliance, organizations are using machine learning to analyze vast amounts of data to enhance fraud detection, improve anti-money laundering (AML), and ensure regulatory compliance,” notes the NVIDIA survey. HPC’s power and speed help AI process these transactions faster, identifying fraudulent exchanges in real time. It can even pick up on patterns that skilled analysts might overlook.

Ultra-high-speed fraud detection also helps financial institutions by reducing the number of false positives, which improves customer sentiment. And because machine learning can rapidly analyze vast data sets more quickly than human analysts, HPC-powered AI can even detect new fraud tactics and help analysts stop them from taking hold.

7.5%

The compound annual growth rate for the global high performance computing market between 2023 and 2030

Source: Grand View Research, “High Performance Computing Market Size, Share & Trends Analysis Report,” February 2023

HPC Adds More Precision to Risk Assessments

AI models review whether a loan or deal makes sense. With HPC, these models can be trained rapidly and accurately, assessing risk in real time. Advanced analytics supported by HPC also allows financial firms to spot existing risk factors before they harm business interests.

HPC Supports Data-Based Decision-Making

The speed at which HPC can support decision-making is remarkable. By automating data analysis, AI can identify patterns and extract insights instantly, giving IT leaders the information they need to make evidence-based decisions.

Within the rapid-fire world of financial trading, a millisecond can translate to millions of dollars. HPC systems give AI data analytics tools the power to process information and execute trades with near-zero latency. This helps ensure that financial institutions can seize opportunities the moment they arrive, resulting in more robust portfolios and stronger performance.

HPC Enables More Personalized Customer Insights

Customer insights, personalized recommendations and marketing campaigns stem from information gathered in large data sets. HPC supercharges those data sets by allowing for an even greater volume of data and more complex analytics, which in turn deepens customer engagement and satisfaction.

One highly visible use of AI in the financial industry that can be supported by HPC: natural language processing tools such as chatbots. Incorporating predictive analytics, textual data analysis and speech patterns, natural language processing tools can provide 24/7, personalized service to customers. They may be able to function as ersatz financial advisers in the future, even as legal and regulatory questions around chatbots linger.

HPC Ensures Regulatory Compliance

Artificial intelligence automates the process of identifying, organizing and analyzing data across systems that feeds into compliance reports, and it does so with a low error rate. HPC supports AI in automating these complicated compliance processes, helping ensure that financial institutions are meeting their ethical and legal obligations and proving it during audits and compliance reviews.

In a year when experts are forecasting more aggressive scrutiny, financial firms need these supercharged tools to reduce the number of resources devoted to compliance and lower overhead.

The symbiotic relationship between HPC and AI will continue to revolutionize the financial industry. It may be a technological union, but its effects enrich humans at every point along the financial journey — and there’s only more to come.

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