Drawing on the power of artificial intelligence applications and high-performance computing systems, financial services companies are taking their businesses to new heights.

When it comes to adoption of new and emerging digital technologies, financial services institutions (FSIs) have a long track record for leadership. This continues to be the case today as FSIs — including commercial banks, investment firms and insurance companies — are capitalizing on the power of artificial intelligence and high-performance computing to make their businesses smarter, faster and more secure.

In some industries, AI is used only in narrowly defined applications. Not so in financial services. In the financial services sector, companies are embracing the AI opportunity across the broad range of their business operations — from engaging with customers and reducing fraud to maintaining regulatory compliance and automating business processes.

Let’s consider five ways in which FSIs are leveraging the power of HPC-driven AI systems to compete more effectively in a rapidly changing industry.

Customer engagement

FSIs are leaders in using AI-driven systems to pull themselves closer to their customers. For example, in customer-contact interactions, many companies use chatbots and sophisticated voice analytics tools to manage customer interactions. These initiatives capitalize on advances in voice-recognition technologies, data analytics and AI algorithms. Today’s systems can now detect not just the words customers use, but also the tone and sentiment behind the words. These capabilities help FSIs respond more effectively to the needs of customers and, in the process, automate quality-assurance monitoring.

In another advance in customer engagement, FSIs are using intelligent systems to personalize and optimize the marketing of products and services. With AI, for example, FSIs can mine transaction history, social media sentiments and other data sources to anticipate a particular customer’s needs and objectives and to provide tailored recommendations for products and services. They can also use AI to cluster or segment customer behavior in order to tailor their products and services to the requirements of groups with similar needs and interests.

Credit risk assessment

In mortgage and retail banking, FSI are increasingly using AI systems to accelerate credit risk assessment and make better-informed decisions on the credit-worthiness of loan applicants. These capabilities can help FSIs reduce the losses that come with loans that go into default. The research firm McKinsey & Company notes, “With machine learning and other technologies, risk models can become more predictive, which suggests that credit losses may fall by up to 10 percent.” Even better, a McKinsey survey indicates that over half of risk managers expect credit decision times to fall by 25 percent to 50 percent with the power of AI on the backend.[1]

Fraud detection

Highly sophisticated, always-on fraud detection is a requirement for day-to-day business in the financial services world. HPC-driven Al systems are now at the heart of these efforts. For example, AI algorithms are helping banks and payment-processing companies identify unusual and potentially fraudulent transactions as they are taking place — so they can stop those transactions. Similarly, insurance companies are using AI systems to spot suspicious claims by comparing new claims against the patterns and specifics of legitimate claims.

In a real-world example of the power of AI in fraud detection, Mastercard leverages machine-learning algorithms running on HPC systems to process large data sets nearly instantaneously in order to identify and stop fraudulent payment-card transactions. This capability helps Mastercard combat fraud without disrupting or delaying legitimate transactions. This is particularly amazing when you consider the scale of Mastercard’s global operations. The company processes 165 million transactions per hour, using machine-learning algorithms and applying 1.9 million rules to examine each transaction — and it all happens in a matter of milliseconds.[2]

Cyber security

On the cyber security front, the networks and systems of FSIs face constant threats from external hackers, thieves and fraudsters, as well as unreliable insiders. They now ward off these threats with a wide range of tools for protecting the security of data and systems. One of these tools is AI, which is used to detect suspicious behavior and other anomalies in real time. Even better, some FSIs are now using machine learning to enable threat-detection systems to continually learn from their experiences and get better over time.

Regulatory compliance

A tidal wave of new national and international regulations has washed over the financial services industry in recent years. For many FSIs, achieving compliance with all the new and existing regulations is no easy task, especially if they rely heavily on manual processes. New AI-driven processes offer a better way forward. With AI systems, FSI can automate and streamline the process of identifying, collating and analyzing data from disparate systems to meet current compliance requirements — and to reduce the chances of human errors that might lead to costly sanctions for non-compliance.

These are just some of the top use cases for AI in the financial services industry.  Others include high-frequency trading, portfolio optimization, risk management and business process automation — the list of AI applications in the industry goes on and on.

Key takeaways

Artificial intelligence is a powerful tool that has applications across a broad range of use cases in the financial services industry. And FSIs are seizing the day. They are embracing AI across the spectrum of their operations — from customer engagement and credit risk assessment to managing compliance and securing networks and systems. Along the way, AI is helping organizations improve customer service, reduce risk, maintain compliance and complete more effectively in a fast-moving industry.

To learn more

For a closer look at Mastercard’s successes with AI, read the Dell EMC white paper “Fighting fraud the smart way — with data analytics and artificial intelligence.” And to explore the technologies for HPC and AI, visit dellemc.com/hpc and dellemc.com/ai.

 

The Convergence of HPC, Analytics and AI High-performance computing, data analytics and artificial intelligence no longer live in separate domains. These complementary technologies are rapidly converging as organizations work to gain greater value from the data they capture and store. In this year-long series, we explore this ongoing convergence, and what it means for today’s IT organizations.

[1] McKinsey & Company, “The future of risk management in the digital era,” December 2017.

[2] Dell EMC white paper, “Fighting fraud the smart way — with data analytics and artificial intelligence,” December 2018.