Banks Are Cashing In on Embedded AI

As artificial intelligence becomes more and more commonplace, banks are investing more heavily in AI-enabled systems. According to a recent IDC report, banks worldwide are expected to spend an additional USD31 billion on AI embedded in existing systems by 2025.

Embedded AI is becoming increasingly popular due to its ability to automate tasks and processes and provide insights and analytics that can help businesses make more informed decisions. The embedded AI sector is expected to reach USD38.87 billion globally at a compound annual growth rate (CAGR) of 5.4% within 2021-2026.

“In the process of coming up with digital products and services, new channels, and new payment methods, businesses might be overestimating the adequacy of their current defense mechanisms against fraud,” said Michael Araneta, associate vice president at IDC Financial Insights.

“What worked well before simply would not be enough now in the more digital world of business. There needs to be a constant upgrade of fraud management capabilities,” he added.

The rise of embedded AI

AI is no longer just a “nice to have” — it’s becoming a “must-have” for banks as they seek to remain competitive in an ever-changing landscape. This, coupled with the rising demand for embedded systems, is resulting in a new “embedded AI” sector, which is expected to see significant growth in the coming years.

Yash Chawla, assistant professor at Wroclaw Tech, defined embedded AI “as the capability of embedded systems or resource-constrained devices that are usually isolated to carry out tasks that require human intellectual capacity." With the help of AI algorithms and models, these systems can function in isolation without needing external intervention.

Benefits of embedded AI

Chawla says that many benefits come with implementing embedded AI into existing systems. These benefits include:

• Increased functionality and responsiveness
• Reduced transfer of training data
• Increased privacy, security, and resilience

"Embedded AI emerges and finds applications in consumer electronics, autonomous vehicles, and industrial sectors. It brings several benefits to businesses and users, such as low latency, optimization in energy consumption, and autonomy," he added.

When it comes to the cloud, Chawla said that businesses could benefit from embedded AI by reducing the amount of data that needs to be transferred to the cloud and the number of times AI models need to be retrained. This can help reduce costs significantly.

Jim Marous of The Financial Brand added that embedded AI could help businesses experiment with AI and quickly build pilots for unique business challenges.

Banks and embedded AI

So far, banks have been primarily focused on using AI for customer-facing applications such as chatbots and digital assistants. However, there is a growing realization that AI can be used for much more than just customer service.

Marous added that banks lagged in their development of AI compared to other industries. However, he believed that if the banking industry overcame AI's challenges, the banks could leapfrog the competition. This is perhaps the biggest advantage, according to Marous, who also said that AI was imperative to support risk and fraud analysis and increased productivity.

In 2021, McKinsey released a report that found that AI is quickly becoming embedded in financial institutions. The report, which surveyed over 200 senior executives across the globe, found that AI is most commonly used for robotic process automation (36%), virtual assistants or conversational interfaces (32%), and machine learning techniques (25%) to detect fraud and support underwriting and risk management.

"Today, the world has become far more data-driven with machine learning-based analysis providing accurate, self-updating models with outputs embedded directly into core business software. This method of AI delivery minimizes the time it takes from running the analysis to delivering meaningful insights. These insights are actionable because of their placement directly into the hands of people that need it most, so they can work more expediently, making workflows more efficient," said John Menhinick, senior director for product management at Oracle.

Embedded AI can unlock even more value for banks

While AI has already started to transform the banking sector, there is still much untapped potential. Banks that want to stay ahead of the curve must start embedding AI into their existing systems. This will not only help them become more efficient and competitive, but it will also help them tap into new revenue streams.

For example, some banks are working with embedded AI providers to offer more relevant products and services, reduce churn, and build customer loyalty. Others rely on embedded AI to self-monitor and automatically prevent or flag fraudulent behavior in real-time.

"By pushing AI beyond the cloud and onto devices, it becomes more democratized and better able to deal with the specific functions the device was designed for," analyst Arthur Cole at Venture Beat said.

Getting started with embedded AI

Banks that want to use embedded AI must consider a few things first. According to a recent report by Gartner, four actions include:

• Finding AI-specific talent: This can be challenging, as many AI experts are already working in other industries. Banks will need to find ways to attract and retain AI talent.
• Incorporating software with embedded AI capabilities: AI-enabled software must integrate seamlessly with existing systems. This can be challenging, but it's crucial for a successful implementation.
• Experimenting broadly with pilots: Banks need to experiment with different applications of AI to find the ones that offer the most value for their specific business.
• Designating an analytical AI implementation leader: This person will oversee the AI implementation and ensure that it meets the bank's goals.