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These Banks are Betting Big on AI

February 14, 2024

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Financial sector leaders like JPMorgan are investing in AI and ML. What are the takeaways for other banks and credit unions looking to drive growth?

The total global spend on AI (artificial intelligence) by the banking sector in 2023 was a whopping $20.6 billion, the highest across industries that year. The buzz around AI-driven innovation has increased significantly over the past few years. With promises of dramatic improvements in efficiency and huge cost savings, AI has become the most sought-after growth driver across industries. Banks of all shapes and sizes are investing in AI to reap the benefits of automation, analytics, forecasting, and personalization. Here’s a look at the big banks that have embraced this technology with open arms and mammoth investments.

The banking sector could harvest 9% to 15% higher profit by successfully applying GenAI to processes and operations.

JPMorgan Chase

The world’s largest bank by market capitalization also leads the list of AI investors. JPMorgan topped Evident AI’s index for the second year in a row in innovation and transparency. With a $12 billion annual tech investment, the world leader has become the first major bank to roll out a virtual assistant for corporate clients.

According to a story published by the bank, if a customer authorizes multiple wires in a given period, the virtual assistant could say: “Looks like you have sent 100 U.S. dollar wires to Singapore. Do you know you can send a foreign exchange ACH payment instead? Click here to sign up.”

The AI-powered money movement assistant can guide users to opt for the most suitable ways of transferring funds. It applies to routine payroll, multi-million-dollar deals, as well as M&As (mergers and acquisitions). The bank leverages AI to achieve consistent customer experiences across channels. It is also equipped to use NLP and answer questions on demand. Further, ML has been integrated to observe customer behaviors and make insightful recommendations to make their lives easier. With a massive team of experts at work to profitably and nimbly implement novel technologies like blockchain, big data, and cyber security at scale, the bank aims to compete with top-tier tech giants both for consumer attention and top talent. The leadership carries a vision of gradually applying AI across all processes and operations.

Capital One Financial

The core idea behind Capital One’s formation was to implement an information-based strategy. It poured two large investments in 2023. The bank has been associated with Databricks for data analytics. Capital One also grabbed the headlines for its efforts to strengthen its AI capabilities with a focus on the ethical use of the technology. The bank is committed to increasing diversity and inclusion in the financial and IT spaces. Consequently, the development and deployment of

Capital One’s AI policy recognizes that the biases of the engineers seep into the technologies they develop, embedding blind-spots and prejudices. Additionally, the limitedness of datasets from which these models are trained further reinforces the bias.

AI at Capital One centers around addressing the inefficiencies in decision-making systems due to design, development, or data-set biases.

The financial services giant also invested in Securiti to leverage unified intelligence and enhance control across governance, security, privacy, and compliance. Capital One also partnered with academic researchers to foster ethics, explainability, and fairness in AI.

At the end of the day, Capital One hopes its AI implementation will simplify and automate extracting value from data.

Royal Bank of Canada

The bank recognized that traders need a lot of assistance to navigate the labyrinth of capital markets. Due to this, it rolled out an AI-based electronic trading platform for its customers across the globe. It started with recommendation support to reduce trading slippage. The solution uses deep reinforcement learning, a technique that does not require recoding. The team recognized that historical data-based approaches don’t fit in the uncertainty-laden, dynamic financial markets.

RBC is also exploring applications of AI in research analysis and report compilation by training large language models. It is taking a cautious approach on use of Gen-AI to assist call-center executives to lower customer grievance costs.

RBC is among the frontrunners in training process automation software with pattern identification to help manage back-office functions. These include anti money laundering efforts, such as flagging suspicious transactions, eliminating fraud originating from credit cards and poor lending practices, and assisting coding and client management personnel.

Are you prepared?

Large players are adopting Gen AI to boost productivity and drive interactions, ML to assess user behaviors and offer intelligent recommendations, predictive analytics to mitigate risk, and much more. To stay relevant and competitive in the financial services industry, you may need to multiply your AI efforts.

With rapid growth in this arena, even large banks are struggling to attract AI talent despite investing billions of dollars. Smaller banks and credit unions find it even more challenging to develop and maintain AI infrastructure and teams. A great way to gain a competitive advantage is to partner with a technology expert.

Goldman Sachs faced a net loss of 106 AI-focused staffers to its rivals. AI talent pools in the banking and financial services sectors are rapidly shifting due to stiff competition.

Leverage the vast experience Opus has garnered in the financial segment, especially in AI-powered data science enablement, AIOps, and data-led transformation. Optimize the value extraction from data across predictive, analytical, and recommendation-based processes. Our experts identify the most suitable approach to maintain operational flexibility and continuity, while driving data-centric transformation. We help you solve complex business problems through a proactive approach to enhance resource utilization, minimize downtime, and streamline data-capability building. Boost operational efficiency through intelligent automation, while mitigating risks and responding to threats. Speak to our experts to learn more and stay ahead of the competition with cutting-edge AI enablement.

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