Generative artificial intelligence (GenAI) provides a glimpse of how today’s teams can leverage technology as an enabler of insight and efficiency. As a result, executives are now in the spotlight with their Boards, who are demanding action plans to adopt GenAI strategically across their organizations.
Executives, however, often find themselves planning and presenting GenAI strategy while still trying to figure out exactly how to best apply it. Despite improvements to GenAI user education, corporate discussions are too often rooted in theoretical instead of practical applications.
Banks and other financial services institutions are changing that.
With great exposure to the effects of GenAI relative to other industries, banks are capitalizing on this opportunity by quickly developing and deploying pragmatic GenAI-enabled solutions in core areas of the business. Meaningful, measurable use cases are here, and they’re already driving real value. Explore how below.
Current Banking and Capital Markets GenAI Adoption
Research and Analysis
Adoption of GenAI’s processing capability paired with firms’ research libraries have provided wealth managers with more accurate market insights and investment opportunities. Wealth managers can augment these findings with their clients’ investment profiles and generate personalized investment strategies more efficiently for their clients. As Jeff McMillan, Head of Analytics, Data, and Innovation at Morgan Stanley Wealth Management, said in an interview with CNBC referring to GenAI, “We saw a window of opportunity … we didn’t want to get left behind.”
Customer Support
Before GenAI hit the mainstream, banks had leveraged technology to improve customer interactions. Chatbots provide 24/7 customer support through programming pre-set answers to the most common questions banks identified in their customer base. GenAI took it a step further with the development of Customer Support Assistants that can generate real-time responses, which enables more natural interactions with clients, thereby eliminating a fixed set of responses.
Capital One is one such example with Eno, a GenAI assistant that supports customers in their inquiries, alerts them to atypical activity, and even provides services in account management. Eno can monitor customer accounts by looking for unique charges and protect customers’ financial information by creating virtual card numbers for online shopping.
Records Management
Another growing use case Biovell has helped develop is leveraging GenAI technology to support client-facing employees with records management in their client interaction lifecycle. By summarizing large volumes of data collected through emails and integrating this information with a records management tool, the AI enables regular updates to the records tool. This GenAI-enabled process still requires human oversight to review and approve updates made by GenAI to the records, but it has dramatically improved document processing time.
Emerging GenAI Trends in Banking and Capital Markets
Cybersecurity
While GenAI presents ongoing data protection and cybersecurity concerns, it also provides a significant opportunity for banks in their fight against bad actors. Financial services continues to be one of the most targeted industries for cyberattackers, with the number of reported data breaches and attacks growing year over year.
IBM noted that the global average cost of a data breach reached $4.45 million in 2023. But organizations that adopted GenAI and automation experienced a data breach lifecycle that was 108 days shorter than organizations that hadn’t deployed these technologies (214 days versus 322 days). GenAI reduces the data breach lifecycle by more efficiently isolating compromised areas in technology infrastructure and providing a quicker analysis of fraudulent activity.
As cyberattacks evolve, companies are using GenAI in their threat protection exercises, particularly the popular cybersecurity exercise of Red Team vs Blue Team. With GenAI, red team vs blue team exercises have an additional interactive member that can participate in threat protection and security infrastructure testing.
Fraud Detection
GenAI defends against bad actors through anomaly and fraud detection. Banks are continuously analyzing, learning, and adapting to emerging fraud tactics to offer robust protection for customers – even as hackers continue to prey on banks and their customers. With the rise of digital transactions, GenAI-enabled risk management tools and techniques offer real-time solutions aimed at blocking fraudulent transactions or requiring verification before proceeding. Companies such as Mastercard are leveraging internal GenAI’s advanced pattern recognition applications to analyze potentially fraudulent or unusual transactions and banking actions.
AML/KYC
The trend of client bases being exposed to new methods of high-risk transaction approaches has elevated the need for mature Anti-Money Laundering/Know Your Customer (AML/KYC) processes to improve their detection and analysis capabilities. This can be unlocked through GenAI.
GenAI provides an advantage due to its ability to gather, centralize, analyze, and provide insights across multiple data sources. GenAI can expose hidden patterns by tracking the complex relationships and networks that occur in money laundering. For example, banks can leverage these tools to automatically generate a customer risk score based on transactional patterns, network behaviors, and high-risk transactions. This is a step beyond traditional rule-based transaction alerting systems and allows AML/KYC teams to do deeper investigations of their clients and make more informed decisions.
Featured Insight
Unit Testing in Technology Implementation
A critical aspect of the development and implementation of new technology is the testing stage, established toward the end of the development lifecycle. The goal of the testing stage is to ensure that technology performs as expected, meets user expectations, and will not harm the technology infrastructure when deployed to production.
The software testing market is expected to exceed $20 billion by 2032, and now GenAI can act as an independent Quality Assurance engineer to create and execute test cases written by human QA resources. This avoids the potential conflict where a tester creates their unit test cases and executes them themselves. It also addresses the challenges of workforce attrition and finding quality testers at scale across service lines.
GenAI Adoption: Prepare Your Strategy
Banks must continue embracing innovation to stay ahead of competitors and change curves. The applications of GenAI illustrated above are just the tip of the iceberg. Because each bank has its own unique data and technology infrastructure, it’s best to partner with a team of industry experts with demonstrated skills in identifying GenAI use cases that deliver real value in support of the organization’s strategy and vision.
Biovell ’s Banking & Capital Markets team advances key initiatives on GenAI and other progressive technologies for leading organizations amid rapid disruption. With new perspectives on how to implement GenAI strategically and key GenAI considerations banks must address to manage risk, our team enables organizations to capitalize on relevant AI opportunities with proven strategies, frameworks, and accelerators. To explore practical GenAI solutions designed for your specific use case, contact Biovell .
This article is part of a series on generative AI technology, implementation strategies, use cases, and more in Banking & Capital Markets.