AI in Financial Services: Why Incremental Innovation is a Smart Path Forward
By Cindy Griffin, Financial Services Vertical Marketing Specialist at Smart Communications
News about artificial intelligence (AI) in financial services is everywhere. From new model launches to agentic AI to meme prompts (e.g., turning your pet into a human), it’s inescapable. Many organizations, however, are struggling with how to implement AI in a responsible way while also quickly taking advantage of AI’s capabilities.
In particular, AI is magnifying security risks in the financial sector. JPMorgan’s Chief Information Security Officer’s recent Open Letter to Third Party Suppliers emphasizes “prioritizing security over rushing features” by “placing it equal to or above launching new products.” So, how does an organization operating in a highly regulated industry like financial services carry out this dual mandate to integrate AI and prioritize security?
JPMorgan has taken a top-down approach to AI, with the appointment of a Chief Data and Analytics Officer to oversee AI initiatives in 2023 and the deployment of a proprietary large language model, LLM Suite, in 2024. However, since most financial services firms don’t have the resources of JPMorgan, AI implementation in this way isn’t typically practical. Likewise, most firms don’t have the luxury of having a powerful Chief Information Security Officer who can tell third-party suppliers how they need to approach security.
Incremental Innovation in AI
Incremental innovation offers a solution for financial services firms that lack JPMorgan’s resources but want to implement AI in a responsible, secure way. What is incremental innovation? Cutter Associates defines incremental innovation as “leveraging technology to make small tweaks to existing workflows and processes to create outsized gains in operational efficiency.”
In addition to being more budget friendly, incremental innovation builds on existing applications using AI, which allows for manageable scaling and risk mitigation. For example, many firms already use AI or machine learning for predictive analytics in areas like fraud detection or risk assessment. Building on existing AI use cases could help firms advance AI within their organizations while keeping security top of mind. Each incremental advancement would be, by definition, small and could be tested in focused groups to avoid exposing the entire organization to potential security threats. Incremental innovations would also allow firms to be more agile in responding to potential process breakdowns.
However, not all AI progress will come from within. As firms look to scale more rapidly or solve complex problems, they may turn to third-party suppliers offering comprehensive AI solutions. While these integrations can promise significant improvements, they also introduce a different set of risks. If a third-party supplier’s AI integration is advertised as the solution to a whole host of issues, consider the impact on the organization if something went wrong.
AI Adoption Vs. Financial Services Regulations
The emerging regulatory environment will also guide financial services firms’ adoption of AI. For example, the EU Artificial Intelligence (AI) Act classifies AI use according to risk. Financial services firms find many activities fall under high risk or limited risk, which require strict obligations before going to market or specific transparency obligations, respectively. The EU AI Act helps organizations determine the overall business risk when deploying AI. Financial services firms should be prepared that the influence of the EU AI Act may arrive in the U.S., one state at a time, each with intricate differences.
Financial regulators in the U.S. have been cautious about adopting AI-specific rules, preferring to provide guidance around existing rules. Even this information can influence how AI is used in financial services firms. For example, in May 2024, FINRA provided guidance on Rule 2210 (Communications with the Public) in an FAQ. The report also noted that communications with the public—whether generated by a human or AI (chatbot)— would be governed by the same rules. In addition, an early executive order of the current administration seeks to remove barriers to American leadership in AI. While the executive order doesn’t have any new AI-specific rules or regulations, it’s indicative of the potential for rapid change in AI regulations.
Regardless of the regulatory environment, financial services organizations that rely on incremental innovation to adapt to new regulations over time reduce the risk of non-compliance caused by rapid changes.
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How Does Smart Communications Approach AI Innovation?
To help organizations safely and strategically incorporate AI, Smart Communications provides a customer communications management solution with integrated AI. SmartCOMM™ establishes a solid foundation for financial services firms to balance incremental innovation in AI with a strong security and governance posture. Integrated AI technology offers the ability to translate content into different languages and adjust the reading level, tone, and formality of customer communications. Why does our approach to AI matter?
- Governance is in your hands. SmartCOMM’s AI integration is an opt-in feature; it is turned off by default. If your firm is not ready to deploy AI in this manner, it’s not a required feature of SmartCOMM.
- Content provenance matters. In highly regulated industries like financial services, the ability to audit data or content is not only helpful, but in most cases required by regulators. SmartCOMM logs events where AI is employed enabling ease in forensic searches of AI-impacted communications.
- Your data won’t be used as training data. SmartCOMM does not share your organization’s data to train the LLM.
- Security comes first. Any AI use will not come at the expense of jeopardizing our commitment to data security and governance.
- Function is prioritized over flash. Any AI integration will be based on usefulness to our customers and how it helps them achieve their goals. We’re not integrating AI for AI’s sake alone.
Ultimately, when leveraging AI in financial services use cases, organizations will need to be transparent, explanatory, and secure in client communications. Firms that adopt AI through incremental innovation and stay compliant with evolving regulations will strengthen, not weaken, their client relationships.
To discover how your organization can leverage AI in financial services through incremental innovation, request a demo.
About the Author
Cindy Griffin is the Financial Services Vertical Marketing Specialist at Smart Communications.-She has more than 25-years of-experience in financial services marketing and business development, performance analysis, product and risk management, and compliance integration.-Cindy has broad knowledge of the financial services space having worked for institutional investment managers, retirement services providers, and wealth managers in a variety of roles. In addition, Cindy worked in business development for a software provider with a primary focus on the financial services vertical.