Goals and challenges in financial services

  • 3 minutes

A recent survey asked FSI executives about their expectations on generative AI applications. Most of them believed this technology would help their organizations in fraud detection (76 percent), risk management (68 percent), and client experiences (66 percent).2

However, AI comprises a wide array of techniques, working in data, text, vision, speech, and so on. Accordingly, there are many more AI use cases that you can apply to your FSI business, whether you work in banking, capital markets, or insurance. Despite this complexity, the FSI industry faces some common goals and challenges.

Goals

Most finance goals derive from the utmost confidentiality of financial data. FSI organizations need to manage data in the most responsible, careful way possible:

  • Data privacy and protection: AI solutions in FSI need to follow strict data privacy and protection procedures. This concern often implies adding multiple layers of data security. AI systems can help ensure these measures in more efficient ways.
  • Compliance: FSI is a highly regulated sector. Actions must follow precise and demanding protocols. AI can help enforce compliance by detecting anomalies and monitoring procedures.
  • Automation: FSI organizations must automate as many data processes as possible, including discovery and policy creation.

Photograph showing people meeting in a conference room.

Challenges

However, there are specific obstacles for the implementation of AI in finance. When your team designs AI solutions, you must watch for these issues:

  • Legacy hardware and software: FSI organizations sometimes rely on outdated technologies. New innovative AI systems can conflict with this legacy infrastructure. Besides, legacy systems often can’t interface with information protection and data loss prevention solutions.
  • Technical debt: Even when hardware and software aren’t themselves outdated, many solutions accumulate technical debt, that is, parts of the code become deprecated and risk the robustness of the system. At some point, this technical debt must be paid for the system to be fully operational or scalable.

Tip

Take a few minutes to consider what other goals or challenges are specific to your organization. Photograph showing people working and talking around a table.

Next, let’s explore opportunities for AI in financial services.