While many companies are eager to experiment with and implement new technologies, the key to successful adoption is to approach innovation with clearly defined goals and a well-communicated strategy to ensure the broader organisation understands the intended outcomes. However, in the financial services industry, this becomes even more critical as firms must also navigate a range of additional barriers and pitfalls when experimenting with new technology, including:
1. Regulation and compliance
Industry regulators such as the FCA or SEC enforce strict rules around customer privacy and the handling of client data. For example, uploading real data to a public generative AI system, even for experimental purposes, could breach these regulations. To remain compliant, it is important to always use dummy data if using any of these systems.
In certain areas of the financial services industry, you may also need to seek regulatory approval for new technology you are developing. Even if the build and testing phases are completed quickly, it’s important to account for potential lengthy regulatory approval times, as these can vary drastically, particularly when introducing something new.
2. Cost management and cloud overspend
Cloud services offer powerful capabilities for someone developing new services and systems. However, because the hardware layer is abstracted from the user when using public cloud services (e.g. Microsoft Azure, Amazon Web Services), it can be very easy to unintentionally scale up test platforms, leading to unexpectedly large costs at the end. To avoid the project going over budget, ensure all cloud experimentation is closely monitored, properly managed and preferably governed by a spending cap.
3. Cultural and legacy infrastructure
Many financial services firms are operating systems that have been in place for years, sometimes even decades. When developing a new service or experimenting with a new category of service, it’s crucial to identify any potential integrations that need to be in place with these legacy platforms. To support this, ensure you have a comprehensive systems map across the organisation and clearly define where any new development will fit.
Cultural factors are also key to a successful implementation. Consider how employees will adapt to change, especially if the new application or service is added to their application stack. When introducing significant changes, ensure that training and awareness are integral to the launch of the new application.
4. Uncertainty of ROI
Many new initiatives begin without a clear goal of the end game. In some cases, services such as AI can be developed and implemented primarily to enhance user experience or improve efficiency, without a specific focus on return on investment (ROI). In others, systems are specifically designed with the explicit aim of delivering measurable financial outcomes.
Regardless of the objective, it’s essential to ensure these budgets and goals are defined early on with a clear specification to ensure the initiative delivers the expected value to the business. It's also important to recognise that experimentation in new technology is sometimes done in the hope of uncovering bottom-line improvements or higher profits, but this can be very hard to define. Acknowledge from the outset that these research and development initiatives can carry risk, and not all will lead to positive results.
Clear goals help you navigate these barriers effectively
Experimenting with new technology in the financial services industry presents a range of barriers and challenges. Regulatory compliance, including the need for approval from industry regulators such as the FCA or SEC, can delay progress due to drastically varying review times. Cost management is also critical, particularly where there is a potential for cloud overspend in public cloud services if unmonitored.
Financial firms must also address the integration challenges with legacy systems and manage cultural resistance to change, ensuring proper training and awareness to ensure successful adoption. Uncertainty around ROI is another key concern, as some initiatives lack clearly defined goals and may not always yield positive results.
Added to this are broader industry challenges such as risk aversion, data security and privacy concerns, high implementation costs, talent shortages, market concentration, interoperability issues, and the need to build consumer trust can further complicate technological experimentation.
To navigate these barriers effectively, make sure your end goals are clear before you press the green button to start any new initiative.
