As financial services firms embark on their generative AI (GenAI) journeys, a critical challenge is balancing the imperatives of innovation and value creation with the need for safety, compliance, and responsible usage.

Capco has a long and successful track record of leveraging broader AI technologies for our clients’ benefit, and over the last 18 months we have also explored and adopted GenAI tools and techniques. 

This practical experience has provided us with valuable insights into how organizations can safely accelerate their own adoption of this game-changing technology.

Our pilot surfaces some fundamental considerations when embedding GenAI into financial services operating models.

Democratizing AI is the quickest route to identifying high value use cases within your organisation. With a focus on unlocking safe exploration and experimentation, we provided employees with access to GenAI tools such as ChatGPT Enterprise – and with that tooling in their hands, they were able to validate new use cases 15 times faster than previously. 

Upskilling the workforce to effectively leverage GenAI is as critical to success as the technology itself. Those employees with the right training saw efficiency gains of up to 50% when completing certain tasks, compared to efficiency reductions of up to 10% for those who had not been trained. Over just six weeks of use, employees' understanding of GenAI improved significantly, with the average self-assessed rating increasing by two grades (e.g. from Poor to Good). This degree of improvement was achieved through interactive training such as ‘promptathons’, a Capco workforce upskilling program on prompt engineering and GenAI best practices to ensure safe and effective use of tooling.

Operating models should minimize the bureaucratic hurdles and silos (particularly within large organisations) that can stifle the cross-functional collaboration essential for innovation. Organisations need to review and adapt their current processes to account for and enable GenAI if they are to avoid slow progress, duplication and low adoption.

Data management demands particular attention given the level of unstructured data that fuels GenAI outputs. Data must be the priority for organizations if they are to ensure the greatest impact and usage of AI. High quality data is vital to successfully scaling both the adoption and democratization of GenAI capabilities as they become more accessible. Most organizations have already begun this journey by enhancing their data governance, management, and architecture initiatives to obtain a better understanding of what data they have, as well as the quality of the data.

Safety and governance are crucial considerations throughout the GenAI exploration process. Capco's approach is built around minimal viable governance, ensuring safety and compliance with regulation without stifling innovation. We applied over 90 controls to ensure responsible usage. Issues identified during testing, such as potential bias or inconsistencies, were carefully analyzed to determine root causes and appropriate mitigation measures before scaling. This risk-aware approach to innovation is essential, especially in highly regulated industries like financial services.

Technology Infrastructure Legacy disconnected infrastructure is prevalent across FS and – which hinders organizations ability to use AI at scale. The modernization of core legacy systems is a critical step in the broader digitalization journey, and it is vital to get it right first time. Capco has developed a proprietary Legacy Modernization Toolkit that ensures systems knowledge can be accessed and transferred effectively and refactoring decisions made in an informed fashion – allowing systems modernizations to be scaled and accelerated at an unprecedented rate.

Optimal use cases for success

Where individual organizations go next will require bespoke choices based on where they are now and the scope of their AI ambitions. Taking our insights into account and recognizing that financial services is a complex and heavily regulated environment, we have identified some high value use cases focusing on customer service, efficiency gains and insight generation, and which retain a human in the loop to reduce associated risks. 

1. Customer Service Assistants

Deploy GenAI-powered assistants to support customer service representatives by handling routine inquiries, providing information, and assisting with basic transactions. This enhances the efficiency of human agents, improves response times, and improves customer satisfaction.

• Low Risk – these assistants can be designed to support human agents rather than replace them, with escalation to human intervention for complex issues.

2. Fraud Detection and Prevention

Use GenAI models to analyze transaction patterns and detect anomalies that may indicate fraudulent activity. The scale and speed of GenAI analysis far exceeds human review. This enhances security and potentially reduces financial losses due to fraud.

• Moderate Risk – requires careful tuning to minimize false positives and negatives, however the technology and methods to achieve this are well-established.

3. Document Processing Automation

Automate the extraction and processing of data from documents like loan applications, claims, and contracts using GenAI. This improves efficiency, reduces manual errors, and speeds up processing times.

• Low Risk – involves automating routine tasks with clear rules and structured data.

4. Personalized Marketing and Recommendations

Implement GenAI solutions to provide personalized product recommendations based on customer data and behavior beyond standard demographic insights. This increases customer engagement and conversion rates for products.

• Low to Moderate Risk – requires good data privacy practices and accurate algorithms, but offers significant marketing benefits.

5. Software Development Lifecycle (SDLC) Optimization

Use AI to optimize various phases of the SDLC, such as code review, bug detection, project management, and testing automation. This enhances code quality, reduces development time, and improves project management efficiency.

• Low to Moderate Risk – augments existing development practices with AI-driven insights and automation.
  
  

As Capco's pilot demonstrates, the road to GenAI value starts with experimentation. The technology itself is just one piece of the puzzle, however. Unlocking GenAI’s full potential demands a more fundamental reimagining of how financial services organizations operate – from their technology foundations and data assets, through to their processes, skills mix and ways of working. 

Those organizations that approach this transformation with openness, curiosity and collaboration will be best positioned to thrive in an AI-infused future.