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Analysis by global consultancy Capco lists the 5 fundamental elements for using
technology more efficiently and safely

An unprecedented acceleration in management has been happening in companies in recent years with the use of Generative Artificial Intelligence (GenIA). In the financial sector, this technology is capable of identifying possible improvements in operational efficiency, innovation in products and services and overall business performance, but it also involves risks that are not yet fully known.

Organizations should benefit from technological developments, but innovation alone does not solve everything. They need to be prepared to face challenges and risks that arise because the technology is still new. Therefore, Capco, a global management and technology consultancy for the financial sector, carried out the study “Five Foundational Elements for Generative AI Governance in Financial Services” (Five key elements for generative AI governance in financial services, in free translation).

“In addition to addressing compliance issues, the study shows that robust governance needs to be adapted to address GenAI-specific risks and to promote the responsible and transparent use of AI technology in the segment,” explains Gerhardt Scriven, CEO of Capco Brazil.

Therefore, organizations need to reassess them to create a control inventory and adapt to GenAI. “In this context, integrated participation by legal, compliance, business and technology teams is essential, aiming for a holistic approach. GenAI should be seen as an additional management tool, and not as an ideal solution,” warns Scriven.

According to the study, the fundamental elements for GenIA governance are:

1- Improve risk identification and management
It all starts with updating risk management structures and controls to prevent unauthorized use of data and not compromise its integrity. This includes strengthening cybersecurity, stricter management of third-party suppliers and GenAI technology providers, and compliance with industry regulatory guidelines. Another crucial aspect is valuing talent, that is, professionals trained to manage and monitor this initiative, supported by automated solutions that detect anomalies in real time, reducing impacts on operations and protecting the customer experience.

2- Define responsibilities to adopt GenAI uniformly
For effective governance, it is essential to clearly define oversight roles and responsibilities. There are three main governance models that can be adopted. One is centralized, with a central body overseeing AI initiatives, defining standards, policies, and methodologies. Another is decentralized, with teams reporting to the organization’s AI governance leader, practicing self-governance with distributed decision-making. In addition, there is the hybrid model, which centralizes AI expertise and best practices while allowing business units to innovate and adapt solutions as the organization needs.

3 – Prioritize privacy and security
Potential barriers to GenAI adoption have been overcome with the use of Large Language Models (LLMs) and other GenAI tools that leverage enterprise data without requiring extensive model training. The problem is that this can include sensitive company information and sensitive data (LGPD), making data privacy and security a major concern and a critical component of overall governance.

To avoid this, it is imperative to use private business models in secure cloud environments, identify sensitive data when using LLMs, take steps to prevent leaks, define access guidelines, and work in compliance with industry standards and regulations. Companies are taking notice. According to Cisco’s 2024 Data Privacy Benchmark Study, most organizations are limiting the use of GenAI due to data privacy and security concerns. Thus, 27% of them have temporarily banned its use and 48% admit to entering non-public company information into GenAI tools.

4 – Have a detailed inventory of applications that use GenAI
Have a framework capable of maintaining a central repository that allows companies to track the use of AI technology across multiple business units, including managing vendor AI solutions, AI adoption projects, AI models, data sources for AI consumption, and critical artifacts such as systems documentation.

5 – Promote an appropriate culture
The company must prepare to ensure that leaders and employees are educated so that the application of GenAI is appropriate for the intended purposes, promoting a culture of responsible use of the technology. Best practices related to Generative AI can be implemented through customized training programs, documented policies and procedures for uniform adoption within the organization.

Capco’s executive warns that, as part of a highly regulated industry, financial services companies need to prioritize regulatory compliance, especially in the case of GenAI, which is marked by high scrutiny and constantly updated new guidelines. “While GenAI offers transformative potential for the financial services industry across a number of use cases, only effective governance of GenAI can ensure that its impact remains compliant, fair and safe for all,” advises Gerhardt Scriven.

About Capco
Capco, a Wipro company, is a global technology and management consultancy focused on the financial services and energy industries. Capco operates at the intersection of business and technology, combining innovative thinking with unmatched industry expertise to support clients across banking and payments, capital markets, wealth and asset management, insurance and energy. We help our clients simplify complexity to see a clear path forward and create solutions that enable them to transform their businesses and build a lasting legacy of success. For more information, visit site.

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