Published : 3 weeks ago, on 15/11/2024

Ivan Garces, CPA, Chief Risk Officer, Risk Advisory Services Practice Leader at Kaufman Rossin

By Ivan Garces, CPA, Chief Risk Officer, Risk Advisory Services Practice Leader at Kaufman Rossin

As we approach 2025, we are witnessing fascinating times in the banking & finance sectors, as tech-driven innovation is transforming the way financial institutions do business and build customer relationships. We have seen a major transition to digital-first strategies and services, significantly reducing in-person customer interactions.

As the implementation of digital transformation initiatives and technologies becomes more widespread, its impact is felt not only by banks, but institutions across the financial services spectrum, including investment firms, asset managers, and FinTech companies looking to drive innovation and meet evolving consumer demands.

In this article, we will explore three key areas where digital transformation is reshaping the industry: customer experience, operational efficiency, and risk management. Additionally, we will highlight potential risks that occur in each area and offer some risk mitigation strategies.

By taking a closer look at each of these areas, we can better understand how financial institutions can successfully balance the power of innovation with the need for robust risk management and compliance strategies.

Elevating digital engagement and redefining the customer experience

In today’s banking and financial services landscape, customers have come to expect seamless, personalized digital experiences. Their interactions with banks are primarily through digital channels such as mobile banking apps and virtual customer service systems. With the rise of “invisible banking” and particularly Banking-as-a-Service (BaaS), institutions are offering more streamlined, integrated customer experiences. Customers can manage their finances anytime, anywhere.

The Role of AI and Personalization

Playing a leading role in the transformation of the customer experience is AI-driven personalization. With AI as a tool, financial institutions can analyze large amounts of customer data and deliver personalized services and recommendations. Examples include customized loan products and specific savings plans or investments.

By offering such personalization, financial institutions can not only improve the overall customer experience, they can also deepen engagement and build stronger relationships with customers, increasing long-term value.

However, with this increased use of customer data, there are risks and concerns to consider, particularly around data privacy and security.

Data privacy and security concerns

As businesses increase the use of customer data to deliver more personalized experiences, data privacy becomes a top area of concern, especially with the rise of global regulations such as the General Data Protection Regulation (GDPR), the Gramm-Leach-Billey Act (GLBA) and the California Consumer Privacy Act (CCPA). Regulations like these are designed to protect customer information and allow individuals to exercise more control over how their data is used.

In addition to regulatory compliance, there are also increasing concerns about fraud and security risks associated with the widespread use of digital technologies:

• Fraud risks have increased due to cybercriminals exploiting digital channels and targeting customer accounts.
• Money-laundering risks are also growing, mostly due to the global nature of transactions and the increased speed of transactions coupled with schemes used by maligned actors to obfuscate their identity.
• The emergence of deepfakes and other AI-powered threats prompts additional concern, as criminals have adopted AI-driven chatbots or generated images for impersonation purposes, making it harder for institutions to verify the identities of individuals interacting with their platforms.

To mitigate these risks, financial institutions should implement effective strategies that include key measures such as:

• Encryption technologies: Using encryption, both at rest and in transit, can be an effective way to protect sensitive customer data. With encryption technologies in place, customer data can remain secure in the event of a breach.
• Multi-factor authentication (MFA): Requiring multiple forms of identification can help reduce the risk of fraud committed through unauthorized access to accounts.
• Advanced verification methods: Institutions can defend against the threat of deepfakes by leveraging advanced verification technologies such as biometric authentication or AI-powered image analysis.
• Robust and real-time Know Your Customer (KYC) and sanctions screening software.
• Clear privacy policies: Transparency is key when it comes to addressing data privacy. It’s essential to clearly communicate privacy policies to customers, not only ensuring regulatory compliance but increasing customer trust.

These risk mitigation strategies can help financial institutions continue to take innovative approaches to provide a better, personalized customer experience while protecting customer data and maintaining regulatory compliance.

Enhancing operational efficiency through AI and automation

We have seen transformative effects on the operations side of financial institutions, as the role of AI and RPA has rapidly expanded. These technologies help streamline key operational processes, fostering increased efficiency, accuracy, and cost savings.  

The McKinsey Global Institute estimates that generative AI could add between $200 billion and $340 billion annually to the banking industry, primarily from increased productivity.

AI and RPA are reshaping a wide range of operational areas, including:

• Customer service: AI-powered chatbots can provide 24/7 customer support, offering convenience by answering common queries, processing simple transactions, and allowing human customer service agents to focus on the more complex cases that require extra attention.
• Fraud detection and prevention: By continuously monitoring transactions for suspicious patterns, AI systems can identify potential fraud in real-time.
• Document processing: Automation is streamlining document processing by increasing processing speed and reducing the need for manual entry, also minimizing human errors.
• Credit scoring: AI is transforming the credit scoring process by assessing a broader set of data points and creating more accurate risk assessments for loan applicants.
• Regulatory compliance: AI and automation can be useful in compliance matters, particularly associated with regulations like Know Your Customer (KYC) and Anti-Money Laundering (AML), also enhancing sanctions screening. The capabilities of AI systems include analyzing vast datasets for customer identity verification, monitoring transactions for suspicious activity, and ensuring that institutions comply with regulations governing financial crime.

Bias, system integration, and compliance challenges

While AI and automation systems provide numerous benefits, they also come with potential risks. One pressing concern is algorithmic bias that could creep into automated decision-making processes, especially in areas like credit scoring or loan approvals. Certain AI systems may be trained on biased or incomplete data. This opens the door to unintentionally producing unfair outcomes, which could lead to regulatory violations or costly litigation and reputational damage.

System integration could present another challenge, as many financial institutions are still relying on legacy systems that are not compatible with advanced AI and automation tools. Trying to integrate these technologies into an older system can lead to difficulties, including inefficient processes and system downtime.

Moreover, if automation tools are not properly configured, this could create compliance gaps. Failure to properly configure bots and keep them regularly updated in alignment with evolving regulations can cause adverse scenarios such as missing crucial regulatory updates and incurring penalties for non-compliance.

Key strategies for AI and RPA risk management

To mitigate the risks associated with the implementation of AI and automation systems in their operations, financial institutions can implement regular audits of these systems, identifying and correcting potential issues. Creating transparent and compliant decision-making processes can help institutions stay compliant with regulations such as the Equal Credit Opportunity Act (ECOA). Establishing AI governance frameworks can help institutions monitor their AI deployments, further ensuring alignment with both operational and regulatory objectives.

Robust risk management strategies in the age of digital transformation

As financial institutions continue to partner with FinTechs and adopt innovative technologies, they face heightened regulatory scrutiny. Compliance with data privacy, AML, third-party risk management and cybersecurity regulations is critical, and regulatory bodies encourage innovation while holding institutions to high standards.

Third parties such as FinTechs can help institutions elevate their business.  Collaboration between the parties should include shared risk mitigation strategies that help ensure that they will work together to meet compliance standards while pursuing their business objectives.

To address the risks that come with third-party partnerships, financial institutions can adopt the following strategies:

• Implement regulatory technology (RegTech) to automate compliance-related tasks, enabling adherence to evolving regulations.
• Establish vendor risk management frameworks to monitor third-party compliance and conduct ongoing risk assessments.
• Work with an advisory firm to navigate complex regulations and provide tailored risk management solutions.
• Strengthen cybersecurity systems and practices, including the addition of AI-driven tools for cyber threat detection and prevention.

These strategies can help banks and financial institutions effectively manage the risks that come with digital transformation, ensuring compliance while protecting themselves and third-party vulnerabilities.

Navigating digital transformation and risk in 2025

Adapting to digital-first strategies in an evolving landscape means institutions must stay agile, implementing digital transformation strategies while navigating regulations and risks. Those who can successfully integrate new initiatives and tools with a robust risk management framework will be in the best position to thrive in the evolving financial landscape in 2025 and beyond.

About the Author

Ivan Garces is a senior advisory principal, Chair of Kaufman Rossin’s Risk Advisory Services practice, serves as the Firm’s Chief Risk Officer and is a member of the Firm’s Management Committee. He has extensive experience evaluating risk management programs, internal controls, anti-fraud, anti-money laundering and sanctions compliance programs, USA PATRIOT Act, Bank Secrecy Act, Office of Foreign Assets Control and Foreign Corrupt Practices Act compliance programs and assisting companies and financial institutions respond to regulatory enforcement actions related to such matters.