AI in finance: how employees can shift their roles from being replaced by AI to being essential contributors (18.12.2024)

Klarna, the Swedish payment services company, has not hired new employees for over a year, relying increasingly on artificial intelligence (AI) to optimize work processes. According to CEO Sebastian Siemiatkowski, the company has reduced its workforce from 4,500 to 3,500 employees, primarily through natural attrition.

AI has already taken over many tasks previously handled by humans. For instance, a GPT-4-based chatbot now handles customer service in 35 languages, effectively replacing 700 full-time employees. This innovation has reduced the average response time for customer inquiries from 11 minutes to just 2 minutes, potentially boosting Klarna’s profitability by $40 million annually.

Despite these changes, Klarna’s website still lists over 50 open positions, mainly in technical roles. Company representatives emphasize that they are not actively expanding their workforce but are filling critical roles, particularly in engineering.

Klarna’s strategy includes further workforce reductions, leveraging AI to enhance efficiency. This approach aligns with its preparation for a potential IPO, as the company seeks to demonstrate both innovation and cost-effectiveness.

The move reflects a broader trend in the tech industry, where companies increasingly adopt AI to cut costs and boost productivity. This shift challenges traditional employment models and presents new challenges for workers.

Opportunities and and Benefits of using AI in financial services to optimize work processes

The integration of AI in financial services offers numerous opportunities and benefits that can significantly optimize work processes.

• Enhanced Efficiency
• Scalability
• Cost Reduction
• Improved Accuracy and Risk Management
• Innovation and New Services

AI systems, such as chatbots and data-processing tools, enhance efficiency by performing tasks much faster than humans. For example, Klarna’s implementation of a GPT-4-powered customer service assistant reduced response times from 11 minutes to just 2 minutes. This level of efficiency allows companies to better serve customers while also cutting operational costs.

AI also brings scalability, enabling companies to manage a much larger volume of transactions, queries, or decisions without the need to proportionally increase their workforce. AI operates continuously, handling tasks across multiple languages and time zones, which is particularly advantageous for global financial services operations.

Cost reduction is another significant benefit of AI adoption. Through automation of repetitive tasks, companies can minimize the need for a large human workforce. For instance, Klarna’s AI chatbot replaced 700 full-time employees, leading to a projected annual profitability increase of $40 million.

AI improves accuracy and strengthens risk management by reducing the likelihood of human error. This is especially critical in financial services, where precision is essential. AI systems minimize mistakes in areas such as data entry, fraud detection, and compliance monitoring.

Furthermore, AI fosters innovation and the development of new services. Financial institutions can offer highly personalized services like tailored loan options and credit evaluations by rapidly analyzing large datasets. AI also drives the creation of new financial products, such as real-time risk analysis tools and predictive financial planning applications.

By leveraging AI, financial services companies can streamline processes, enhance decision-making, and create innovative, customer-focused solutions.

Challenges and Risks

The adoption of AI in financial services also brings with it several challenges and risks.

• Job Displacement and Workforce Impact:
• Dependence on Technology
• Algorithmic Bias and Fairness
• Regulatory and Legal Challenges
• Customer Trust and Acceptance
• Skill Gaps

One major concern is job displacement and the impact on the workforce. For example, Klarna’s use of AI has resulted in the replacement of hundreds of human workers. While this can lead to reduced operational costs, it raises ethical and social issues related to unemployment and the changing nature of work.

Another significant challenge is dependence on technology. Heavy reliance on AI creates vulnerabilities, such as system failures, cyberattacks, or biases in algorithms. These issues can disrupt operations and weaken customer trust, especially when errors occur or systems fail unexpectedly. Additionally, algorithmic bias remains a persistent risk. Since AI systems are only as unbiased as the data they are trained on, they can perpetuate discrimination, including unfair credit scoring or loan denials for marginalized groups.

Regulatory and legal challenges further complicate the integration of AI into financial services. Companies must navigate strict oversight and ensure compliance with evolving laws related to data privacy, algorithm transparency, and accountability for automated decision-making. Moreover, customer trust and acceptance represent another hurdle. Although AI has the potential to improve service delivery, customers may be hesitant to trust automated processes, especially for sensitive financial transactions. Balancing technological efficiency with the human touch is critical to maintaining this trust.

Lastly, skill gaps pose a challenge as organizations transition to AI-driven processes. Employees must acquire the skills necessary to manage, monitor, and refine AI systems, requiring companies to invest in reskilling their workforce. This process can be both time-consuming and costly, adding another layer of complexity to AI adoption.

Embracing AI in Finance: How Employees Can Adapt and Thrive in the Age of Automation

Employees in finance can adapt to the rise of AI by developing skills that complement technology rather than compete with it. Here are key areas where skill development can help employees stay relevant:

• Technical Proficiency
• Strategic Thinking
• Soft Skills and Emotional Intelligence
• AI Management and Oversight
• Continuous Learning and Adaptability

Technical proficiency is vital; employees should become familiar with AI-powered tools like predictive analytics, risk assessment algorithms, and robotic process automation (RPA). Additionally, building data literacy—understanding how to analyze, interpret, and visualize financial data—enables employees to uncover insights that go beyond the capabilities of machines. Learning basic programming languages such as Python, R, or SQL is also advantageous, as these skills facilitate collaboration with AI systems, process customization, and data management.

Strategic thinking is another essential area to focus on. Employees should aim to interpret insights generated by AI and use them to make informed decisions. Machines can process vast amounts of data efficiently, but they lack the ability to place that data into broader strategic or ethical contexts. Strong decision-making that incorporates long-term planning and ethical reasoning will be critical to ensuring the effective use of AI within finance.

Soft skills and emotional intelligence remain irreplaceable in an AI-driven environment. Employees should prioritize building strong customer relationships by leveraging interpersonal communication, providing empathy, and addressing client needs—qualities that AI cannot replicate. Collaboration is equally important, as successful teamwork will involve combining AI expertise with financial domain knowledge to bridge the gap between technical applications and business strategies.

AI management and oversight are also vital skill areas. Employees should become proficient in monitoring and supervising AI systems to ensure they operate as intended and mitigate any potential issues such as biases or errors. Additionally, staying informed about AI governance and compliance is essential for organizations to navigate the complex regulatory landscape effectively.

Continuous learning and adaptability will ensure employees remain competitive. This involves pursuing relevant courses, certifications, and consistently keeping up with technological innovations in AI and finance. As roles evolve, being open to new opportunities such as AI Ethics Advisor, AI Risk Manager, or AI Collaboration Specialist will allow professionals to align their expertise with changing demands.

By developing these complementary skills, finance professionals can transition from fearing replacement by AI to becoming vital contributors who shape and guide its application across the industry.

About ECEBiS

At ECEBiS you are going to understand what will change the trajectory of the financial industry. You will develop a transversal view on the forces that are shaping the future financial industry.

From payments and lending to investment and money management, tech providers are actively shaping the future of the financial landscape - even pushing the boundaries of currency itself. You might evaluate the impact of robo-advising on health management and examine portfolio recommendations from a diversified set of RAs and attempt to identify the factors behind proposed splits between asset classes.

ECEBiS is a platform in academic research on new business models and innovative products. We investigate in fast moving sectors that are reshaping the financial world of tomorrow and pioneering new ways of doing business. We want to attract outstanding ECEBiS students in finance with experiences and exposures, who intend to

Doctorate of Business Administration (DBA) in Finance (online, 3 years part-time)

• develop knowledge on challenges that shape the future of financial industry

• engage with a program that offers the convenience of online learning with the benefits of accreditation and global reach.

• raise awareness on the importance of fintech and sustainability in finance

• identify the best practices in the financial industry to spread positive changes

• Go beyond the virtual classroom and network with other ambitious executives and entrepreneurs as you expand your credibility and expertise in the world’s most transformative fields.