INSPIRATION FROM RESPONSIBLE AI-USE CASES IN FINANCIAL SERVICES AND RETAIL
Pause or accelerate AI-development?
Some of the biggest names in tech are calling for artificial intelligence labs to stop the training of the most powerful AI systems for at least six months, citing “profound risks to society and humanity.” Elon Musk was among the dozens of tech leaders, professors and researchers who signed the letter, which was published by the Future of Life Institute, a nonprofit organisation backed by Musk.
The letter comes just two weeks after OpenAI announced GPT-4, an even more powerful version of the technology that underpins the viral AI chatbot tool, ChatGPT. In early tests and a company demo, the technology was shown drafting lawsuits, passing standardized exams and building a working website from a hand-drawn sketch.
The letter said the pause should apply to AI systems “more powerful than GPT-4.” It also said independent experts should use the proposed pause to jointly develop and implement a set of shared protocols for AI tools that are safe “beyond a reasonable doubt.”
AI-Powered transformation: embracing resilience in a rapidly evolving world
In today’s rapidly evolving world, industries such as banking, insurance, and retail are however encountering exceptional challenges that can be effectively addressed through the use of AI systems. The COVID-19 pandemic, political instability, and natural disasters have imposed considerable pressure on these sectors. According to the annual industry reviews conducted by Mc Kinsey, the operating models within these industries have unveiled significant problems, impacting their potential for growth and profitability. This is further substantiated by research from E-cology Innovations, an AI-business accelerator and venture capital firm, which confirms these findings based on the first-quarter results of 2023.
Fortunately, visionary industry leaders have not only recognized these challenges but are actively devising strategies to overcome them. Cost-cutting measures and digital transformations have emerged as common approaches in the face of adversity. However, despite concerns regarding the rapid advancement of AI technology and its potential risks, I firmly believe that artificial intelligence (AI) should play a pivotal role in driving a profound transformation of business models within these industries. It surpasses mere proofs-of-concept and necessitates a comprehensive overhaul of operating models. However, I emphasize that rather than halting progress in AI, the key lies in exercising control and ensuring a responsible and regulated development of these systems.
Successful use cases act as powerful catalysts for company transformation. In this blog, I will discuss three impactful areas where responsible AI can revolutionize industries. Drawing from my research findings and practical experiences, I will explore how these sectors can and should utilize AI to fundamentally transform their operating models. By embracing AI in this manner, companies can embark on an accelerated path towards resilience and growth, ultimately achieving valuations that exceed industry standards.
Area 1: Dynamic enterprise risk management for accelerating company resilience
In times of economic uncertainty, effectively managing risks is one of the greatest challenges faced by companies. The diverse array of risks, ranging from market fluctuations to cybersecurity threats and regulatory compliance, makes this task complex and interconnected. Many companies struggle to keep pace with the rapidly evolving nature of these risks, often relying on traditional and fragmented approaches.
However, breaking free from this trend and embracing AI-centered business models paves the way for integrated and proactive enterprise risk management. By harnessing the power of AI-powered predictive models and dynamic data, companies can gain better insights into potential risks and opportunities before they materialize, enabling them to take proactive measures to mitigate their impact.
In my academic paper, “AI in Risk (2018),” I pioneered the development of cutting-edge AI models for risk prediction. Through extensive analysis of data from over 133,000 mortgage and credit card customers in the UK and the Netherlands, I conducted a compelling comparison between these AI models and traditional approaches. The results were remarkable. The AI-powered mortgage risk decisioning models demonstrated an enhanced predictive power of 10%-20%, while the credit card risk decisioning models showed an impressive boost of 25%-35%.
By leveraging AI, banks can proactively identify at-risk customers at an early stage, enabling them to take crucial actions to mitigate risk exposure. These actions may include renegotiating loan terms or providing tailored financial counseling. This not only mitigates risk but also addresses the information asymmetry that exists for customers. Furthermore, by incorporating dynamic data from open banking, mobile phone behavior, and psychometric decision-making, the effectiveness of risk control is further accelerated, promoting financially healthy customer decision-making.
Similarly, insurers can leverage predictive analytics to identify policyholders with a high likelihood of making claims, enabling them to adjust premiums or coverage levels accordingly. In an experiment conducted with an insurance company, we trained AI models that accurately predicted 80% of potential churners and 90% of high-value churners. This valuable insight allowed the insurer to refine their strategies and effectively retain more customers.
Moreover, retailers can employ predictive analytics to forecast demand for different products, enabling them to optimize inventory levels and pricing strategies to maximize profitability. In my work with a prominent home-improvement retailer in Asia, we discovered that the implementation of intelligent pricing and forecasting emerged as the second most significant driver of profit growth.
By embracing AI and its predictive capabilities in dynamic-risk systems, companies can revolutionize their risk management practices, adapt swiftly to changing circumstances, and unlock new avenues for growth. The transformative potential of AI in these domains is immense, empowering companies to thrive in an era defined by uncertainty and disruption.
Area 2: AI- driven customer engagement and retention
AI-driven customer engagement and retention initiatives are essential in today’s competitive landscape. Companies can leverage AI-powered next best action engines, customer engagement tools, and retention strategies to forge stronger and personalized relationships with their customers. By doing so, they can increase customer value, boost revenue, foster loyalty, and minimize churn.
For instance, at AdviceRobo, we harness the power of AI and AI-driven tools to automate the processing and analysis of data from various open banking providers. This enables our customers to create their own marketing and risk use cases, empowering them to deliver targeted and tailored experiences to their clientele.
Similarly, AI can revolutionize the insurance industry by offering personalized advice and tailored coverage options. Leveraging AI, insurers can leverage lifestyle data to create personalized insurance policies that align with a customer’s unique needs and preferences.
In the retail sector, AI-driven analytics can unlock valuable insights from customer purchase data. This information can be utilized to provide personalized recommendations, suggest complementary products, or offer exclusive discounts to customers who have demonstrated repeat purchases.
In conclusion, embracing AI-powered customer engagement and retention strategies opens up a world of possibilities for businesses across industries. By leveraging AI’s capabilities, companies can elevate their customer interactions, strengthen brand loyalty, and drive sustainable growth in today’s dynamic market.
Area 3: AI-centered supply chain optimization
In the face of economic uncertainty, businesses are confronted with the formidable task of maintaining seamless supply chain operations. However, with the transformative potential of AI-driven supply chain optimization, companies can proactively identify and mitigate potential disruptions, bolstering their resilience and minimizing the risk of costly interruptions. With AI-powered supply chain optimization, companies can proactively fine-tune their operations, minimize costs, and consistently deliver reliable service to their customers. By anticipating potential disruptions and fostering the resilience of their supply chains, businesses can successfully navigate economic storms and emerge even stronger.
Envision a world where retailers possess the ability to accurately predict their stock requirements through AI-driven demand analysis. This ensures they never experience stockouts of popular products or waste resources on excess inventory. Picture a banking system that leverages AI to optimize cash management processes, effectively mitigating the risks associated with cash shortages or surplus liquidity. Similarly, insurers can harness AI to streamline underwriting and claims processing, ensuring prompt and precise payments for customers when they need it most. Furthermore, retailers can revolutionize their logistics and pricing processes by embracing AI and dynamic data, resulting in enhanced customer service and satisfaction.
In the realm of AI, the debate about risks and benefits rages on, with calls for caution and control. However, amid these discussions, it is crucial not to overlook the immense potential that AI holds for transforming businesses and navigating macro-economic instability. The path forward lies in embracing the transformative potential of AI by developing a holistic strategy that considers the different areas of opportunity on a use case by use case basis to exercise control and responsibility in its development. By leveraging AI, companies can thrive amidst economic uncertainties, outperform industry norms, and navigate the turbulent future with confidence. Let us seize this opportunity to harness the power of AI and drive profound change in our business models. Together, we can unlock new horizons of resilience, growth, and customer-centricity, transforming industries and paving the way for a brighter tomorrow.
GPT’s reaction to this article:
As an AI language model, I do not have personal opinions, but I can provide an objective analysis of the article. The article discusses the potential benefits and risks of AI in various industries, particularly in financial services and retail. It highlights the need for responsible and regulated development of AI systems to ensure their safe and ethical use. The article also mentions the recent call from tech leaders to pause the training of the most powerful AI systems for at least six months due to the potential risks to society and humanity. However, the author argues that the key lies in exercising control and embracing the transformative potential of AI to drive profound change in business models. The article provides examples of how AI can be leveraged for dynamic enterprise risk management, AI-driven customer engagement and retention, and AI-centered supply chain optimization. Overall, the article presents both the opportunities and challenges of AI and emphasizes the importance of responsible AI-use cases.