Written by Ronald Poon I 4 min read
TL;DR — Key Takeaways:
- Embrace AI for Risk: Companies like Deutsche Bank and Marqeta (an innovative FinTech company) are using AI to revolutionize risk management.
- Prioritize AI-Driven Customer Experience: Firms like BMO and JP Morgan Chase are setting new customer satisfaction standards through AI.
- Invest in AI for Sustainable Profit: Initiatives like HSBC's ESG Risk Improvers Index show that sustainability and profitability can coexist.
A New Transformative Era in the Financial Services Industry
The financial sector stands on the brink of a transformative era, fueled by Artificial Intelligence (AI). With AI applications promising an estimated $447 billion in cost savings for banks globally, the time to act and learn as much as possible about this emerging technology is now.
Three Major Benefits of AI in the Financial Services Industry:
- Precision and Accuracy: AI algorithms can sift through vast datasets to make highly accurate predictions and decisions, reducing errors.
- Operational Efficiency: Automation of routine tasks frees up human resources for more complex tasks, thereby increasing efficiency.
- Hyperpersonalized Customer Service: AI-driven chatbots and personalized service recommendations can greatly enhance customer satisfaction.
The urgency for prototyping and experimenting in this domain is clear to a lot of directors and senior leaders. Early adopters will capitalize on this transformative wave, setting new standards within the financial services industry.
1. Risk Management with AI (Deutsche Bank and Marqeta)
Financial risk management AI is revolutionizing how banks assess and mitigate risks, a transformation that is evident across both traditional banking institutions and FinTech innovators. Traditional methods have been labor-intensive and less accurate, but AI can process vast amounts of data in a fraction of the time. Deutsche Bank, in collaboration with NVIDIA, is pioneering this space with their "Financial Transformers," AI models that not only identify early warning signs related to financial transactions but also expedite data retrieval and highlight data quality issues.
In the FinTech arena, Marqeta is making strides with its purpose-built tools designed to mitigate risk across the cardholder journey. Their Real-Time Decisioning tool allows for the development, testing, and execution of highly customizable rules based on hundreds of data attributes, including card network risk scores, for every card transaction. This not only improves the cardholder experience by blocking potentially fraudulent transactions but also minimizes false positives, thereby delighting risk operations teams.
Both Deutsche Bank and Marqeta's initiatives represent monumental leaps in proactively managing risks and ensuring financial stability. They showcase the transformative power of AI and purpose-built solutions in reshaping the landscape of financial risk management.
2. AI-Driven Fraud Prevention (JP Morgan Chase)
Fraud is a persistent thorn in the financial sector, especially credit card fraud, which has surged due to the rise in e-commerce. JP Morgan Chase's OmniAI platform is a robust solution that employs AI to analyze clients' behavior, location, and buying habits. When an anomaly is detected, a security mechanism is triggered, thereby preventing potential fraud. The platform also uses synthetic data to train its models, overcoming the challenge of data privacy and availability. This is a prime example of how AI-driven fraud prevention can be both effective and efficient for large banks like JP Morgan Chase.
3. Hyperpersonalized Customer Service (BMO)
The digital age has raised customer expectations for personalized services. BMO Financial is meeting this demand head-on by using AI to deliver personalized banking insights. Their AI-driven platform offers features like "Where You Spend" and "Spending Category" Mini-Quizzes, providing customers with valuable insights into their spending behavior. As Mathew Mehrotra, Chief Digital Officer at BMO, so aptly puts it, these insights are designed to help customers make "real financial progress” by meeting customers where they are, and providing automated, bite-sized insights that feel like they were made and “meant for the customer alone”.
4. Revolutionizing Trading and Investments (BlackRock and The GPT Portfolio)
AI in trading and investments is not just about speed; it's about precision and foresight. BlackRock's Aladdin platform is a testament to this. It uses AI to analyze both structured and unstructured data, providing investment managers with actionable insights. The platform generated $1.1 billion in revenue in 2020, setting a new industry standard. The key has been the ability to build incredibly precise and complex pricing models for almost any asset with historical data.
In other exciting developments, emerging experiments (such as “The GPT Portfolio” on Twitter) are showcasing the democratizing potential of AI in trading. Managed entirely by AI algorithms, this portfolio has shown promising results, particularly in trading the SPY ETF (The SPDR S&P 500 ETF Trust). These real-world tests offer intriguing insights into the potential of AI to make trading more accessible and potentially more profitable for the average person. While still in the experimental stage, the early results are compelling enough to capture the attention of industry leaders and warrant further exploration.
This multifaceted discussion not only highlights the achievements of established players like BlackRock, but also brings attention to innovative grassroots alternatives, making the discussion around AI in trading and investments all the more far-reaching and engaging.
5. Process Automation and Efficiency (Citibank)
Robotic process automation (RPA) in finance is the gateway to digital transformation. Citibank is leveraging AI to automate cash application processes, which traditionally required significant human intervention. This automation reduces errors, lowers operating costs, and allows for the reallocation of human resources to more strategic tasks. Ernst & Young has reported a 50%-70% cost reduction in these kinds of tasks, underscoring the operational efficiency that AI can bring.
6. Decarbonization and Sustainability Through AI (HSBC)
As sustainability becomes a core focus, AI decarbonization strategies are gaining prominence. HSBC's ESG Risk Improvers Index is a groundbreaking initiative that tracks companies expected to benefit financially from ESG improvements. Arabesque AI provides an “ESG momentum score” for each constituent, offering a financial indicator of future performance.
In a similar vein, BMO Financial Group took a proactive approach to sustainability by hosting an internal innovation sprint last year, called Destination Digital. The challenge focused on leveraging AI and advanced machine learning techniques to determine the best decarbonization opportunities for retail and commercial clients. This initiative not only underscores the importance of AI in driving sustainable practices but also serves as an example for other financial institutions to follow.
By incorporating both large-scale initiatives like HSBC's and targeted efforts like BMO's, this discussion offers a comprehensive view of how AI is shaping the future of sustainability in the financial services industry.
The Future is Now, and It's AI-Driven
The financial services industry is at a watershed moment, teetering on the edge of an AI-driven revolution. The stakes are high, but the rewards are monumental. Companies that seize this moment to invest in AI will not only gain a competitive edge but also become the architects of new industry norms. The key to this transformative journey is not just in adopting AI but in daring to prototype, experiment, and innovate with emerging technologies.
Yet, the road to AI transformation is fraught with complexities and challenges that require specialized expertise. This is where Onova can be your strategic partner. With a proven track record of working with some of the world’s largest banks, such as HSBC and BMO, we specialize in running large-scale generative AI hackathons that fast-track innovation. Our approach is designed to help you identify the most promising AI use cases, rapidly prototype solutions, and implement them at scale, thereby ensuring that you are not just a participant, but a leader in this space.
