How Moody’s is leveraging adaptive AI

London Tech Week, an annual tech gathering in central London, unites global tech visionaries to explore technology’s impact on our digital future. As proud Platinum sponsors, we enjoyed our very own Jonathan Whiteside, Global SVP of Engineering, taking the stage alongside Nick Zylik, Managing Director of Product Strategy at Moody’s Analytics, to discuss how the financial industry is leveraging adaptive AI.

Moody’s is an integrated risk assessment firm that helps clients understand, assess, monitor, and report risk exposures across various portfolios and partnerships. Leveraging an unrivalled set of data analytics and domain expertise, Moody’s empowers businesses to make well-informed decisions. 

In this fireside chat, we explore how Moody’s combines their extensive data resources and expertise with the power of AI and machine learning to build innovative products and services. We’ll also discuss their approach to maintaining trust and ensuring the quality of insights while embracing AI-driven solutions. We’ve also listed the top takeaways below. 

Over the years, big tech companies have invested billions in AI and machine learning capabilities. With recent advancements in AI, these capabilities are now available to businesses of all sizes. Moody’s, already equipped with vast data resources and a mature data-focused approach, aims to integrate AI into their products and services.

Moody’s possesses a considerable advantage with its in-house data, including credit ratings, credit data, research, climate, and ESG data. The firm is now focused on leveraging this data in a rapidly evolving consumption landscape. They aim to deliver valuable insights to clients faster, make sense of complex data, and provide additional valuable connections within the data.

Here’s how: 

Prioritise trust and data security
As a firm with a voice of authority in the marketplace, Moody’s prioritises trust and reliability in their AI-driven insights. They understand the importance of data quality and validation to ensure the accuracy and credibility of the outputs from AI models. Data security remains a top concern, and they maintain the principles used to safeguard proprietary data in the AI world.

Manage risk and build new skills
Given their core function of managing risk for clients, Moody’s applies similar risk management principles when embracing AI. They acknowledge the importance of scale and the challenge of aligning resources to deliver AI solutions effectively. To succeed, the company recognises the need for new team roles and capabilities.

Democratise AI ideation
At Moody’s, a culture of advocacy for investing in AI exists at the leadership level. They encourage a bottom-up approach to ideation, allowing individuals closest to clients’ challenges to propose innovative solutions. However, they emphasise centralisation to ensure coherence and prevent redundant efforts.

Making informed investment decisions
Moody’s focuses on investing in AI solutions that offer real value to customers. They consider both short-term efficiency gains and long-term revenue opportunities. Decisions are driven by carefully evaluating customer benefits, data implications, and time-to-market.

Validating AI insights
Ensuring the quality of AI-generated insights is vital. Moody’s strives for continuous improvement, testing, and validating various AI models to deliver their clients the most accurate and valuable outputs.