Modernize Risk Modeling in the Cloud

In today’s rapidly evolving financial landscape, firms are confronted with a slew of challenges that test their resilience and adaptability. The intersection of economic volatility, political uncertainty, cultural shifts, and public health crises has created an unprecedented environment for financial services. It’s within this context that the imperative for substantial advancements in risk modeling at financial institutions has emerged, especially the potential benefits of migrating these critical processes to cloud-based platforms.

Modernizing risk modeling processes is not just a luxury but a necessity for firms of all sizes. This necessity stems from the need to remain competitive and efficient in a market that values agility and foresight.

The Challenges of Traditional Model Development

A revealing case study can be drawn from a Tier 1 bank that embarked on developing risk models for its mortgage business. The process, far from being streamlined, was characterized by a reliance on our product for model development and a grid system for deployment. This approach, while seemingly robust, was fraught with inefficiencies. Developers were tasked with manually segmenting data for parallel processing, leading to significant disparities in efficiency. The grid, burdened by supporting multiple processes—including production—suffered from availability constraints and performance slowdowns. Further compounding these challenges was the manual documentation process, which was both time-consuming and prone to errors. The workflow culminated in a cumbersome transition phase where approved models, delivered via email, had to be recoded into C++ by a separate deployment team, followed by an exhaustive testing phase. The entire cycle was marked by delays, highlighting a glaring need for a more agile and efficient approach.

The Initial Steps Towards Modernization

Despite these challenges, the journey towards modernizing the model life cycle has only just begun for many firms. Our experiences across various global projects have revealed a persistent reliance on outdated technologies and operational models characterized by manual operations, a lack of repeatability, and protracted cycle times. However, the recent shift towards cloud-based solutions signifies a pivotal first step towards addressing these shortcomings. The transition to the cloud is more than a mere relocation of code; it necessitates a comprehensive reevaluation of how data and models are managed and utilized.

Envisioning a Cloud-Based Future

The cloud represents a paradigm shift in computing, offering a suite of servers and management protocols that promise scalability, robustness, and failover capabilities. However, a truly modern cloud architecture goes beyond these basics, offering a framework for automating numerous activities across the model life cycle. This architecture is underpinned by containers and container orchestration tools that facilitate seamless updates, microservices that provide essential functionality for both technical and analytical operations, and an API-driven development approach that ensures data integrity and accessibility. Such a framework lays the groundwork for a more integrated and efficient model development process.

Embracing a New Paradigm in Model Development

The adoption of this modern development paradigm is exemplified by a leading bank, which has committed significant resources to support this transition. The bank’s approach allows model developers to utilize templates with adjustable parameters, facilitating a more streamlined and standardized development process. This not only reduces the reliance on specialized coding skills but also enables the automation of model documentation, thereby enhancing efficiency and collaboration across the organization. Models are stored in a common repository, accessible as microservices for various purposes, including validation and real-time decisioning. With data and results available via API, the process eliminates redundant tasks, marking a significant leap forward in model development and deployment.

The move towards modernizing risk modeling processes, with a focus on cloud-based solutions, is not merely a trend but a strategic imperative for financial services firms. By embracing this new paradigm, institutions can achieve greater agility, efficiency, and resilience, positioning themselves to navigate the complexities of the current and future financial landscapes successfully.

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