Risk Dynamics provides solutions across credit risk models, digital process design, and regulatory adherence

Our 150-plus experts have hands-on expertise in credit risk model development and validation, embedding cutting-edge tools into digital workflows, and ensuring the tools work seamlessly across underwriting, model development, and maintenance.

What do we do?

We work with global and regional banks, serving the full spectrum of client needs. This ranges from short interventions like Covid-19 model overlays and rapid model diagnostics and benchmarks, to end-to-end transformations, emphasizing capability building and agile digital implementation. We have developed extensive credit engine blueprints and model development workbenches, allowing us to work rapidly with client teams to create customized solutions.

02.Credit_Risk_01 (1)
02.Credit_Risk_02 (1)

Our impact

We significantly reduce time to market, create major efficiency gains, and often boost revenue, while reducing the cost of risk management. Some examples:
  •  A 50 percent reduction in time for model development and implementation by introducing an agile approach
  • A 30-50 percent reduction in operating costs through shorter handling times, and by shifting to self-serve digital channels
  • A 150-basis point reduction in default rates by significantly improving impairment rates

Case studies

  • Streamlining the model landscape to reduce costs and improve agility

    We worked with a global bank on its internal ratings-based (IRB) approach to credit risk, developing high-performing, capital-efficient models with minimal increases in risk-weighted assets (RWAs) from new regulations.

    In the process, we streamlined the model landscape - achieving more comprehensive coverage, avoiding unnecessary complexity, and significantly increasing standardization of the model development and maintenance process.

    This created five areas of impact:

    • Lowered investment and maintenance costs through an optimized plan for global A-IRB models, including more than 20 redevelopments -- saving more than 60 FTE years vs. initial plans
    • Improved organizational agility through a 50 percent reduction in the model development lifecycle (including data & validation)Transformed an expected increase in RWA into a net reduction by placing a “capital lens” on model design decisions
    • Systematically captured new value through a higher level of control and consistency, thanks to central steering and pooled resources
    • Improved credibility and relations with regulators through timely and high-quality delivery and planning clarity

  • Transforming the lending value chain

    We worked with a leading regional bank to transform its credit value chain for retail mortgages and lending to a wide range of small- and medium-sized businesses. The effort spanned four countries and included existing and new customers.

    We focused on creating a customer-centric journey, with fast credit decisions thanks to an automated decision engine. Our work also featured rapid development of the front end, and a scalable micro-services middle layer with more than 20 back-end integrations. And we created a state-of-the-art credit engine with a scalable and powerful credit analytics platform.

    The impact across this effort included:

    • A 30-to-50 percent reduction in the required handling capacity of finance and credit officers
    • Reduced front office time necessary to support loan applications, from 7 hours to 30 minutes per application
    • Reduced number of screens required to complete an application from 60 to 5
    • Reduced default rates through higher credit quality from better decision models
    • Increased revenue from lower leakage in the credit application process
    • Improved self-service through faster processes
    • Improved cross- and up-selling
Copyright © 2024 Risk Dynamics, a McKinsey company