We help financial institutions manage risk along the entire credit value chain, addressing challenges and opportunities related to origination and underwriting, credit portfolio management, loss mitigation, and credit modeling and advanced analytics.
Managing credit risk is always a complex challenge—one that becomes even more complex against a backdrop of market volatility and evolving regulatory guidelines. We help clients maximize returns from their credit operations by applying our expertise in:
Credit strategy, organization, and portfolio management
At an average commercial bank, credit-related assets produce about 40 percent of total revenues; credit-related costs, including provisions and write-offs, account for a significant fraction of expenses. We help clients increase revenue and minimize costs by supporting the development of sound credit-risk strategies, organizational structures, and portfolio-management processes. Our recent projects have included:
- helping a client define its risk appetite for large-corporate credit underwriting
- devising decision criteria to yield profitable growth in a client’s consumer-lending business
- transforming portfolio-level credit guidelines into actionable loan policy
- optimizing the design of a bank’s credit-portfolio-management unit
Well-designed credit processes can reduce operating expenses by 15 to 20 percent and risk costs by more than 20 percent, while improving customer experience. We have extensive expertise in optimizing credit processes (origination, underwriting, pricing, administration, monitoring, and management) across all customer segments. Our approach combines a deep understanding of business and credit-related issues with proven lean techniques. Examples of our process-optimization work include:
- helping a commercial bank with an end-to-end redesign of credit processes for the retail, small and medium enterprise (SME), and corporate segments
- developing best-practice capabilities for SME underwriting by improving processes and creating advanced statistical models
Financial institutions must proactively manage potential credit losses to sustain value, especially during volatile economic periods. We help clients design and implement effective strategies for every stage of the collection process, from early delinquency to work-out. When necessary, we also create targeted approaches for asset disposal. Our projects typically reduce the cost of risk by 10 to 20 percent. Recent projects have included:
- introducing behavioral segmentation and developing differentiated recovery strategies to maximize recoveries on retail and commercial loans
- “ring-fencing,” evaluating, and preparing the sale of large nonperforming loan (NPL) portfolios
Advanced analytics for credit
Banks increasingly require deep analytical insights to understand the value and risks associated with their credit portfolio, as well as to respond to market fluctuations and regulatory requests (for example, stress testing and capital management). We have more than 40 analytical experts in Europe and Asia dedicated to helping clients develop specialized models that can be applied either to individual loans, portfolios of assets, or a bank as a whole.
Among other projects, we have helped retail banks create behavioral models to drive credit underwriting and monitoring. We have also developed asset-specific models to assess the value of specific portfolios under different scenarios.
Credit surveys and benchmarks
Our clients can participate anonymously in a wide range of surveys covering all major aspects of credit risk, including organizational effectiveness, credit processes, risk model performance, and portfolio management. These surveys allow clients to benchmark their performance against a group of relevant peers.
Credit diagnostic. The credit diagnostic benchmarks the quality of end-to-end credit processes (including risk selection and customer excellence) as well as their operational efficiency, against that of peers. It helps identify key areas for optimization and serves as a starting point for defining specific improvement levers.