Organizations are making major investments today to harness their massive and rapidly growing quantities of information. They are putting existing data to work that had been trapped in business units and functional silos, and they are managing new types of data coming at them from a wide variety of external sources. They are also building better models with greater predictive power by applying advanced tools and techniques.
These investments are vital to improve risk management for today’s challenging global environment. However, if organizations are going to get maximum value from them, they need to go beyond just the data and models. They need to rethink and fine-tune their strategies, and change their culture and processes.
McKinsey is at the forefront of helping organizations transform risk management through advanced analytics, while supporting broader efforts to maximize risk-adjusted returns. We do so by combining our expertise in risk analytics with deep experience and understanding of our clients’ business context.
What makes us distinctive
Understanding that technical expertise is a prerequisite to success, we have made significant investments to increase our capabilities:
- We have more than 130 professionals who specialize in serving clients on risk advanced analytics. This group not only includes our consultants with deep expertise in analytics, but also a group of over 65 specialized modelers with advanced mathematical degrees across the Americas, Europe and Asia.
- We are evolving our model to deliver impact through analytics. This includes larger team structures that combine the talent of our consultants, modelers and data scientists, and quantitative knowledge experts. Furthermore, in some cases, we link our fees to faster growth, cost reductions and other metrics.
- Risk Dynamics, a McKinsey Company, furthers our ability to help clients create sustainable modelling and analytics platforms in a data-driven world. Our global team develops and deploys leading-edge solutions for clients, incorporating the latest innovation in methodology and technology, while maintaining in-depth knowledge of regulatory requirements.
- We have developed proprietary knowledge and assets, including a digital credit assessment, qualitative credit assessment, sentiment analysis, and quantitative commodity-price scenario analysis.
- We have an exceptional team of external senior advisors as well as partnerships with research and statistical centres, such as the Cambridge Centre for Risk Studies, to offer our clients deeper insights in the field of risk advanced analytics.
We also understand that top-notch technical capabilities like these are not sufficient on their own. Organizations are under constant pressure to deliver greater value to their customers and create sustainable sources of competitive advantage. To help our clients accomplish these goals, we combine our capabilities in risk advanced analytics with a deep understanding of their organizations, and the industries in which they operate, along with expertise in strategy, organizational transformation, and how to make change happen. This combination makes our value proposition unique and powerful.
We know that merely solving the problem at hand isn’t enough, and so we work closely with key employees at all levels to build their core capabilities and refine processes. We help our clients align their “quants,” business-unit personnel, senior executives, and boards on what’s important and how to capitalize on it.
In short, we help our clients turn the promise of risk advanced analytics into impact.
How we help clients
Here are some specific areas where we bring distinctive risk analytics to our clients.
Credit risk modeling and analytics
Advanced credit risk analytics enable institutions to improve underwriting decisions and increase revenues while reducing risk costs. We work across all asset classes, credit risk models, and the entire credit life cycle, including profit maximization, portfolio management, and loss mitigation. We cover a wide variety of sectors, including banking, telecommunications, and government agencies. Our work helps clients address six strategic imperatives:
- Understanding and adapting to changing consumer behavior
- Mining the vast amounts of available data
- Expanding the credit “buy box” without altering the overall risk profile or appetite
- Increasing penetration of the customer base
- Containing credit risk within the portfolio
- Understanding aggregate risk levels in a range of baseline and stress scenarios.
Stress testing and balance-sheet analytics
A structured, well-defined stress-testing process connects the “engine room” to the board room. It goes beyond cumbersome exercises aimed solely at achieving regulatory compliance and moves board members and business leaders to action. Our stress-testing capabilities include generating scenarios, translating them into environmental parameters through macroeconomic quantification, and then assessing the impact of these scenarios on the market, and on the client’s profit and loss (P&L) and balance sheet. All of this informs an action plan to mitigate risks and swiftly capture opportunities.
Operational risk and fraud analytics
We provide advanced operational risk and compliance analytics, protecting clients’ P&L and capital. We support both financial and nonfinancial institutions in solving the most complex analytical problems across all nonfinancial risk types. These risk types include loss and scenario-based models—for setting capital requirements (for example, the advanced management approach and the Solvency II Directive) and for stress testing (for instance, the Comprehensive Capital Analysis and Review in the United States, the Prudential Regulation Authority in the United Kingdom, and the European Banking Authority and the European Central Bank in Europe). We also cover advanced models for operational risk and compliance management, such as anti-money laundering, know-your-customer fraud, and unauthorized behaviors.
Model validation
We support clients on a broad spectrum of model risk-management topics: defining model governance, policies, and procedures, identifying model needs, validating models, and providing the necessary organizational support, capabilities, and culture. Our deep capabilities in advanced analytics allow us to assist clients in model validation across all model classes. With more than 200 experts in data, analytics, model development, and model risk, covering all geographies across the world, Risk Dynamics, a McKinsey Company, brings a combination of deep analytics expertise, industry knowledge, regulatory perspective, and distinctive capabilities in corporate strategy and transformation.
Machine learning
We help clients complement traditional risk analytics with machine learning to find previously unidentified patterns and make better predictions. For example, we use machine learning to improve fraud detection and mitigation, improve underwriting decisions, and optimize collection efforts. Our efforts with a Latin American telecommunications provider enhanced its collections process and identified the 15 percent of customers causing 83 percent of losses.
Institutional-investment analytics
We help institutional investors—particularly large public pension plans, sovereign-wealth funds, and endowments—better understand the risk and return potential of their portfolios. We help clients analyze risk factors, model asset and liability matching, and enhance their asset-allocation methodologies. We also help them disaggregate the sources of investment performance and costs to get a fuller view of their risk-adjusted returns. Increasingly, we help institutional investors use insights from big data and machine learning to stay at the cutting edge of their disciplines. We embed these insights and techniques into ongoing investment and risk-management processes to help clients build lasting capabilities.
Insurance analytics
We help insurers apply big data and advanced analytics to address key issues, such as underwriting and pricing. In doing so, we help optimize new-customer acquisition and maximize economic value from policies to ensure that clients settle claims fairly for customers and shareholders.
