Where to focus when lending is up (but this also applies to criminal matters)
By Roger Lang, Principal Product Marketing Consultant, SAS
The banks are focusing on lending and the loan volume is back to pre-crisis levels. But violations are on the rise and credit portfolio management needs to improve.
With a resurgence in lending banks, they are back to levels not seen since 2008. BREXIT, Italy’s exciting banks, Asian and European credit challenges, and an unstable market structure are all indications that banks need to improve credit portfolio management or they will be back into the soup.
In Bank of America’s 2015 Annual Report, Chairman and CEO Brian Moynihan described growth in several areas:
- Core loans balance $ 75 billion.
- $ 10.7 billion in new credit for small businesses.
- Millions of new credit cards.
- $ 70 billion in home loans.
This return to the core strategy is also repeated in Europe, but increased lending has, however, been accompanied by a rising interest rate in the number of criminal commercial and industrial loans. In his September 2016 issue Bold Dashboard & Fundamentals financial report, Brian Barnier of ValueBridge Advisors observed criminal conditions in 2Q2016 was 1.6 percent, up from 0.6 percent in 1Q2015, while in Europe, criminal terms for commercial and industrial loans are also at historic highs.
As noted by Gabriel David, Senior Director, BurntOak Capital Ltd. (an advisor to central banks), criminal matters are partly related to the current increase in loan volumes and may also be linked to external factors in the economy and financial markets such as historically impaired assets and systemic financial problems.
While higher crime rates are caused by factors that banks either expected or could not have foreseen, it is clear that the rise in lending has been accompanied by rising crime rates.
Implications for managing the credit portfolio
With increased focus on lending core business and a continued rise in criminal conditions, banks need better credit risk management processes and analyzes. They need insurance, decision-making and workflow analytics to optimize and manage the origin and treatment of loans. For loans that become delinquent, banks need better models to project potential losses and determine how best to allocate collection resources. Currently, a number of middle and back-office processes associated with credit portfolio management – from data collection to using spreadsheets to analytics – are time-consuming, expensive and difficult to scale to accommodate rising loan volumes. In addition to these manual processes, there is a significant additional expense to meet regulatory requirements. Therefore, the process of managing risks in credit portfolios must be streamlined and highly automated to remove as many costs as possible from each step.
Each solution to this challenge will have three main components:
- Ability to gather data and support decision making across business areas and geographies.
- A credit model risk management platform.
- Ability to run multiple stress tests as needed.
Credit risk managers need to take a business view on risk across their portfolios, and they need information to support credit decision making. To achieve this, they must collect and analyze data across business areas and geographies. Detailed data resident in each region and line of business must be made available at the enterprise level to obtain a business perception of risk and optimize the allocation of capital across the balance sheet. In an environment of increasing risk and pressure on margins, credit risk professionals must automate the workflow and streamline management of much larger data sets for analysis and reporting.
Model risk management
Credit risk modeling across the loan portfolio – from commercial to small and medium-sized businesses and mortgages – is starting to look more like the evolving credit score scoring techniques. This involves the use of more complex scenario-based models that analyze large sets of both traditional and unstructured data.
Credit risk modeling must be integrated into automated and streamlined workflows from credit origins to analysis, reporting, service and collection. Modeling automation also serves to reduce costly and manually intensive processes.
As models become more, more complex and extend across the enterprise, model inventory management must be automated and centrally managed. Model governance is more than just setting lines in defense and oversight. It includes software assurance and tuning throughout the model lifecycle. In addition to meeting the critical business need for a well-organized credit modeling process, model governance is also a regulatory requirement with specific guidance that is subject to review (by the Federal Reserve under SR 11-7 and increasingly considered a best practice by banking regulatory authorities in other parts of the world including the EU).
A key business benefit of streamlined systems and model automation includes the ability to run more timely stress tests, enabling management to respond to near-real-time events and address new risks as soon as they are identified. In their 2015 JPMorgan Chase Annual Report, CEO Jamie Dimon described the opportunity to run thousands of stress tests as a key feature linked to improved capital returns and balance immunization.
A path ahead
Credit portfolio managers generally agree that they are unable to implement the procedures, controls and credit models they need to manage cost effectively across different silos without the right tools. The amount of data to be analyzed has increased exponentially. Advances in software and technology, coupled with improved credit risk analysis, offer the tools that credit portfolio managers need to analyze large, detailed data sets from traditional and unstructured data sources. With this capability, they will be better positioned to tackle the rising risk of default as banks refocus their lending strategy and increase the size of their loan portfolios.
The way forward for credit portfolio managers is a continuous improvement in streamlining costs, reducing risk and optimizing capital allocation. It is the only way to maintain profitability in an increasingly regulated environment.