Commercial Lending Credit Risk Management: Business and Risk Technology Practices
Within an environment of heightened economic uncertainty, lending practices at most banks have changed. As we face a more perilous risk environment, firms are adopting conventional ‘defensive’ measures such as tightening lending standards, scrutinising approvals more closely, and mobilising workout departments’ ability to manage deteriorating credit conditions.
In Celent’s recent survey of commercial banks, we uncovered insights on commercial lending credit risk management practices, as well as how technology is managed and deployed. Here, the study covers the state of risk technology management practices in four important areas:
These areas, in many ways, are foundational competencies that enable firms to build out more advanced capabilities related to both credit risk and loan processing functions. However, in meager times, as firms tighten their belts, the challenge often lies in discerning incremental improvements to hone and guide critical capabilities – for instance, around collateralisation, company-wide credit exposure reporting/ monitoring, ‘balanced’ early warning mechanisms, and workout effectiveness – such that the efficacy of these capabilities are high.
In general, the business case and requirements for front office workflow have increased as institutions streamline their commercial lending operations, effectively unbundling the lending value chain towards a higher degree of specialisation (e.g. separating client-facing/sales from non-sales and servicing related activities), centralisation of underwriting, standardisation of procedures for various type of commercial loans, and streamlining decisioning and approvals.
For many of the surveyed firms, workflow was regarded as lower priority given perceived execution complexity and pace of change in the market:
Forward thinking firms embrace intelligent optimisation of workflow rather than full integration to strengthen linkages between systems.
The decision to achieve a balanced integration in relation to front office workflow needs to be achieved with a broad understanding of current workflow across product groups and where value is derived within certain parts of the workflow chain. Specific parts of the chain may include managing leads, RFP/proposal development, evaluation of loan proposal, and syndicated lending processes.
Here, each business process represent different value accrue to an organisation, depending on current system architectures, product set/process complexity, pipeline of business, and nature of the bank’s value chain activity. For example, if a firm participates heavily in loan syndications (whether as a lead or assignee), the ‘supply chain’ complexity of product and workflow with internal stakeholders (e.g., legal, risk) and external participants increases and hence should be given more emphasis.
Overall, while full integration is not necessary to achieve efficiency, intelligent optimisation of workflow can strengthen linkages between systems.
A robust universal customer identifier (UCI)/obligor hierarchy is obviously critical to building out customer centricity and CRM capabilities. While this is not a new topic, consistently differentiated customer relationship management services is a domain that is, more often than not, littered with less than successful implementation stories.
Advancing current UCI as key to understanding portfolio exposures across multiple dimensions (e.g., obligor, parent, customer, partners).
Accomplished firms report success with agile development (in other words prototyping) approaches to address the needs of risk management technology development needs.
To achieve success, the processes behind the data matter – consistency, auditability, and transparency – are paramount. However, the challenges associated with delivering to these requirements grow exponentially with the number of information capture points, data owners, and divisions sharing customer information, as well as the scope of usage. With the latter point for example, the scope of use beyond risk management may include client intelligence (e.g. micro segmentation, customer profitability analytics), opportunity prospecting, client servicing and collaboration, and legal/compliance handling (e.g. anti-money laundering).
One point to note is that UCI data initiatives of this sort usually require successive cycles of iteration in order to achieve results – ‘not glamorous’ from an IT perspective. They also require prolonged buy-in from business stakeholders willing to take a medium-term perspective on when real paybacks would be fully realised (e.g. three to five years). A cautionary note needs to be raised, particularly around this area of UCI data. We are aware of more anecdotal failures than successes. Based on Celent observations and estimates, less than 20% of cross-business unit efforts are successful.
The increasing proliferation of collateral volumes and asset types pledged has raised the profile of this often ad hoc, back office function. Needless to say, the turmoil associated the recent credit crisis has put collateral management practices to the test and revealed gaps associated with the way collateral information is captured, consolidated, and processed across the collateralisation lifecycle.
Collateral data highlighted identified as key to proper risk measurement (e.g. LGD, portfolio stress testing with good progress made to date among most survey participants).
Collateral management is most likely prone to being ‘left behind’, given the rapid pace of change in collateral types (e.g. commercial real estate, evolving subordination levels). Collateral classification is key to ensuring inherent risks understood and recover rates optimised and firms should consider developing a ‘prototype’ outside the existing infrastructure to minimise disruption and test.
Collateral management systems are already playing a key role in providing transparency into the underlying loan quality, and this is especially relevant in today’s credit markets. But challenges don’t lie in defining what needs to be achieved, or its benefits – they lie in being able to develop an approach to execute effectively despite changing requirements, the complexity of data migration, asset class coverage, and fragmented collateralisation processes/tools.
Loss data management sits typically in desktops, Excel spreadsheets, Access databases, bespoke applications, and similar tools that are developed in-house. These in-house development approaches in workout functions so often result in information being highly parochial, for which the sharing of data is limited and advanced analysis close to impossible.
Loss data results showed the biggest gap to leading practices, currently structured to support work out efforts versus strengthening credit risk management capabilities. They were not identified as a leading priority for survey participants and solutions were generally standalone, usually developed internally.
Leading practice solutions identified also tended to be internally developed. Improving loss data capture is invaluable to supporting advanced credit risk management capabilities (e.g. LGD calibration, stress testing and portfolio modeling):
Given recent market pressures, optimising loss represents a particular opportunity to develop a competitive advantage and strengthen risk management capabilities. Having high quality loss data is foundational not only to LGD estimation but also to other risk management practices such as pricing and portfolio management.
As firms head into a tougher economic environment, commercial lending institutions will need to be more disciplined and streamlined in the way technology enables lending operations. Risk management functions, especially, need to be geared up to manage deteriorating credit conditions, enable positive customer selection efforts, and improve and retain a targeted level of profitability.
The insights and conclusions in our survey indicate that the range of capabilities in the integration of credit risk data and applications need to be diverse. Forward-thinking institutions have built out these capabilities to be able to meaningfully uncover actionable insights to give senior executives and business planners sufficient information to make sound credit policy and strategy decisions, or line managers and operations personnel the information they need to manage their day-to-day activities effectively within the credit cycle.
Any wholesale change in strategy is obviously not an appropriate response to the sluggish economic conditions and a heightened risk environment. However, strengthening a handle on risk and pricing, honing precision in prospect selection and selling efforts, and improving execution efficiencies in sales and back office operations will pay dividends and pave the way through an increasingly harsh business terrain. Indeed, for the long haul, banks need to revisit the more profound question of what it means for commercial lending to be profitable in its own right without relying on cross-subsidies from other products. All these will separate leading institutions – those that have the capability to take advantage of opportunities in a more volatile environment – from firms that are merely on the defensive.
Excerpts from this article were taken from the Celent report titled ‘Commercial Lending Credit Risk Management: Surveying Business and Risk Technology Practices’. Based on global surveys of more than 20 commercial lending institutions in North America, Europe and Asia, this report highlights ongoing risk IT pain points faced by firms, the spectrum of industry practices and geographical nuances, as well as delivering insights into best practice approaches and considerations for investing in, and building out risk technology management capabilities.