How Banks Can More Efficiently Meet the Working Capital Needs of Their Energy Sector Clients
In a world of volatile energy prices and razor-thin margins, energy companies are looking for every edge to reduce costs and time to revenue. This extends not just to their exploration, drilling, trading and other business operations, but to their relationships with their banks. One area that is ripe for improvement is credit originations, where quick, efficient access to working capital has become essential to the energy industry.
Typically, the credit originations process requires a great deal of manual work. When an energy company wants to initiate a credit request, it must spend a lot of time collecting, scanning, emailing and faxing documents to the bank, such as company and executive financial statements, references, tax ID verification, credit scores and D&B reports. The bank then manually re-enters all of this data into its systems before it starts routing the application through the originations and risk decisioning workflow. This ends up an opaque, error-prone process that often takes several weeks to complete, leaving the energy company with little insight into when they will get the money or why the process has stalled.
The experience is even worse for companies like energy marketing and trading firms. These companies not only endure lengthy credit originations for their own business, but must repeat the process for each client with whom they wish to trade. As a result, credit originations has become a bottleneck, thwarting rapid response to highly volatile energy market conditions. Many energy companies now consider a bank’s ability to efficiently process and approve credit requests as mission critical and will terminate relationships with those banks that cannot respond in a timely manner. Obviously, losing clients is not a good thing for the bank, nor is the fact that lengthy processes negatively affect the bank’s time to revenue.
However, there are digitization technologies that banks can leverage to change this experience, turning credit originations into a streamlined, efficient process that can become a business differentiator. These include:
- Using integration adaptors to simplify and speed up data collection
- Operationalizing risk models to enable faster, more accurate risk analytics and decisioning
- Implementing a platform to automate and orchestrate data collection and risk decisioning within the credit originations process
Simplify Data Collection with Automated Data Integration
The biggest hurdle to efficient credit originations lies in the substantial amount of information that must be gathered from multiple systems, such as company data, financial statements and accounts receivable from mainframes, CRM, ERP, financial and document management systems; address verification from web-based services; and anti-money laundering and other KYC information from government databases via third party services.
For energy companies and their servicing banks, automating this complex data capture seems like a great idea, but not if it comes with very high costs for developing and maintaining integrations with all of the required systems. The solution lies in leveraging pre-built integration adaptors that provide easy ways to create both real-time and batch connections between systems. The best adaptors use industry-standard integration methods and provide visual configuration capabilities that eliminate programming. Instead, using familiar visual tools, both IT and business analysts can quickly configure the data elements needed from each system. By leveraging easy-to-implement integration adaptors, banks can automatically consolidate comprehensive company, financial and relationship information from any enterprise or third-party data source, reducing time and costs for data capture.
Improve Efficiency with Operationalized Risk Models
Banks make sizeable investments in their analytics models for credit analysis and risk decisioning. However, because integrating these models into an originations workflow usually requires sophisticated, expensive resources and considerable time, they tend to remain disconnected from the process, slowing down the originations cycle and increasing the likelihood of errors or misjudgments.
Leveraging technology that makes it possible to integrate risk models into an automated workflow-and thus “operationalizing” the model-banks can do away slow, costly programming cycles. In addition, operationalization ensures that risk decisioning is always using the most up-to-date models, improving both compliance and the accuracy of decisions.
Operationalizing a risk model requires the following capabilities:
- Model-agnostic integration technology that supports a wide range of industry-standard models and scorecards, such as SAS, R and Excel models, or models which can be exported using PMML or MathML.
- Visual configuration tools that guide business users through the process of importing a model, mapping and validating the data to be shared between the model and the automated process. Well-designed configuration tools enable a complex model to be operationalized in as little as a day, while changes to an existing model can be implemented in just a few minutes.
Visual configuration tools allow business users to rapidly create the relationship between a
third-party risk model and an automated originations process.
Streamline Originations with an Orchestration Platform
While the individual capabilities of integration adaptors and operationalized risk models can substantially increase the efficiency of credit decisioning, their value is maximized when they function as part of a platform that orchestrates their use within complex processes.
For example, a platform can:
Eliminate manual data gathering by orchestrating capture of specific data elements from multiple systems and automatically verifying that all of the required data has been gathered.
- Provide greater data collection flexibility with support for capturing data in multiple ways including manual data entry, document scanning and automatic uploading from multiple systems.
- Increase accuracy with a complete audit trail that includes change tracking and version control to make sure the most recent financial statements are used.
- Automatically determine quantitative ratings using business-defined rules to apply risk models and scorecards to aggregated financial data.
- Simplify the development of qualitative ratings by dynamically generating appropriate questions based on such factors as financial data and region.
- Efficiently manage risk rating on an on-going basis with visual tools for viewing previous or historical ratings, modifying ratings and re-rating.
Credit originations can become a meaningful differentiator for banks serving the energy industry. Using digitization technologies that focus on reducing the complexity of the originations process, banks can offer energy companies an experience that focuses on meeting the need for rapid access to working capital while ensuring accurate, reliable risk decisioning.