Implementing digital infrastructure, strategies, and frameworks has never been more important for banks. The pace of technological disruption was supercharged by the pandemic, and there is now an even greater push to become digitally resilient to remain competitive. Credit and risk management teams are no exception. From dynamic financial spreading tools to cloud-based storage, a host of capabilities are being actively deployed to help streamline and automate risk assessment processes to improve efficiencies and stay ahead of the curve.
Our recent report, “Digitization in Credit Risk Management" summarizes insights we gathered from over 200 professionals in countries around the world to see what steps they were taking before the COVID-19 pandemic took hold, and how this unprecedented time has accelerated change. It is clear that the surge of bankruptcies taxed traditional credit risk management workflows, causing many to look for alternative sources of data, new analytical approaches, and more dynamic reporting to stay on top of deteriorating credit conditions.
Many Benefits of Digitization
A full three quarters (75%) of respondents to our survey were already working on digitization efforts before the pandemic hit to capitalize on a range of benefits. A large number (71%) indicated that digitization provides for better risk control and management to protect organizational profitability, while 62% mentioned improved efficiencies and 59% pointed to having better early-warning systems in place.
Having lived through a crisis situation, 64% of respondents now see the importance of developing more automated and dynamic reports for executive decision-making. It has become clear that creditworthiness not only differs by sector and sub-sector, but also within these categories, requiring more detailed monitoring. In addition, a range of new risks related to environmental, social, and governance (ESG) issues and additional regulations must now be taken into account.
Off-the Shelf Automation via Desktop Solutions
Many automation tools have been in play for a long time on desktop solutions, helping credit and risk management professionals stay on top of breaking news and minimize time spent on repetitive tasks. At S&P Global Market Intelligence, for example, this includes:
Alerts to help monitor counterparties: Saved portfolio lists can be shared across teams and automatically trigger alerts to news, filings, key developments, and regulatory updates that are sent directly to a user’s inbox or mobile app.
Custom templates to save time: Using bespoke templates built for specific workflows, industries, and companies eliminates the need to replicate tasks, and also enforces consistency every time the analysis is done.
Microsoft Excel® Plugins to increase functionality: Plugins provide an excellent way to increase the capabilities of Excel for custom tasks and are ideal for distributing user-defined worksheet functions. Users can create refreshable models, access pre-built templates, do Excel screening, and more — all with a one-click refresh.
Multiple sector classifications and business criteria to screen, assemble, and monitor entities: This makes it easy to tie together a variety of company-level information, such as transactions, transcripts, estimates, fundamental data, and more.
Data tracing to link back to original sources: Tracing capabilities automatically link individual data items to their source documents. This lets users see any adjustments that may have been made to standardize concepts for comparison purposes.
Dashboards to instantaneously tell a story about the data. Users can track performance, market data, press releases, filings, and events in one centralized location with customized viewing of graphs, charts, and reports.
Many more capabilities continue to be added to desktop platforms to further streamline workflows and increase efficiencies. At the same time, there are additional capabilities available today that help bring bank data together with external data to drive a host of proprietary applications that are housed within a bank.
Driving Internal Applications with Data that is Reliable, Consistent, and Unique
Data is obviously a critical asset for businesses trying to uncover important insights that can provide a competitive edge. Incredible changes have taken place, however, in terms of the volume of data that is available and the speed at which it needs to be processed. This has brought many new capabilities to the forefront to quickly cleanse, link, spread, and deliver data for a wide range of build-it-yourself bank applications in the credit risk function. For example, there are:
Cleansing capabilities to improve data accuracy: Company data held internally can often be messy, having incomplete company names, spelling errors, and the use of aliases and abbreviations. Now Kensho Link ties each company to S&P Global Capital IQ IDs, reducing manual processes and integrating more data in less time.
Cross reference services to link disparate data: Extensive reference data can quickly link companies, sectors, and instruments, enabling users to better manage their data integration and minimize manual processes.
Tools to easily spread data: Newer capabilities automatically extract and spread relevant data from PDF financial statements by leveraging Natural Language Processing (NLP) combined with Optical Character Recognition.
Flexible data delivery options to support internal data warehousing: Robust data feeds, APIs, and cloud-based storage are being actively used to address the volume and speed concerns head on. Whether through file transfer protocol (FTP), or cloud-based and API solutions, data can be seamlessly delivered to a centralized bank database, as well as to dashboards/visualization tools, models, and more.
Machine readable textual data to assess sentiment in transcripts: NLP can be applied to corporate earnings call transcripts to dissect the tone, complexity, and overall level of engagement with analysts, as indicators of earnings sentiment. There is also an ability to sync with events data via a feed or by streaming XML messages for details on calls scheduled for transcription.
When asked how third-party providers could enhance their credit risk management offerings to address some of the challenges around digitization, many answers were given by respondents to our survey. Almost two thirds (63%) said they are interested in predictive analytics or insights, while 58% would like to see advanced analytics for early-warning systems. To meet growing demands, third-party providers are taking their risk management capabilities to new levels, and considering where investments are most important.
Click here to learn more about how we are working with banks to help automate the credit risk management process.
 Over 40% of respondents were from commercial banks and other financial institutions.
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