GDS Link offers effective solutions to help companies increase revenue by automating and streamlining their recovery process.
The COVID-19 pandemic has shown us that after the 2008 financial crisis, institutions, creditors and lenders learnt a valuable lesson: pay more attention to collections management. Ever since, they have been gradually incorporating new analysis tools to improve their processes. One of the most devastating impacts of the current health crisis is the financial uncertainty, and this itself has had catastrophic consequences; many households which were previously financially stable are now vulnerable and having to take measures to cope with debt. Many industries and businesses have also been seriously hit by the circumstances and, with closures and confinements, have also had to take on more debt.
According to GDS Link, “There is increasingly more pressure on organizations to recover unpaid debt and address growing default rates in increasingly squeezed markets. Currently, many institutions have chosen to be more flexible with their default policies and have agreed on measures to alleviate the financial burden placed on families and businesses by the pandemic. As a result, they have carefully scrutinized their strategies and processes and applied specific approaches to differentiate between ‘COVID debtors’ and the rest.”
Debt is not an isolated phenomenon but is closely related to market and economic conditions, processes and potential risks. Meanwhile, collections are vital for those financial institutions that are trying to lead the sector, be more effective and continue to grow. A positive collections process guarantees customer recovery and greatly boosts repeat business, and it has been proven that each interaction with a customer is an opportunity to strengthen that relationship if it is done correctly. According to a report produced by Deloitte entitled “Collections Trends Portfolio Recovery in the Financial Sector after the Crisis,” technology is key for ensuring an effective collections system, with advanced analytics, numerous data sources and learning algorithms all helping to find the signs and patterns that identify customers at risk.
One example is the Modellica Collections Suite, a highly configurable GDS Link solution that caters for a wide range of collections requirements. At each stage of the credit life cycle, it applies the appropriate response to restore payments and prevent defaults. It does this by using powerful segmentation, communication and decision strategies that use predictive analysis, models and scoring to prioritize recovery efforts. Furthermore, GDS Link makes it possible for institutions to reinvent the origination process by combining a set of analytical functions and market-leading technology in a unique and powerful framework. Process management and strong decisions bring together the necessary data, analysis, decisions and execution to maximize the value of the customer relationship.
Ultimately, COVID-19 is driving the digital transformation of collections systems towards effective solutions, and with an efficient collections tool like Modellica Collections Suite, organizations and institutions will be able to improve their results with a more advanced, targeted approach. The better and more complete the customer profile, the easier it will be to precisely identify the most valuable customers or those likely to become valuable customers. It also enables powerful segmentation campaigns without losing sight of the principles of cautious risk management, applying analytics and decision models to all operational decisions. According to GDS Link, by implementing more advanced credit line management strategies, financial and credit institutions will be able to increase profits by growing their best customers’ purchasing power whilst limiting the exposure of those that have greater risk. Furthermore, credit institutions can carry out real-time, on-demand credit increases, improving revenue and customer satisfaction by minimizing the number of manual operations at the point of sale.
