Collections and Client Recovery: An Evolutionary Approach

Collections and Client Recovery: An Evolutionary Approach

Global economic growth has been limited since 2008. The combination of high unemployment rates along with high levels of government debt and overall economic uncertainty has been difficult to overcome, even in some developed economies. Consumer default rates, which tend to be closely related to economic conditions, often grow during economic downturns, adding more pressure on companies profitability. In order to mitigate losses, companies find themselves having to improve their credit and collection practices. In many cases, this means an increase in contact rate which can put more pressure on debtors (clients). Accenture believes that it is possible to differentiate among debtors and to define collection strategies according to debtors profile, thus preserving as much as possible the client relationship. Obtaining repayment of a loan is crucial, but treating clients appropriately may be much more rewarding in terms of future revenue streams. 2

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Maturity Stages in Collections and Client Recovery In our observations and analysis of collection and recovery practices used across industries, we have identified three levels of sophistication in a firm s collection and recovery practices, as outlined in Figure 1 below. Stage I Debt Collection Debt collection is the most basic stage of the collection and recovery cycle. Businesses that find themselves in this stage often use the same collection techniques across the entire portfolio of overdue loans, with little or no effort made to differentiate between different types of clients. Funds collected are often used to replenish the business s cash flow, providing limited or no additional insights that can be used to help improve the sales, credit, billing or cash-to-order processes. Stage II Credit Recovery In debt collection, most companies wind up in the Credit Recovery stage. The main emphasis during this stage is on maximizing collection, and doing so effectively. In the Credit Recovery stage, the strategies used are dependent upon the nature of the client. Collections are not automatically initiated for each overdue bill. Rather, they are undertaken from a client or contract perspective, analyzing a client s and/or contract s pool of overdue bills, taking into account the client s history and potential future revenue stream. In our view, collection can be seen as a lever for driving revenues and objectives are set in terms of desired recovery rates and cost targets set as a percentage of the expected recovered amounts. Stage III Client Recovery This is the most advanced form of collections capabilities, seen in only a few companies. To avoid contract cancellation and possible loss of clients, the collection process is managed from a client s perspective. The goal is to initiate the right actions and make the right offers to clients based upon their risk profile. The use of analytics can help accelerate loan recovery and contributes to the success of negotiations. In our view, avoiding client churn during this stage is very important. In this sense, the effectiveness of the collection process is often measured not only in terms of the credit recovery level but also in terms of the level and quality of the client relationship, client retention and its effect on driving potential future revenues. Figure 1. Evolutionary stages of collection practices Stage I Debt Collection Stage II Credit Recovery Stage III Client Recovery Added Value Sophistication Objective Collect Maximize recovery Monetize the base (keep the good clients) Focus Negotiate debt (agreements) Deplete the portfolio Collect efficiently Treatment aligned to the client s profile Vision Bill Contract/Product (all product bills) Client (all products and debts) Approach Reactive Standardized across all client types (one-fits-all) Predictive (recovery potential) Customized (right offer to the right client) Classic Indicators (non-exhaustive) Default rate Fulfilled deals rate Recovery rate Cost per recovered rate Win-back rate Churn rate Implications Collections as a function of the revenue cycle Collections as a value lever on the revenue cycle, with set objectives (goals) Challenge is to keep good clients while collecting on debts Source: Accenture Risk Management, December 2013 5

Using Analytics to Strengthen Collection and Recovery Programs In a collection and recovery program, analytics can help accelerate the recovery of outstanding debts and set the proper level of interaction between the lender and the client during the negotiation process. By using scoring and segmentation predictive models, the lender can reduce operational expenditures, preserve the client relationship and increase recovery rates. Analytics can also be used to monitor the client s risk profile, a process initiated the moment the client contracts for the goods or services purchased. As seen in Figure 2, this process is defined as Early Warning and focuses on preventive and anticipatory measures, such as predicting a likely default. Using analytics and the Early Warning process in a comprehensive, interrelated manner can enable the development of targeted strategies tailored to each client profile. Collection activities are intensified based upon the type and level of client relationship, as well as the probability of debt recovery. The main challenges for the business or lending institution usually relate to the availability of quality data to run in these predictive models, as well as the integration of these tools within the organization s existing technology infrastructure. In many cases, analytical models with a strong potential for increasing earnings through recovery are developed but never integrated into the technology environment. These ultimately become obsolete and useless through a lack of use. Figure 2: Analytics and early warning process Early Warning Timely identification of default potential Collection Score Line of actions according to the probability of credit recovery Clustering Approach and intensity of communication according to the client s risk profile Benefits Increase in recovery capacity: identifying clients who will be prioritized in the collection order Improvement in operational expenditures management: activation cost in line with recovery efforts for each client Client relationship: attrition level reduction, especially in self-cure* clients Suitability in proposals: definition of the most appropriate proposals differentiated according to the client s profile *Note: Self-cure is defined as the low action period (cost-free actions) during which spontaneous payment from the client is expected Source: Accenture Risk Management, December 2013 6

Final Considerations Recovery and collection strategies, processes and programs offer businesses a significant opportunity to reduce their collection costs and increase recovery levels while retaining potentially good clients. As interest rates eventually rise along with levels of business and household debt, the need to optimize the organization s ability to recover debt will become a more important credit risk management capability. Statistical-based processes such as Early Warning, along with tools and techniques such as segmentation models applied to client profiles, can make a significant difference in the way debts are monitored and collected. By gaining a more complete understanding of the client who falls behind on payments and by identifying the best way to initiate negotiations with a client companies can reduce collection costs, increase earnings and lower the cost of future sales. 7

About the Authors Tales Sian Lopes Tales Sian Lopes is a managing director, Accenture Finance & Risk Services. Based in Sao Paulo, Tales brings industry and consultancy experience in credit risk management, operational risk management, and credit and collections management to the benefit of leading companies in the financial services, retail and telecommunications industries. You can reach him at: tales.s.lopes@accenture.com Frederico Succi Frederico Succi is a senior manager, Accenture Finance & Risk Services. Based in Sao Paulo, Frederico brings his experience in enterprise risk management, business and risk process analysis, design and implementation and credit and debt recovery to the service of financial services, retail, telecom and energy clients. You can reach him at: frederico.succi@accenture.com Clarissa P. Braga Clarissa P. Braga is a manager, Accenture Finance & Risk Services. Based in Rio de Janeiro, Clarissa leads projects aimed at strengthening analytics strategies and programs for collections and debt recovery processes for sectors such as financial services, telecom and energy. You can reach her at: clarissa.p.braga@accenture.com About Accenture Accenture is a global management consulting, technology services and outsourcing company, with more than 323,000 people serving clients in more than 120 countries. Combining unparalleled experience, comprehensive capabilities across all industries and business functions, and extensive research on the world s most successful companies, Accenture collaborates with clients to help them become high-performance businesses and governments. The company generated net revenues of US$30.0 billion for the fiscal year ended Aug. 31, 2014. Its home page is www.accenture.com. DISCLAIMER: This document is intended for general informational purposes only, does not take into account the reader s specific circumstances, and may not reflect the most current developments. Accenture disclaims, to the fullest extent permitted by applicable law, all liability for the accuracy and completeness of the information in this document and for any acts or omissions made based on such information. Accenture does not provide legal, regulatory, audit or tax advice. Readers are responsible for obtaining such advice from their own legal counsel or other licensed professional. Copyright 2015 Accenture All rights reserved. 02-7776 / 13-4573 Accenture, its logo, and High Performance Delivered are trademarks of Accenture.