Delivering AI-Driven and Digitally Led Solutions to Improve Experiences for Borrowers and Lenders, Lower Costs to Collect, and Increase Dollars Collected.
In 2020, the US unemployment rate peaked at a level not seen since data collection started in 1948. This has fueled a significant increase in inbound calls to collections centers with some banks and financial institutions (FIs) fielding increases of more than 2,500 percent daily. While delinquencies have not risen due to consumer relief provided by the CARES Act and other accommodations made by lenders, banks and FIs are racing to find ways their debt recovery efforts might help the financial well-being of consumers while enabling debtors to serve and collect more effectively.
Today we explore some of the key design principles behind more effective debt collections and recovery strategies, such as AI-led intelligence frameworks and digital collaboration, personalization and self-service channels, AI-enabled unified agent workstations, and product-agnostic technology modernization.
Adopting New Risk Segmentation & Prioritization Models
Does your risk segmentation and prioritization strategy answer these key questions: who is likely to charge off, who has previously paid consistently, who has a stronger financial profile to make a payment, who would benefit from early loss mitigation, what is the customer’s receptivity to different channels? A successful strategy begins with a robust decision engine to shift banks and lending institutions from rule-based risk segmentation to a learning-based organization that leverages data for personalization across all customer touch points. This shift to a learning organization helps debtors connect with customers on the right channel, with the right message and the right curing strategy at the right time.
Implementing a learning-based risk segmentation strategy helps banks and FIs prioritize targets and more effectively reach customers with the right message, right curing strategy, on the right channel, at the right time.
An effective risk segmentation and prioritization model goes beyond segmenting high value at risk (HVAR) customers and looks at the more granular dimensions of financial ability to pay, willingness to pay, and the lifetime value of customers. Leveraging native AI and advanced ML capabilities that redefine collections by improving the accuracy of risk segmentation models and appropriate collections strategies, lenders can get accurate predictions.
Improving Omni-Channel Experience: Self-Service, Flexible Curing and Payment Options
Consumer frustrations with debtors have been exacerbated by the pressures of not being able to pay bills. Debtors who rely too heavily on phone channels are often not contacting customers on their preferred engagement channel and missing opportunities for customers to self-cure. Most consumers in the 0-30 past due bucket have simply forgot to pay bill and would relish in the ability to self-serve and avoid receiving a call from a collector.
Enabling customers to self-serve via IVR, text, email, virtual assistants, and online banking/mobile apps empowers them to communicate and transact on their preferred channel. With the ability to offer customers more flexible payment types, including ACH, debit cards, and remote check deposit, and digitize the financial hardship application journey, banks and FIs can increase dollars collected and better serve clients on lower cost channels – all leading to improved customer experiences.
With a unified alerting omni-channel strategy and self-service payment and financial hardship application capabilities, banks and FIs can optimize channel effectiveness using AI to detect the presence of customers on a digital channel to surface alerts and engage customers on their channel of choice. A continuous feedback loop to the decision engine will ensure that customer receptivity to different channels is captured for future engagement.
Increasing Agent Effectiveness: AI-Enabled Conversations, Integrated Workstations
Several debt collectors today are plagued by large product ecosystems that require agents to access up to 10 systems to reach and service a single customer. Banks and FIs who favor a single integrated agent interface can benefit from persona-based dashboards and AI-assisted agent and customer journeys that provide agents with the next best conversation and curing solution to improve promise to pay and kept rates while reducing average handling times.
With machine learning models streamlining channel optimization, agents can focus on high value, at risk customers, and engage other clients at critical points of their interactions through lower cost digital channels. The AI-driven agent workstation can also detect aging on digital payment channels and during the loss mitigation application process to provide collaboration tools such as video chat and co-browsing that help customers complete transactions and lead to increased dollars collected.
Interaction timelines can provide agents with insights on the customer’s interactions with the bank, the channel on which they occurred, and whether they were initiated by the customer or the bank, eliminating customer frustrations with lack of insight into their historical conversations. Access to transcripts from recent service inquiries may also help agents have a better understanding of the customer’s current financial situation.
Modernizing Technology Platforms: Unlock Digital Value in Existing Tech Stacks
By decoupling the experience layer from the underlying technology layers of communications, modeling, data services, and product and payment engines supporting collections operations, banks and FIs can untangle the web of complex, legacy technology architectures to achieve a single, integrated user interface and omni-channel customer and agent experience. Enabled by developing the data services and an API ecosystem, a new product-agnostic technology architecture helps banks and FIs accelerate their capability speed to market. This provides a unified experience to customers and agents that drives more effective communications, collaboration, and self-service for customers.
Banks and FIs can leverage their existing product engines to unlock the value of their digital assets, while maintaining control over the experience layer to completely align user experiences for customers and colleagues and prioritize their product roadmap based on their specific vision (not a product vendors). Using an incremental approach where each building block is engineered to leverage enterprise capabilities (e.g., e-signature, document upload), solutions can be fully extendable and enable rapid scaling through short design and development cycles.
The New Normal: Digital First and Outcome Focused Transformation
Banks and FIs seeking to reduce costs to collect and improve the collections experience for customers are shifting to digital first operating models. As customer expectations to be served on their preferred channel increase and organizations seek to lower operating costs, having the ability to manage and scale your workforce with digital self-service channels, empower agents with AI-assisted conversations and curing strategies, and automate supporting back office functions is paramount.
Enabling transformation through a value seeking and a value capture model ensures self-funded transformation. By prioritizing MVPs that will result in the greatest business impacts delivered in the shortest period, organizations can more quickly implement a collections transformation strategy that delivers immediate value to customers and colleagues.
To learn more about how Infosys can help accelerate your debt collections and recovery transformation, contact us today.
Managing Partner, Financial Services and Insurance
As Managing partner- Financial Services and Insurance (FSI), Rajesh leads the global FSI practice for Infosys Consulting. Rajesh has been with Infosys consulting for 17 years and has played a varied set of leadership roles. Rajesh has helped drive large transformation programs across various themes, regulatory compliance, commercial banking, wealth and asset management with clients like Citigroup, Wells Fargo, American Express, Fidelity, Goldman Sachs, UBS and Allstate, to name a few. Some of his industry-leading thought leadership is featured on our Insights digital platform. These include “Capturing next wave of growth in banking: a post COVID-19 roadmap”, “Reinventing Wealth Management in the Digital Age” and “Reimagining Investment Research”. Rajesh is an alumnus of Jamnalal Bajaj Institute of Management, Mumbai and Stanford Business School and is based out of our New York office.
Swaminathan Sundaresan is an Associate Partner at Infosys Consulting and is focused on driving digital transformation and analytics programs in the space of wholesale banking. Swami has worked with a number of leading global banks in delivering strategic programs at the intersection of Analytics and Digital transformation across the wholesale banking value chain.
Michele Boudway is a leader of experience design and digital strategy at Infosys Consulting, focused on reimagining customer and colleague experiences and driving business outcome-based digital transformation for banking and financial services clients. Michele has worked with several top global banks and financial institutions to help them envision and execute transformation through a human-centric lens while creating and capturing value.