Three Predictions for Lending Industry and AI

I had the privilege of spending the summer working with Shantanu Gangal, Sangram Raje and many others at Prodigal. They’re building something special, not just innovative products (though they certainly have that), but also an extraordinary team and company culture. As I move on to my next chapter, I want to share three predictions about the future of the lending industry and what these predictions mean for Prodigal. 

The big picture

There is a transformative shift taking place in lending. AI, ML, digitization, and automation are opening the door for new, innovative models for origination, underwriting, and servicing. How significant are these new opportunities? In the first half of 2021 alone, VC investment in fintech reached a record $25B. This funding will accelerate the democratization of lending. Traditional lenders and their lending partners are being forced to adapt or exit. As new entrants increase, traditional players often adapt by consolidation. Nowhere is this more evident than in collections. While the collections industry has grown, acquisitions have reduced the number of agencies in operation from 8,000 to 4,000. Experts expect agencies will consolidate further, reaching 2,000 or less. Winning players will be the ones that successfully embrace new capabilities and unlock superior returns. 

Servicing 2.0

Servicing is the next phase of the lending lifecycle to experience a tremendous amount of investment activity (see Shantanu’s perspective on this trend in “The Lending Innovation Framework”). The key problem lenders face in the servicing phase is this: How do we reduce operational overhead while simultaneously maximizing collection and cross-sell, and deepening customer relationships? Solutions addressing this problem fall in two domains: loan software and interaction AI. Loan software includes loan origination and servicing systems. These solutions automate and enhance both customer-facing and back-office loan processes. Meanwhile, interaction intelligence consists of a holistic blend of omni-channel agent assistance, virtual assistants and other machine learning applications. Taken together, interaction AI solutions can leverage structured and unstructured customer interaction data gathered across all communication channels. Solutions leverage this data to optimize everything from initial customer contact to customer support to post-interaction analysis. The next few years will see much-needed changes in these domains in order to better serve both lenders and borrowers. 

Industry predictions 

While new players in lending software and interaction AI offer more flexibility, better functionality, and ultimately superior bottom line results, legacy incumbents are hard to dislodge because of compliance and integration barriers. However, there are at least three reasons why legacy incumbents will weaken and give way to new solution providers. 

Prediction #1: Macroeconomic conditions and increasing customer expectations in lending will drive first-party lenders to focus more on servicing and collection than ever before. 

Customers are increasingly expecting greater speed, personalization, and service in return for their patronage. Long an after-thought of lenders, servicing and collection can no longer be “just good enough” because lenders risk losing borrowers and missing out on revenue from cross-sell and improved retention. Meanwhile, economic headwinds threatening borrower health also threaten to overwhelm lenders’ servicing and collection capabilities. While lenders are well positioned to handle standard default volume of two percent, a volume increase reaching four to five percent induced by declining economic conditions would overrun operations, leaving lenders searching for improved servicing capabilities. 

Prediction #2: Interaction AI solution providers who specialize in the lending vertical will capture market share from larger, industry-agnostic players. 

Customer interactions in the lending vertical are quite different from interactions in other B2C contexts. For example, loan-related customer interactions are centered on complex loan contracts instead of physical services or products. Financial products entail unique and complex terms and compliance requirements. Furthermore, even within the lending vertical, use cases and compliance requirements vary significantly across asset classes. Mortgage debt processes and mortgage-related customer interactions are quite different from credit card processes and credit card customer interactions. Interaction AI solution providers who are deep specialists in asset-specific nuances will be able to offer ready-made solutions requiring minimal configuration and delivering superior performance compared to vertical-agnostic solutions. 

Prediction #3: In order to differentiate from legacy platforms and satisfy yet unsolved customer needs, partnerships and acquisitions between loan software and interaction AI solution providers will increase. 

New and traditional lenders are seeking to introduce new loan products with increasing speed and agility. But old loan software and interaction AI is not suited for the newly democratized lending landscape. Legacy solutions are patchwork, outdated, and high-maintenance. The market is waiting for a single, scalable, integrated platform to rapidly launch new loan products. But this requires loan software capabilities with interaction AI embedded. This type of solution empowers lenders to rapidly deliver new and improved products because it simultaneously enables both efficient processes as well as optimized customer experiences. Legacy providers offering separate solutions for loan software and interaction AI will find this model too expensive and time consuming for next gen lending opportunities. 

Implications for Prodigal

Prodigal’s market timing, product suite, and customer traction has them well positioned for rapid growth. Their  recent Series A provides the fuel they need to continue meeting the needs of lenders devoting increasing attention to servicing and collection. As an emerging leader specializing in lending and interaction AI, Prodigal has a prime position even compared to larger, vertical agnostic players. And Prodigal’s impact will only increase as it expands its network of partnerships with loan software solutions. No one knows for sure what the future will hold, but for Shantanu, Sangram, and Team, I expect “Prodigal” returns on investment. 

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