The recent global slowdown, policy overlays, debt moratoriums, fiscal injections, and increased delinquency rates have all brought the scanner on collections experience. Today’s credit environment is different, and so are the digital-first customer support systems and the banks’ criticality to maintaining long-term customer loyalty.

As debt loads and loss rates rise across multiple markets, the leaders in the chaotic collections practice are doubling down – using the current period to ramp up staff skills and leverage advanced analytics to improve performance at a lower cost.

Undoubtedly, the next-generation collections model in retail banking must involve a nuanced understanding of the at-risk customers and the corresponding interventions. A digital-first collections strategy will shoulder the bulk of this burden. The numbers, too, bear this out. A study points out that digital customer service reduces 20% in non-performing loans (NPL), resolves 30+ past due dates (PDD) by 25%, reduces 15% in collections cost, and boosts customer engagement by 5X.

While customer-centric collections capabilities with digital at its core increase each day, the key for collection agencies lies in the following steps.

1.    Advanced Segmentation: Today, most machine-learning approaches operate on creating micro-segments for more targeted interventions. The analytics-driven collections efforts will move away from static delinquency stages or risk scores classifications and be able to treat each borrower as a “segment of one.” Building a sophisticated risk model that estimates ‘value at risk’ will project conditional probability instead of single risk scores.
2.   Matching Channels and Preferences: Research posits that contacting customers through preferred digital channels improves effectiveness significantly, especially in low delinquency stages. An effective multi-channel contact strategy goes beyond a one-size-fits-all. It depends on technology infrastructure, AI and Automation capabilities, and a contact strategy that addresses various segments through appropriate channels, with the right messages in the proper sequence.
3.   New tech implants in the collections environment: From contact center interface, banking machines (with automated touchpoints), IVR, Website messaging, Messenger and chat platforms, mobile apps, virtual agents, most banks are moving to advanced algorithms to establish the best times to call, down to the hour and minute. The optimal contact sequencing across various communications (voice, text, email, IVR message, self-service) positively influences customer behavior to prioritize payments.
4.  Customer-oriented operations with centralized systems: As smartphone and app usage increases, collection agencies are beginning to accept app-based payment to go with web-based methods. With app payments and automated phone calls, online payments inject convenience into the process. Another efficiency initiative is the centralized system – a program that allows personnel to view the same accounts on the same database. Using diallers and prompts, collectors review reports, and trigger alerts are cost-saving measures that ease workflows and decision-making issues.
5.   Competency building for frontline staff: To assess (and treat) at-risk customers for their ‘ability to pay and willingness to pay is a valued skill in collections. Locating skilled candidates that bring this rare social (or local) mindset is not easy. Furthermore, connecting at the human level and employing an easy meticulous manner that listens and also problem solves is critical for collections. All this constitutes the complexity of selecting, onboarding, training, and motivating collections staff – a job, when done well, pays rich dividends.
6.  Maximizing Machine Learning Models: Integrated analytics models that work on an assembly of data masses are a potent way to decide the optimal contact and treatment strategy. These methods, over time, have lowered charge-off losses and increased recovered amounts. Today’s sophisticated lending agencies use multiple variables across various systems (customer demographics, account activity, payments, risk ratings, cash flow status, collections history).

Conclusion

The future of collections will see more lending institutions investing in data analytics that better understand data gaps, identify internal and external data sources to create alerts, build intelligence for optimal micro-segments with similar risk profiles, and develops models for advanced validation.

With a slew of hyper-personalization initiatives, the UK’s retail banking market responds to increasingly intelligent devices, rapidly evolving CX, and real-time data processing. Coming on the back of a ravaging pandemic, stung with financial hardships, retail banks, like most banking organizations, scramble to reimagine a new future.

Today’s essential question is how far do the UK banks lag and the way to leapfrog?  

A study for Western Europe projects a future in which revenues dropped anywhere from 16 to 44 percent. The phoenix-like aspirations can come true as and when UK’s retail banking market can seize three primary opportunities: First and the easiest would be to capitalize on customers’ acceptance of digital behaviors that have evolved in the pandemic years. The second will be to launch new products (especially as physical branch numbers thin out, freeing up fiscal commitments). The third lever will pursue innovative risk mitigation approaches that aim for higher accuracy using real-time transaction data.

Digital Retail Banking in the UK – the new equation. 

The starting premise is straightforward. Before investments in digital skills and new transformation capabilities and next-gen technologies to empower customers can happen, the critical difference will come from a banks’ mindset that is not only aware of the sheer width of complexity at hand but also employs human ingenuity in the service of the single biggest (and most elusive) ‘bankable’ commodity – trust.

Digital Transformation in Retail Banking – A fair or unfair comparison?

Interwoven in our daily lives, ‘software’ has changed how we operate as a society; the definition does not completely extend to retail banking. So, on hand, it isn’t easy to imagine a life without Uber, Spotify, Netflix, Amazon, Alibaba, Google, and on the other hand, as a report suggests, only 35% of small-business executives say they depend on banks for financial advice, or only, 14% of customers experienced a financially impactful event in the last 60 months and sought help from their bank.

No matter where the verdict rests, retail banking embraces innovations in ways more than slapping more software onto an archaic system.

The influx of new-age tech in Retail Banking

The case for digital transformation – regardless of a bank’s current position, future aspirations, customer focus, brand promise, regulatory challenges, and capital constraints – is unequivocally clear: Go full steam ahead. However, there is an apparent reality that UK retail banks are coming fully to terms with, namely, the Brexit displacement. After all, financial services firms operating in the UK shifted 7.500 employees and more than $1.6T of assets to the EU.

The projections appear impressive, the disruptive technologies driving digital transformations in retail banking like Cloud/SaaS, API’s microservices, DevOps, Big Data, AI/ML, and Blockchain/distributed DB. One, the core banking platforms premised on the mentioned tech. can deliver complex functionality 20X faster, and two are 10X cheaper to run.

CX Plus

Traditional banks ‘ emphasis changes en-masse by learning from Amazon and Google (and their financial forays).

Circling back to the criticality of building trust, retail UK banks are incorporating a digitally augmented customer experience into their capability models. What does that entail?

From distribution and channels aligned to Millennial and Gen Z preferences (Omni-channel, contextual user experience, mass personalization, and open banking) to infusing analytics (flexible modular product engines riding on scalable, secure Cloud and operating on agile operating models), retail banking is combating the familiar pain points (high Opex, poor CX, reduced speed to market and weak real-time insights) with renewed vigor.

The Road to Recovery for UK’s Retail Banking

Admittedly, like other industries impacted by digital transformation, the pivot points are the same for retail banking – protect and grow market share and, at the same time, create new trust-based revenue streams.

An exciting study points out that one in four retail banks and credit unions had embarked on some form of digitalization in 2019 (and 45% had yet to launch in 2021.) Less than four of 10 feel they are halfway in their journeys, and here is the rub – only 14% have embraced Cloud computing and APIs or invested in ML workflows, or even deployed chatbots.

The reality is sobering. The ‘delusion of digital’ must be dispelled soon. 

How would UK’s retail banking CEOs know their transformation trajectory is a true one? Proof of the pudding lies in the eating.

Put the customer back into the equation and test for systemic friction (including the back end). For instance, the minutes it takes to fill out an account opening form, approve loan applications, or even the time it takes to bring a digital product to the market.

The answers will point to the journey ahead!

Retail Banking IT difficulties and arrangements in a hyper-associated age

As start-ups redraw the retail banking world map as we know it, there are estimates of $4.7T in revenue being displaced from incumbent financial services firms. The fierce competition coincides with the customers’ ease of switching providers. It appears the big-bang-banking moment is near. After all, the last 24-months demanded the execution of a virtual and untested retail banking services model. As customer restlessness runs at an unprecedented high, community banks, credit unions, and Fintech vie for the same pie. A study points out attrition rates in retail banking hovers around 11%, but the annual churn rates for new customers is close to 25% during the first year, half of which doesn’t make it to the 90-day mark.

Read that again: One in four customers will leave before the year runs out.

Compounding these churn challenges are the anachronistic siloes traditional banks cling to. When two departments in the same bank, a retail banker with transactional data and the wealth manager with a net worth or loan data, do not engage with the customer in a joint (or ‘Omni’ way), rich behavioral insights and sales opportunities are instantly sacrificed. In a world where customers are digital natives, operating out of multiple sources of truth is untenable.

Top five IT challenges and coping mechanisms for Retail Banks 

1. Cost Reduction: A industry report highlights the top three priorities that consume the lion’s share of their budget: regulatory compliance, elevating customer service, and implementing new technologies. These draining effects and relentless cost reduction pressures leave little over for banks to innovate. How do banks resolve this challenge? IT cost investments for retail banks are best decided over a ‘skills maturity – market opportunity’ matrix. Integrated into the long-term strategy, C Suite leaders must demonstrate agility by estimating risks accurately and wiring that into their innovation growth plays.
2. Answering pivotal questions correctly: When compared across their regional and global vision, core competencies, risk appetites, or capital constraints, no two banks are alike. As modernizing their core is a must to come good on customers’ digital expectations, retail banks face an exhausting slew of variables. Where does one begin? The front office or middle office, or back office? What are the critical use cases that should be pursued? What are key trends to be prioritized from an IT perspective – conversational banking, credit underwriting, anti-fraud, cyber security, AI-enabled biometrics, or Omnichannel banking? These questions do not come with easy answers. The way to move forward is via deep dives that assess revenue impact sizes and the ecosystem opportunities that work best for leapfrogging attempts.
3. Addressing Open Banking: The third IT challenge that retail banks face for a year comes from Open banking. CMA (competition and market authority) and market forces have undeniably brought banks into an aggressive mode. The complex demands involved in creating open, collaborative platforms require refurbishing legacy systems, redefining banking ecosystems, building holistic business models that monetize data assets and avoid future data siloes. Understandably, open banking is relatively new, as leading retail banks vigorously prepare for it. Agile and responsive intermediary layers atop core banking are being implemented. These new systems allow for API engagement, enabling third-party providers to receive customer and transaction information. Another way banks are meeting the IT challenge is by actively collaborating with Fintechs to tap into new and unrealized revenue opportunities.
4. Meeting the AI and ML challenges: The potential annual value of AI and analytics for global banking is tipped to cross $1T. Banks, like other industries, are thrust into an AI-powered digital age as data storage, processing costs crash, customer access, and connectivity increase each day, and the mountains of data generated by the second, call for ‘beyond-human’ decision-making abilities. What does this shift do to IT departments in traditional financial organizations? Under pressures to rapidly digitize, simplify and rebuild their processes to become more agile, IT leaders fail to precisely map how tomorrow’s winning equation will function with its AI and ML variables. The sweet spot lies in adopting a flexible and adaptive approach that presents challenges in a future-ready framework where technology meets its business potential.
5. Enabling Innovation: In the climate of customer-centric business models, optimized distribution, leveraging data analytics, and proactively managing risks, the largest source of challenge for IT departments comes from the need to foster innovation capabilities. While banking leaders highlight the primary focal areas to innovate (customer interfaces and channels, customer need identification, products, and core platforms), banks are not exactly the hotbed for innovations. The reasons that aren’t difficult to decipher are not restricted to IT. First is the dearth of talent across data and analytics competencies and agile development capabilities (product and technology). The second block comes from limited ecosystem partnerships that hinder IT functions to create innovation crucibles for prototyping new products. The solution for this lies in changing the current mindsets, namely, leadership commitment (and innovation sponsorships) in cultivating a penalty-free culture.