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
- 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.
- 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.
- 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.
- 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.
- 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.