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The Reinvention of Banking

Allison Karavos
June 22, 2023

Why banks need to ensure resiliency and innovation to achieve long-term profitability

As economic stability increasingly looks like a thing of the past, what does this mean for traditional banks? With disruption after disruption in the financial services sector, it’s clear that resiliency is a must. According to McKinsey, “banks will need to become more resilient and reinvent their business models to ride out the current volatile period and achieve long-term growth and profitability.” But what does reinvention really mean? And is it possible to reinvent your business models quickly? We’re looking at some of the key challenges the banking industry is facing, and the ways that upgrading credit risk decisioning capabilities can help solve for some of these challenges.

Banking Disruptors:

Banks and the financial industry as a whole face many challenges, not the least of which includes fintechs and challenger banks. But the need to keep up with the competition is not the only obstacle banks are facing.

Evolving Regulations: Complying with various regulatory requirements is always a challenge, but it’s even more difficult when those regulations are constantly evolving. Look at the world of Buy Now, Pay Later as an example – as this non-traditional financial services offering continues to grow and shift worldwide, more and more traditional banks are sitting up and taking notice. But getting into the market can be fraught with compliance issues, which can be costly and time-consuming, and as a result, impedes your ability to innovate and respond quickly to changing customer needs.

Increasing Digitization: If the last few years have taught us anything, it’s that more things than ever thought possible can be done digitally. Customers increasingly want digital channels to meet ALL of their needs, including financial services of all kinds – whether that’s applying for credit or embedded finance enabling banking super-apps. But this requires clear investment in technology from banks to remain competitive.

Growing Competition: Speaking of remaining competitive – more than ever, new players are continually entering the market, vying for a share of the wallets of increasingly discerning consumers. Whether it’s established players with new offerings or innovative fintech startups, the landscape is changing, putting pressure on banks to reduce costs and improve offerings, while still providing frictionless experiences for consumers.

Also, read: What is Banking as a Service?

Turning Disruption into Opportunity:

But it’s not all dire. Banks can be uniquely positioned to effectively deal with these disruptors. As Siobhan Byron writes, “established banks, though still only recently starting to harness the power of digital, have a key advantage over new entrants. Their decades of institutional knowledge is difficult to build up quickly.” Banks are also in a better position to deal with market shifts than they were a decade ago – if they can leverage data analytics and automated workflows to make “better and more informed credit decisions.”

So, if you’re a bank, what can you do? Look for ways to leverage advanced technology like artificial intelligence and machine learning, automated credit risk decisioning, and data integration to improve efficiency, reduce costs, and renew your focus on customer-centric products and services.

Increase Efficiency: Machine learning algorithms can enhance your credit risk models, processing vast amounts of data quickly and reducing the time and person-power needed for risk assessments and credit decisioning.

Reduce Costs: Automating your credit risk decisioning process reduces the manual labor required, allowing you to allocate resources to other strategic initiatives that can help grow your revenue and improve the customer experience.

Enhance the Customer Experience: Focus on frictionless onboarding and customer management, with faster credit decisions, digitized processes, and more personalized product offerings (including everything from interest rates to loan terms, upsell/cross-sell offers, and even optimized collections strategies).

Improve Risk Management: Advanced analytics can enable you to identify key patterns and trends in customer behavior, ensuring more accurate risk assessments and reduced losses due to defaults and improved fraud detection.

Enable Agility: With more flexible, user-friendly decisioning technology, you can make changes to decisioning workflows quickly, respond to market shifts, meet changing consumer demands, and launch new products faster to stay ahead of your competition.

Foster Innovation: Enabling all the above points (with more automated decisioning, advanced analytics, superior data integration, improved efficiency, etc.) means you can foster a true culture of innovation. Allow your teams to focus on strategic initiatives, competitive insights, and innovative product development for customer-centric offerings that can help put you ahead of the competition.

Roadmap for Success:

The larger the bank and the more complex the systems, the more daunting it can feel to implement any changes to your decisioning software or data sources. But fear not, follow some simple steps to incorporate tech upgrades into your credit risk decisioning – and remember, it’s not all or nothing: look at decisioning solutions that can easily work alongside your existing systems and/or partners that have experience replacing legacy systems to ensure a smooth transition.

  1. Assess Current Capabilities: Evaluate your existing credit risk decisioning capabilities and identify areas where you can improve your processes.
  2. Define Your Objectives: What are your goals for upgrading your tech? Prioritize the areas that are most important for you (i.e., reducing costs with improved efficiencies, versus enhancing the customer experience with increased digitization capabilities).
  3. Select Technology Capabilities: Choose what is most critical to upgrade – is it automated risk decisioning, machine learning, data integration?
  4. Choose Your Solution: Outline a plan for integrating the chosen technology into your existing systems and workflows, with a partner that can help with timelines, resource allocations, and important milestones.
  5. Test and Iterate: Be sure your chosen risk decisioning solution offers you the ability to test workflows, refine your credit models, easily integrate new data sources, and iterate your processes – on your timeline, not theirs!

With the right technology in place, not only can you accomplish all the goals set out above, but you can more easily maximize the value of your customers across the entire lifecycle. Because with upgraded credit risk decisioning, you can more efficiently move beyond credit origination and onboarding and bring that customer-centric experience to all the financial services products you offer. As McKinsey points out, “banks that have already embedded high-performance credit-decisioning models into their digital lending have reaped three key benefits,” including increased revenue, reduction in credit losses and gains in efficiency. So, what are you waiting for?

Want more info on how to turn challenges into opportunities?


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