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  • Writer's pictureCorridor Research

Digital Decisioning Challenges for Credit Unions and Community Banks in Recession

Updated: Oct 27, 2023

Blog Summary – To compete in today’s market, mid-tier banks and credit unions must transform their decisioning capability to meet customers’ heightened digital lending expectations.

Advances in mobile internet technology, growing smartphone use, and shifting consumer expectations have driven consumers’ appetite for more responsive digital banking platforms. Due to this escalating demand, a growing number of financial institutions now offer relevant, real-time digital lending products.


The digitization of banking has fundamentally transformed the financial landscape. Traditional lending practices are no longer enough to survive, let alone thrive in today’s market. Credit unions and mid-tier banks may have invested in front-end digitization. However, most still lack the sophisticated decisioning capabilities to compete with Tier 1 banks. Uplifting decisioning requires automating and uplifting the entire decisioning workflow; starting with controls on data, creating models at scale, and then using them in decisioning strategies with strict compliance, for example in underwriting, risk-based pricing, collections and proactive marketing.


If Tier 2 banks want to retain and grow their customer base, upgrading their overall digital decisioning process from data infrastructure to decision analytics, and robust governance and compliance with flexibility and speed is crucial.


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Digital Lending: A New Landscape for Banking and Financial Services


Modern consumers are increasingly tech-savvy. They expect innovative, convenient, and easy-to-use digital tools in every facet of their lives—and financial products are no exception. Digital lending is now imperative as table stakes, it’s no longer just a nice-to-have service option.

As digitization of banking products and service offerings has ramped up, customers expect personalized treatment, like one might experience personalized service with Amazon or Uber. The bar is high!

Most consumers prefer to apply for loans online. As such, product flexibility, straightforward application processes, and swift decision- making capabilities by lenders are key. Building an online lending platform is not enough. Online lenders also need to provide well-targeted offers at the point of need, utilizing the full spectrum of real-time contextual and customer permissioned data.

Delivering a superior and near-instantaneous experience rests on excellent digital capabilities, advanced modeling techniques, and new data streams. Larger banks have had several years to reach this point and are still fine-tuning algorithms and ironing out compliance issues. But smaller banks must also embrace precise credit assessment based on better AI, automated and customized digital decisioning workflows quickly to compete in the current recessionary environment – else they could suffer adverse selection.


Modern Decisioning Challenges for Credit Unions and Community Banks

It is imperative that credit unions and community banks offer consumers a fully automated, responsive, and personalized digital lending platform. However, this requires a level of decisioning capability that comes with its own set of complications.

Below are some of the particular challenges posed by data and analytics, in tandem with decisioning technology and need for frictionless customer experience.


Data

Banks have access to a wealth of customer data, from credit history to income and bank statement data, as well as utility payment data. However, this means little without the requisite governance capabilities to use this data for real-time decisioning.

There has been a proliferation of new data sources, both structured and unstructured. Mid-tier banks often struggle to deal with the sheer scale of these new inputs. The central challenge is to overcome a legacy decisioning lifecycle that is based on simple decision-making rules using bureau scores versus sophisticated custom ML and manual compliance and governance processes. In addition, there are risks associated with the uncontrolled usage of sensitive data—not to mention an overlong, expensive learning curve.

Faced with operational and regulatory bottlenecks, how can smaller banks hold their own against the dominant players? Especially when larger entities have access to better data to make contextual offers at the right time.

To be competitive, mid-sized lenders must implement secure and well-governed cloud architecture for decisioning. Key features of this new infrastructure must include access to external and internal bank data, as well as APIs for instant decisioning. Institutions unable to create attractive and meaningful digital product offerings will face major negative select at acquisition which creates losses downstream, not ideal in an impending recession.

Analytics Community banks and credit unions need a sophisticated machine learning and AI decisioning platform to compete with Tier 1 banks’ value propositions. This requires professional talents and resources of sophisticated in-house decisioning analytics.

The current model risk management frameworks are fairly manual, including handoffs, then back and forth between modeling teams and compliance teams, which may have been sufficient for traditional modeling capabilities so far. However, with the increased sophistication of analytics modeling technique, these manual handoffs now become a barrier and create significant speed lag in terms of speed-to-market and ability to monitor and track decisions.

Break down is inevitable.

Today’s dynamic digital lending marketplace demands ready-to-use decisioning and machine learning. If banks wish to remain viable, upgrading analytics to provide for at-scale development, efficient processes, automated monitoring, and transparent governance is no longer a choice-it’s a necessity.


Decision Tech & Customer Experience

Successful lending institutions rely on advanced analytics and real-time, interactive decisioning at point of need to optimize the customer experience and improve uptake rates. That means offering fast-yet well-constructed risk appetite loan decisions. Upgrading decisioning technology and compliance allows for rapid iterations and quick deployment. Based on systemic governance, workflow automation, automated monitoring, and pre-vetted or standardized compliance dashboards.

Fully automated, digital-first lending platforms must also ensure regulatory compliance. For instance, Consumer Financial Protection Bureau (CFPB) advisory makes it clear that the prohibition on discrimination applies not just at origination but through the lifetime of a loan.

Bottom-line, banks cannot afford to make mistakes. So systematic governance and ready-to-use compliance artifacts is a core capability, not a function that can be outsourced as a small piece of the puzzle. The full lifecycle of the loan and ongoing efforts to comply is a necessary activity to keep and build as an in-house capability.

In the absence of appropriate decisioning technology and contextual information, smaller banks will be unable to provide consumers with fast, personalized, loan offers. It follows that customers who don’t receive the anticipated level of service will soon switch to an institution that’s more responsive to their needs, and those applicants who come to the bank might be the ones you do not want to approve due to adverse selection.


Source : Shutterstock


Decision-as-a-Service: The Next-Gen Solution for Real-Time Decisioning

The rapid uptake of digital lending has put many mid-sized and regional banks at a significant disadvantage as they lack the tech infrastructure required to support real-time decisioning.

The time is now to level the playing field with a solution built to provide ready-to-use features able to handle data, run analytics, and sharpen automated, on-the-fly decisioning.

Decision-as-a-Service (DaaS) solutions give community banks and credit unions off-the-shelf Tier 1 capability, marked by speedy digital decisioning and robust analytical capabilities. It’s the best way to establish a digital lending presence in the current financial environment without costly mistakes, delays, or do-overs.

DaaS shortens the time-to-market through quick loan approvals, quality customer service, and transparent governance. DaaS also provides online lenders the opportunity to define their lending appetite thereby improving their ability to select creditworthy customers more efficiently. This significantly reduces the risk of credit-loss rates and optimizes compliance across the entire loan journey.


Update and Elevate Your Decisioning Capabilities With the Experts at Corridor Platforms Today!


As a leading provider of proprietary decision workflow governance and automation software, Corridor Platforms leverages the power of data and digital solutions to provide an innovative decision workflow automation platform to swiftly assist you with getting your tech and processes set up to fix this complex problem.


EXL, Corridor Platforms, and Oliver Wyman have collaborated in a joint venture to provide financial institutions with a Decisioning-as-a-Service risk solution. Their breakthrough model combines advanced analytics, AI, and cloud technology to deliver the instant digital lending decisions needed for digitization initiatives, such as point-of-sale financing, digital loans, mortgage approvals, and real-time credit limit changes. Read more about this offering at https://riskdecisioning.ai/.


Banks can learn on the job from industry experts while modernizing and automating systems to deliver real-time digital lending decisions with sufficient risk governance to meet their fiduciary requirements. Enhance your lending institution’s decisioning capabilities with a partner like Corridor Platforms to help your institution grow into a digital lending centre fit for the future of finance.


Contact the experts at Corridor Platforms today to find out what Decision-as-a-Service can do for you and address challenges of the current recessionary environment head-on.

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