In a survey conducted to understand the role of community banks and credit unions in the US financial system, 44% of bank executives, small business owners (SBOs), and consumers said that they expected community banks to offer online account opening facilities. However, only 57% of community banks and credit unions were found to offer it. (Source: Wakefield Research)
This is only one of many such statistics that show that despite being an integral part of the US financial system, community banks and credit unions are falling behind in catching up with the rapid digital transformation that the banking and financial services (B&FS) industry is experiencing presently.
The personal touch, more flexibility, and lower rates and fees that community banks and credit unions offer to their customers indeed make them the cornerstone of local economies, maintaining competition and equity in the financial ecosystem. However, to bridge the growing digital transformation gap faster, what they need is a more focused approach to modernizing their IT infrastructure.
A modern data platform becomes the foundation for adopting advanced data analytics and cutting-edge technologies like generative AI that can help them address the numerous industry challenges community banks encounter. This can also empower community banks and credit unions to survive the stiff competition they face from the mega global banks, regional banks as well as contemporary neo-banks.
Table of Contents
5 Key Industry Challenges Faced by Community Banks and Credit Unions
The COVID-19 pandemic has fundamentally altered the way we live and work, presenting community banks and credit unions with some of the following challenges that they must overcome:
1. Growth of Digital Banking
With mobile banking and online transactions taking center stage, particularly post-pandemic, community banks and credit unions face the urgency to fast-track their digital transformation initiatives and evolve with the competition.
2. Shifting Customer Expectations
The rapidly rising expectations from customers today require community banks and credit unions to deliver a similar level of personalization and seamless customer experiences that larger banks offer to their customers.
3. Competition from FinTech & Neobanks
Open banking is on the rise. Fintech companies and neobanks are redefining the B&FS landscape through their ultra-modernized offerings. Bringing such agility and innovation emerges as a top priority for community banks.
4. Increasing Cybersecurity Threats
Advancements in technology have given rise to increasingly sophisticated cyberattacks such as AI and generative AI phishing. Community banks and credit unions must build a stronger defense against safeguarding their systems and the sensitive customer data they are entrusted with.
5. Regulatory Compliance Complexities
Community banks and credit unions are governed by regulatory bodies such as the National Credit Union Administration (NCUA), the Federal Reserve Board, and the Consumer Financial Protection Bureau (CFPB). Additionally, they must also comply with local laws and regulations. The focus should be on building capabilities to ensure compliance with these complex and constantly evolving regulatory expectations.
The Data Challenge
As the B&FS industry turns toward digitalization, community banks and credit unions are presented with a critical challenge: harnessing the volume, variety, velocity, and veracity of data for efficient decision-making.
- Big Data and Unstructured Data: There’s a plethora of customer data out there waiting to be leveraged. However, the complexity of managing all this data, particularly unstructured data such as social media sentiments, call center transcripts and customer emails, using traditional tools and strategies hinders the ability to deliver personalized services and improved efficiencies.
- Data Agnostic Digital Strategy: A data-agnostic digital strategy fails to prioritize data utilization and optimization. When B&FS institutions attempt digital transformation without a clear focus on harnessing the data, they may miss out on the competitive advantages offered by data-driven decision-making and may not be able to catch up with the rapid industry transformations.
- Poor Data Handling Practices: Traditional mechanisms of storing and processing data across disparate on-premises systems lead to data silos and fragmented insights. Banks struggle to get a full picture of their data which is essential for making holistic informed decisions.
- Knowledge Management Challenges: With legacy systems in place, banks and credit unions fail to organize and share the vast volume of information they must deal with such as regulatory updates, product information, policies and other data properly with employees or customers.
The Struggle with Legacy Systems and Infrastructure
In the age of real-time transactions and quick scalability to respond to market volatilities, credit unions and community banks using legacy systems struggle to catch up with the modern needs of the B&FS industry. Here’s why:
- Account-centric Banking: Traditional data platforms struggle to deliver a ‘Single View of data’ which leads to account-centric banking. Whereas, the need of the hour is customer-centric banking, where a B&FS institution can meet evolving customer expectations and deliver seamless omnichannel experiences through a holistic view of customer data.
- Lack of Interoperability: Multiple isolated legacy systems accumulated over the years lead to a lack of interoperability. Various departments or functions within the community bank struggle to communicate and exchange data efficiently. This leads to inefficiencies, errors, and challenges in providing a smooth and integrated experience to customers.
- Manual Dependencies: Disparate legacy systems fail to support automation. Manual and batch processes result in slow and error-prone operations, leading to sluggish business growth.
- Scalability Limitations: Legacy systems built on-premises also pose scalability challenges, limiting responsiveness to dynamic market trends and evolving customer demands.
- Technological Impairment: Integrating the latest tools and technologies into age-old systems becomes challenging, leaving little room for modernization. This becomes a major obstacle in keeping up with the competition, restricting innovation and growth.
- Limited Analytics Capabilities: The legacy constraints in tapping into the power of advanced data analytics and technologies like generative AI to unlock deep insights about customers’ financial habits and preferences, potential risks, latest market trends, etc. restrict informed decision-making.
- Maintenance Overheads: Upgrading and maintaining legacy systems and software is costly and resource-intensive. Smaller community banks and credit unions, often operating with fewer resources, struggle with finding skilled personnel to maintain these legacy technologies.
How Modern Data Platforms Benefit Community Banks and Credit Unions
Modern Data Platforms integrated with cutting-edge technologies like generative AI and machine learning (ML) become a powerful solution for community banks and credit unions, enhancing operational efficiency, customer experience and offering numerous other benefits.
1. Cloud-ready Infrastructure
This opens doors to the swift implementation of digital channels like mobile banking and online loan applications, accelerates time to market for products and services, and eliminates costly overheads.
2. Generative AI Integration
Leveraging the latest generative AI, community banks and credit unions can further transform customer interactions, product offerings, and processes through automation, predictive analytics and decision-making support.
3. Conversational AI
Modernized data platforms can support conversational AI such as chatbots and virtual assistants that take customer experience and engagement to the next level through instant 24×7 support, answering queries and offering assistance.
4. Streamlined Operations
Modern core banking systems integrated with these data platforms can further streamline operations and reduce costs.
5. Seamless Data Access
Efficient data management and knowledge management can empower bank employees with swift and centralized access to all the latest information to solve the customers’ needs at the first interaction and operate efficiently.
6. Customer Insights and Personalization
Revolutionary technologies like AI and data analytics can be used to unlock valuable customer insights for personalization, enabling smaller community banks to win over their customers more easily.
7. Enhanced Security
Features like encryption and access controls in modern data platforms can help community banks and credit unions address their biggest fear of data breaches and compliance.
A Case in Point: A Community Bank Drives Business Growth with Data Platform Modernization
Challenge: A leading community bank’s leadership was planning to scale the business and serve customers beyond its traditional physical footprint. However, they faced several limitations due to their dependency on legacy technologies. This hindered real-time data sharing and collaboration with partners. Tackling infrastructure challenges such as data ingestion complexity and poor data quality concerns was not easy. Also, ensuring data security and compliance was a top priority.
Solution: The bank’s leadership partnered with a reputed technology consultant to build a modern, future-proof data platform integrated with Gen AI capabilities using Databricks. The bank leveraged Delta Sharing for secure data sharing across platforms and clouds. They transitioned from their data lake-based platform to a lakehouse architecture with Databricks, enabling real-time data processing, scalable infrastructure, and simplified data management. Databricks integrated smoothly with Azure and offered a wide range of data transformation and engineering tools that helped the bank reduce risk concerns, both internally and across partner systems.
Value Gained: The modernization initiative brought about unprecedented time-to-value, accelerating customer acquisition and growth while improving operational efficiencies. With Databricks, the bank streamlined data ingestion, improved risk management and compliance, and scaled to serve millions of customers through their partner ecosystem, driving business growth and enhancing customer experiences.
Data Platform Modernization to Unlock Powerful Use Cases of Analytics & Gen AI for Community Banks & Credit Unions
| Operational Excellence | Customer Experience |
|---|---|
| Customer Churn Prediction | Digital-First Approach |
| Fraud/Anomaly Detection | Customer Next Best Action |
| Customer Verification | Customer Journey Analytics |
| Sales Intelligence | Customer Sentiment Analysis |
| Marketing Campaign Effectiveness Prediction | Customer Onboarding Experience |
| Document Intelligence (ICR/OCR/OMR) | Customer Spend Analytics |
| Payment Default Prediction | Conversational Banking |
| Real-time Transaction Monitoring | Conversational AI for Contact Centers |
| Loan Default Prediction | Single View of a Customer |
| Credit Risk and Delinquency Prediction | Lead Intelligence for Customer Acquisition |
| Branch Performance Optimization | Customer Segmentation |
| Compliance Monitoring and Reporting | Customer Profitability Prediction |
| Knowledge Management | Customer Click Stream Analytics |
A Strategic Approach to Modernization
By strategically embracing modernization, community banks and credit unions can optimize their investments in new technologies and infrastructure. The focus should be on choosing the right tools and technologies to harness the full potential of their data assets, make more calculated business decisions, address specific challenges, and achieve a larger business vision.
Beginning with an assessment of existing tools and resources can be a good first step. Identifying gaps in existing processes and the biggest pain points where modern technology can be beneficial can be the next step. From there, possible areas for automation and modernization can be explored. A review of the industry peers to understand how they are addressing the common challenges can also help in making the right decisions.
As a digital transformation enabler, KANINI offers tailored solutions in data analytics and AI that enable community banks and credit unions to understand their local market more proactively and plan their business strategies accordingly. To know more about how we empower community banks and credit unions to gain a competitive advantage, speak with our experts.
Author
Anand Subramaniam
Anand Subramaniam is the Chief Solutions Officer, leading Data Analytics & AI service line at KANINI. He is passionate about data science and has championed data analytics practice across start-ups to enterprises in various verticals. As a thought leader, start-up mentor, and data architect, Anand brings over two decades of techno-functional leadership in envisaging, planning, and building high-performance, state-of-the-art technology teams.
