This blog was co-authored by Perficient banking expert: Scott Albahary
A slowing global economy, coupled with a divergent economic landscape, poses challenges for the banking industry in 2024. Driven by technological advancements, regulatory changes, and shifting consumer preferences, the banking industry must evolve and respond accordingly.
As institutions adapt, Perficient’s financial services expert, Scott Albahary, has identified six key trends to shape the banking landscape in the year ahead.
1. Credit Scoring and Decisioning
Influenced by the pandemic and subsequent economic shifts, has necessitated a more sophisticated approach to credit scoring and decision-making. Banking institutions are responding by integrating advanced technologies, particularly artificial intelligence and data analytics, into their lending operations to enhance efficiency and adaptability.
The emergence of modern alternatives to traditional credit scoring signifies a broader movement toward financial inclusion. By harnessing alternative data sources and supplementing conventional credit reports, institutions can offer fairer assessments of creditworthiness, extending credit opportunities to underserved populations. Through the analysis of diverse data sets, automation of loan processing, and consideration of varied factors, financial institutions are not only increasing customer satisfaction and reducing operational costs but also fostering resilience in the face of evolving economic landscapes.
Going forward, banks should:
- Implement AI-driven systems to streamline credit decision processes, reducing decision times, and enabling faster responses to loan applications.
- Utilize advanced algorithms and data analytics to enhance risk assessment methodologies, allowing banks to identify and mitigate default risks more effectively, thereby making more informed lending decisions.
- Leverage data analytics tools to optimize portfolio performance by identifying trends, patterns, and potential risks, enabling banks to make proactive adjustments and maximize returns.
- Explore and integrate alternative data sources and innovative scoring models to offer fairer assessments of creditworthiness. This approach extends credit opportunities to traditionally underserved populations, promoting financial inclusion within the banking sector.
2. Embedded Finance
Embedded finance, characterized by the integration of financial products into non-financial apps or websites, is gaining significant traction, especially in the commercial side of the banking industry. As new regulations come into play, embedded lending is becoming increasingly prevalent, highlighting the need for banks to leverage data analytics and automation effectively while ensuring compliance with regulatory standards.
Embedded finance offers banks in the commercial sector numerous advantages, including:
- Smooth integration of financial services: Embedding financial services into non-financial platforms allows for seamless integration, providing customers with a unified experience.
- Enhanced consumer access to credit: Enables consumers to access credit more conveniently, thereby improving the accessibility and usability of financial products.
- Increased data analytics: Recognizing the importance of data analytics and automation is pivotal in successfully implementing embedded finance solutions. Intelligent automation and other data analytic tools enable banks to optimize processes, enhance decision-making, and improve customer experiences.
- Facilitation of embedded lending while ensuring compliance: Embedded finance initiatives must adhere to regulatory requirements. By prioritizing compliance alongside embedded lending, banks can mitigate risks and ensure trust in their financial services offerings.
3. Banking Rewards and Loyalty Programs
Throughout the year, banking rewards and loyalty programs will take on increased significance, highlighting the critical role of personalization in enhancing customer retention and maintaining competitiveness in the face of external pressures such as money markets. Banks are recognizing the need to analyze customer data and behavior patterns comprehensively to tailor rewards programs to individual preferences, thereby fostering stronger relationships and increasing loyalty.
To remain relevant and competitive, banks should seriously consider upping their rewards and loyalty programs, ensuring they reflect the following characteristics:
- Showcasing individualized incentives, preferences, and rewards based on customers’ unique spending habits and behaviors. Personalization not only enhances the customer experience but also strengthens the bond between banks and their clientele.
- Offering customized loyalty programs that stand out from competitors. By providing unique benefits tailored to specific customer segments, banks can attract and retain customers more effectively.
- Understanding customers’ preferences and behaviors allows banks to deliver tailored experiences that resonate with individuals, ultimately driving loyalty and long-term engagement.
As conversations around the competitive landscape intensify, banks must prioritize enhancing their rewards and loyalty programs to not only retain existing customers but also attract new ones. By embracing personalization and customization, banks can strengthen their position in the market and build lasting relationships with customers.
Improve the Customer Experience: Our Success in Action
Our client sought ways to improve its feedback processes to more accurately collect and respond to feedback, both internally and externally. We implemented artificial intelligence (AI) and natural language process solutions to analyze feedback across multiple channels. The system can accurately identify feedback across claims, sales, and internal employees, and resulted in data being processed 5 times more efficiently and a 98% reduction in response time.
4. Operational Resiliency
In an environment marked by heightened regulatory scrutiny and evolving customer expectations, operational resilience stands as a paramount concern for banks. To address this, institutions are increasingly turning to technology-driven solutions aimed at enhancing service reliability, compliance, and security.
The controlled integration of AI, intelligent automation, and machine learning empowers banks to achieve the following:
- Leveraging AI and machine learning enables banks to deliver personalized services, thereby enhancing customer satisfaction and fostering loyalty.
- Automation of tasks not only reduces costs and errors but also liberates resources for higher-value activities, thus streamlining operational efficiency.
- Empowers banks with actionable insights, enabling faster and more informed decision-making processes.
- Instrumental in proactively identifying potential risks and issuing alerts, thereby enhancing the institution’s ability to respond swiftly and mitigate adverse outcomes.
Perficient’s Expertise
A client needed to improve its loan operations to overcome challenges with productivity reporting, system maintenance, and time-consuming compliance processes. We facilitated a low-risk, efficient transition from a legacy enterprise content management platform to IBM FileNet P8 and enhanced the P8 environment with Trex, our proprietary transaction-processing application framework.
The solution automated content-centric workflows for loan documentation review, loan operations, quality assurance, and closed loan processing.
5. Debt Collections
During times of financial difficulty, considered customer communications are essential. Modern technologies, such as machine learning models, offer banks the opportunity to enhance efficiency and compliance throughout the debt collection process.
AI-powered debt collections allow banks to achieve to meet objectives, such as:
- Facilitating faster resolution of outstanding debts: Automating routine tasks like reminders, follow-ups, and data analysis, streamlines the debt collection process and enhances operational efficiency while ensuring adherence to compliance standards.
- Tailoring collection strategies: Personalization is key in debt collections. AI enables banks to tailor collection strategies based on individual circumstances, thereby increasing the likelihood of successful debt recovery while preserving positive customer relationships.
- Utilizing more data analytics: Through the analysis of vast data sets, AI technologies identify trends, predict payment behavior, and optimize collection strategies. This data-driven approach empowers banks to make informed decisions and allocate resources effectively, enhancing overall debt recovery outcomes.
- Ensuring regulatory compliance: AI-driven debt collection systems standardize collection practices and flag potential risks, thereby reducing legal and reputational liabilities associated with debt collection activities. By ensuring compliance with regulations, banks mitigate risks and maintain trust with customers and regulatory authorities alike.
6. Fraud Detection
Banks are increasingly turning to AI-powered solutions to effectively detect and prevent fraudulent activities. Through advanced AI algorithms, banks can swiftly identify and mitigate emerging fraud risks while ensuring regulatory compliance and safeguarding customer data. The advent of generative AI introduces disruptive capabilities across industries, particularly in fraud detection and transaction security enhancement. Key advancements include:
- Synthetic Data Generation: By creating synthetic datasets that mirror real-world transactions, banks can train fraud detection models on diverse and realistic data sets without compromising customer privacy. This approach enables banks to enhance the robustness and accuracy of their fraud detection systems.
- Novel Pattern Detection: AI-powered systems excel in uncovering previously unseen patterns and anomalies within transaction data. By leveraging these capabilities, banks can enhance the effectiveness of their fraud detection systems by identifying emerging fraud schemes and swiftly adapting to evolving threats. This proactive approach strengthens the overall security posture of banks and mitigates potential financial losses due to fraudulent activities.
Looking Ahead
The banking industry in 2024 is characterized by innovation, resilience, and a relentless focus on customer-centricity. By embracing emerging technologies, leveraging data analytics, and adapting to regulatory changes, banks can position themselves for sustainable growth and success in the coming year.
Staying ahead of these trends will be critical for banks to meet the needs and expectations of their customers while driving operational excellence and mitigating risks effectively.
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