Careers
Work with us
Category: Gen AI

AI’s Mid-Market Makeover in Financial Services

Blanc Labs

AI’s Mid-Market Makeover in Financial Services

hero

Summary

Mid-sized financial services institutions (FIs) are facing significant challenges during this period of rapid technological change, particularly with the rise of artificial intelligence (AI). As customer expectations grow, smaller banks and lenders must stay competitive and responsive. Canada’s largest financial institutions are already advancing in AI, while many others remain in ‘observer’ mode, hesitant to invest and experiment. Yet, mid-sized FIs that adopt the right strategy have unique agility, allowing them to adapt swiftly and efficiently to technological disruptions—even more so than their larger counterparts.

This report explores how AI can tackle these challenges by transforming operations and generating substantial value across departments and business lines. We present a detailed approach for identifying, prioritizing, and implementing AI use cases, empowering mid-sized financial institutions to maintain a competitive edge in the fast-changing financial industry.

AI offers a major opportunity to enhance productivity, personalize customer interactions, improve decision-making, and create new business models. Successful AI integration requires a balanced, strategic approach that aligns with business goals and carefully evaluates potential risks.

Several challenges facing mid-sized financial services companies

In a time of rapid technological advancements and changing market conditions, mid-sized financial services companies are at a crossroads. They must meet rising customer expectations and deal with growing competition, presenting them with unique challenges that can either hinder their growth or drive them to seek new opportunities. Here are the top four challenges in this area:

Rising Customer Expectations

Competitive Pressures

Workforce Dynamics and People Constraints

Technology and AI Disruption

In this exploration, we look at how mid-sized FIs can use AI to overcome challenges and improve operations and customer engagement. In a following article, we will prioritize AI use cases to help these institutions make informed decisions. 

Creating Value Across All Departments

Amid the challenges faced by mid-sized financial firms, AI stands out as a key driver of progress. It enables transformative change, boosts operational efficiency, personalizes customer interactions, enhances decision-making, and fosters the development of new business models. By addressing these challenges, AI has the potential to create significant differentiation and impact every aspect of the business.

Here’s how AI can boost businesses:

Productivity Customer Decision making Business model
Increase Productivity and Efficiency Personalize Customer Experiences Augment Decision Making Invent New Business Models

Increase Productivity & Efficiency

AI-driven tools are revolutionizing operational workflows by streamlining processes and reducing manual intervention. Through intelligent document processing, regulatory compliance monitoring, and process automation, financial services firms can achieve unprecedented levels of productivity. By leveraging AI-powered copilots to augment humans in tasks like email management and coding modernization, organizations can optimize their day-to-day operations and enable their workforce to focus on higher-value activities.

Personalize Customer Experience

In today’s competitive market, personalization is key to customer satisfaction, and AI is at the forefront of this capability. With AI-powered sentiment analysis and recommendation engines, financial services companies can tailor services and products to meet individual customer needs more effectively. Furthermore, AI-driven customer engagement tools, from text-to-video communications to generative experiences, enable businesses to create seamless, personalized journeys that enhance customer loyalty and retention.

Augment Decision Making

AI augments decision-making processes by providing real-time, data-driven insights that enhance business strategies. From underwriting assistance to dynamic pricing and risk scoring, AI enables financial institutions and other businesses to make informed decisions faster and more accurately. By integrating AI in areas like fraud detection and smart financial advisory, companies can mitigate risks while optimizing their decision-making processes, leading to improved outcomes and competitive advantage.

Invent New Business Models

AI is not just about optimizing existing processes; it also drives the creation of entirely new business models. For example. the advent of AI-powered embedded finance and autonomous lending platforms demonstrates how AI can unlock new revenue streams and business opportunities. Through insights-as-a-service offerings and new partnership value streams, organizations can capitalize on their data, leverage AI to explore untapped markets, and invent business models that could disrupt traditional banks and lenders.

In a subsequent article, we’ll explore these topics in depth, breaking them down with detailed explanations and real-world use cases.

GenAI Value Creation: Aspiration vs. Reality

As financial institutions navigate the complex landscape of AI adoption, two distinct sentiments emerge, each underpinned by its own set of expectations and concerns.

On one hand, the optimists in the financial sector view GenAI as a revolutionary force capable of driving significant industry changes. This group is excited by the potential for:

True Hyper-personalization: Tailoring products and services to individual preferences and needs for every single customer.

Maximum Customer Experience: Leveraging conversational AI to improve service quality and user engagement across all channels.

Automation Everywhere: Implementing AI-driven processes to streamline operations and reduce the need for manual and paper-based work.

Giant Productivity Leaps: Increasing efficiency & effectiveness across all organizational levels, by augmenting employees to focus on the highest value activities.

Zero-Fraud Financial Systems: Using advanced AI algorithms to detect and prevent fraud in real-time.

These optimists are encouraged by projections suggesting that GenAI could unlock over $1 trillion in banking revenue by 2030[1], signaling a major shift in how financial services are structured and delivered. Moreover, 75% of executives anticipate that GenAI will drive disruptive changes within the industry over the next three years.[2]

Conversely, the skeptics approach GenAI with caution, emphasizing the potential pitfalls over the promised perks. Their concerns include:

Boom & Bust Cycles: Risk of overinvestments driving unsustainable growth, low ROI, and financial problems down the road, as was the case with several technology waves in the past decades.

Reliability Issues: Worries about the limitations and flaws of new GenAI technologies, and their impact on mission-critical financial processes where the room for error is very small.

Regulatory Constraints: Challenges to AI growth due to evolving, stringent regulations across local and federal jurisdictions in financial services.

Security and Privacy Risks: Increased risk of cyber threats, data privacy concerns, and potential bias as AI continues to handle and process more sensitive information on customers and employees.

Overpromise, Underdeliver: Many worry about the prospect of AI failing to meet the current hype, and see in it an over-marketed tech that is less revolutionary that it seems.

Interestingly, despite the much touted prospects of AI, a significant 66% of executives surveyed express ambivalence or dissatisfaction with their organization’s progress in AI integration, highlighting a gap between expectation and execution.[3]

Embracing AI Optimism with Prudence

Broadening Our AI Understanding
Evaluating AI’s Imperfections
Looking Beyond the Present
Avoiding Common Pitfalls

AI encompasses a wide array of tools and capabilities, including battle-tested solutions based on both predictive and generative AI. Recognizing the full range of AI technologies will enable us to leverage the most effective solutions for our specific needs.

Like humans, AI is not infallible—it makes mistakes. However, combining human oversight with GenAI’s capabilities could enhance our decision-making processes beyond what’s achievable by human efforts alone.

The rapid progress of AI means what’s cutting-edge today might be outdated tomorrow. We should consider the potential of future AI developments, much like how each model (e.g. GPT-4o) has expanded on the capabilities of its predecessors. Looking into the not-so-distant future, imagine what GPT-14 would be capable of vs. GPT-4.

AI isn’t a one-size-fits-all solution, and should not be treated solely as a technology problem. Rather than adopting AI for its own sake, it’s vital to focus on strategic AI use cases that align with our specific business goals.

The Spectrum of AI Adoption in Financial Services: Where Companies Stand

In the financial services sector, firms vary significantly in their approach and adoption of artificial intelligence. This diversity is best understood through four distinct groups: Observers, Experimenters, Implementers, and Innovators. Each category defines the group’s current engagement with AI technologies and also underscores its strategic vision and operational readiness for future disruptions.

 

new-chart

Observers

Many observers are choosing to wait for large, proven returns on investment (ROI) and clearer technology convergence before diving into AI. While this cautious stance lets them learn from early adopters, it risks putting these FIs behind competitors who are seizing AI-driven advantages now.

Experimenters

Experimenting FIs are cautiously dipping their toes into AI through small-scale projects and pilot programs, testing the waters to gauge capabilities and potential benefits without diving into full-scale implementation. This approach nurtures a culture of learning and adaptability, but without a comprehensive strategy, its impact and scalability may remain limited.

Implementers

Implementers are more advanced in their AI journey, embedding AI systems within specific departments and processes to generate tangible business value. These FIs are building significant AI capabilities and gaining advantages in differentiation and operational efficiency. However, their challenge is to scale these benefits across the entire organization to prevent siloed success and ensure widespread impact.

Innovators

Innovators are embedding comprehensive AI strategies across their business models, reshaping their operations and potentially revolutionizing the financial services industry for a powerful competitive edge. However, this ambitious approach comes with heightened risks and substantial investments, making the journey to success both challenging and uncertain.

Competitive AI Landscape: Lessons from Canada’s Big Financial Institutions 

As mid-sized FIs consider the question of AI, it’s crucial to recognize the significant strides made by Canada’s largest banks. Notably, three of the Big Five banks are ranked among the top ten globally for AI maturity [4], showcasing their leadership in using AI to transform financial services. Here’s how some of these banks are creating competitive advantage with AI: 

Ranked among the top three globally for AI maturity, RBC owns Borealis AI, a dedicated research and development institute. It has launched AI-driven products like Aiden for trading and NOMI for personal finance management, and utilizes AI to enhance internal processes and modernize legacy systems. 
With its AI R&D center, Layer 6, TD has grown its AI talent to over 200 professionals and is developing over 50 AI solutions across its business lines. It is the leading patent filer in AI among Canadian FIs (450+ AI-related patent filings) and uses predictive AI models to pre-approve mortgages in seconds, demonstrating a strong commitment to integrating AI across its operations.[5]
Winner of the Best Gen-AI Initiative by The Digital Banker 2024, CIBC has developed its own custom built ‘CIBA AI system to improve productivity and enable staff to focus on high-value activities. The introduction of tools like GitHub CoPilot boosts developer efficiency, and the bank plans to significantly expand its data and AI workforce by hiring 200+ related roles over the next 12 months.[6]
Scotiabank’s customer-facing AI chatbot handles 40% of queries with a 90% accuracy rate and has significantly sped up agent training. The bank has also launched a global AI platform to enhance customer insights across all touchpoints and employs large language models to improve employee experiences.[7]
BMO considers AI integral to its bank strategy. Its mobile app provides AI-driven personalized insights to improve customer engagement, its ‘Digital Workbench’ offers real-time analytics for commercial clients, and its contact centers’ service quality is boosted through NLP tech. Last year, it upskilled over 3,500 employees through learning & development programs centered on AI and cloud. Externally, BMO demonstrated commitment to AI by sponsoring the ‘Next AI accelerator.[8]

 

Strategic Imperative for Mid-Sized FIs 

The AI advancements by Canada’s largest banks illustrate a clear trend: AI is not just a technological upgrade but a strategic necessity. Mid-sized FIs must recognize the need to keep pace and innovate beyond traditional technologies and models. Key actions for staying ahead include: 

  1. Accelerated AI Adoption and Scale-Up: Mid-sized FIs need to prioritize their own AI roadmaps and seek opportunities to rapidly scale adoption of AI solutions across various departments. 
  2. Target High-Value AI Applications: Focus on areas where AI can quickly deliver the most significant returns, such as improving customer experience and increasing operational efficiency – before exploring how AI can enable the development of new financial products & services. 
  3. Invest in AI Talent and Partnerships: Expand internal capabilities by hiring AI specialists and consider partnerships with AI tech & service providers to tap into external expertise. 
  4. Monitor and Adapt Best Practices: Keep a close eye on industry leaders and continuously adapt their AI best practices to suit smaller scale operations and unique market demands. 

By embracing these strategies, mid-sized FIs can respond to the competitive pressures exerted by larger banks and carve out their own niche in the rapidly evolving financial landscape. 

Competitive AI Landscape: Lessons from Canada’s Big Financial Institutions 

As mid-sized FIs consider the question of AI, it’s crucial to recognize the significant strides made by Canada’s largest banks. Notably, three of the Big Five banks are ranked among the top ten globally for AI maturity [4], showcasing their leadership in using AI to transform financial services. Here’s how some of these banks are creating competitive advantage with AI: 

Ranked among the top three globally for AI maturity, RBC owns Borealis AI, a dedicated research institute. It has launched AI-driven products like Aiden for trading and NOMI for personal finance management, and utilizes AI to enhance internal processes and modernize legacy systems. 

With its AI R&D center, Layer 6, TD has grown its AI talent to over 200 professionals and is developing over 50 AI solutions across its business lines. It is the leading patent filer in AI among  Canadian FIs (450+ AI-related patent filings) and uses predictive AI models to pre-approve mortgages in seconds, demonstrating a strong commitment to integrating AI across its operations.[5]

Winner of the Best Gen-AI Initiative by The Digital Banker 2024, CIBC has developed its own custom built ‘CIBA AI system to improve productivity and enable staff to focus on high-value activities. The introduction of tools like GitHub CoPilot boosts developer efficiency, and the bank plans to significantly expand its data and AI workforce by hiring 200+ related roles over the next 12 months.[6]

Scotiabank’s customer-facing AI chatbot handles 40% of queries with a 90% accuracy rate and has significantly sped up agent training. The bank has also launched a global AI platform to enhance customer insights across all touchpoints and employs large language models to improve employee experiences.[7]

BMO considers AI integral to its bank strategy. Its mobile app provides AI-driven personalized insights to improve customer engagement, its ‘Digital Workbench’ offers real-time analytics for commercial clients, and its contact centers’ service quality is boosted through NLP tech. Last year, it upskilled over 3,500 employees through learning & development programs centered on AI and cloud. Externally, BMO demonstrated commitment to AI by sponsoring the ‘Next AI accelerator.[8]

 

Strategic Imperative for Mid-Sized FIs 

The AI advancements by Canada’s largest banks illustrate a clear trend: AI is not just a technological upgrade but a strategic necessity. Mid-sized FIs must feel the urgency to not only catch up but also innovate beyond traditional models to remain competitive. The following strategic actions are recommended: 

  1. Rapid AI Adoption and Scale-Up: Mid-sized FIs need to prioritize AI adoption and seek opportunities to scale AI solutions across their operations quickly. 
  2. Focus on High-Impact AI Applications: Identify areas where AI can create significant value, such as enhancing customer experience, improving operational efficiency, and developing new financial products. 
  3. Invest in AI Talent and Partnerships: Expand internal capabilities by hiring AI specialists and consider partnerships with AI tech & services firms to leverage external expertise. 
  4. Monitor and Adapt Best Practices: Keep a close eye on industry leaders and continuously adapt their AI best practices to suit smaller scale operations and unique market demands.

 

By embracing these strategies, mid-sized FIs can respond to the competitive pressures exerted by larger banks and carve out their own niche in the rapidly evolving financial landscape. 

Conclusion

The financial services industry is at a turning point, especially for mid-sized FIs. Adopting AI is no longer a choice but a necessity to remain competitive and meet the growing demands of the market. With extensive experience working with mid-sized FIs, Blanc Labs recognizes the transformative potential AI brings—from boosting operational efficiency to tailoring customer experiences and introducing new business models. As technology continues to advance at a rapid pace, it’s crucial that these institutions take decisive action to leverage these tools. By embracing AI now, your organization can gain a competitive advantage, fuel growth, and position itself for long-term success in an increasingly fast-paced industry. 

The next article in this series will explore real-world examples of AI in action within financial services and offer a structured approach to identifying and prioritizing the most impactful AI applications for mid-sized FIs.

Latest Insights

Financial Services
Advisory Services
Digital Transformation for Lenders
Articles

Lenders Transformation Playbook: Bridging Strategy and Execution

October 08, 2024
Learn More
Financial Services
AI
Artificial Intelligence
Articles

AI’s Mid-Market Makeover in Financial Services

October 07, 2024
Learn More
hero

Mid-sized financial services institutions (FIs) are facing significant challenges during this period of rapid technological change, particularly with the rise of artificial intelligence (AI). As customer expectations grow, smaller banks and lenders must stay competitive and responsive. Canada’s largest financial institutions are already advancing in AI, while many others remain in ‘observer’ mode, hesitant to invest and experiment. Yet, mid-sized FIs that adopt the right strategy have unique agility, allowing them to adapt swiftly and efficiently to technological disruptions—even more so than their larger counterparts.

Financial Services
Automation
BPI
Case Studies

Process Improvement and Automation Support the Mission at Trez Capital 🚀

July 29, 2024
Read Now
Trez Capital

Trez distributes capital based on very specific criteria. But with over 300 investments in their portfolio, they process numerous payment requests and deal with documents in varied data formats. They saw an opportunity to enhance efficiency, improve task management, and better utilize data insights for strategic decision-making.

Financial Services
AI
Digital Transformation
Articles

Align, Assemble, Assure: A Framework for AI Adoption

May 09, 2024
Learn More

An in-depth guide for adopting and scaling AI in the enterprise using actionable and measurable steps.

Financial Services
Advisory Services
Artificial Intelligence
Articles

Blanc Labs Welcomes Two New Leaders to Advance AI Innovation and Enhance Tech Advisory Services for Financial Institutions Across North America

May 07, 2024
Learn More

Blanc Labs and TCG Process have partnered to transform lending operations with innovative automation solutions, using the DocProStar platform to enhance efficiency, compliance, and customer satisfaction in the Canadian lending market.

Financial Services
Banking Automation
Enterprise Automation
Articles

Blanc Labs Partners with TCG Process to Integrate their Automation and Orchestration Platform and deliver Advanced Intelligent Workflow Automation to Financial Institutions

May 03, 2024
Learn More

Blanc Labs and TCG Process have partnered to transform lending operations with innovative automation solutions, using the DocProStar platform to enhance efficiency, compliance, and customer satisfaction in the Canadian lending market.

Financial Services
Business Process Improvement
Enterprise Automation
Articles

BPI in Banking and Financial Services in the US & Canada

April 23, 2024
Learn More
Business Process Improvement in Financial Services in US & Canada

Banking and financial services are changing fast. Moving from old, paper methods to new, digital ones is key to staying in business. It’s important to think about how business process improvement (BPI) can help.

Financial Services
Banking Automation
Business Process Improvement
Articles

Business Process Improvement vs Business Process Reengineering 

April 08, 2024
Learn More

Business process improvement vs. reengineering is a tough choice. In this guide, we help you choose between the two based on four factors.

Financial Services
Business Process Improvement
Articles

What is the role of a Business Process Improvement Specialist? 

February 16, 2024
Learn More
Business Process Improvement Specialist in Canada

A business process improvement specialist identifies bottlenecks and inefficiencies in your workflows, allowing you to focus efforts on automating the right processes.

Financial Services
API Management
Open Banking
Financial Services

Open Banking Technology Architecture Whitepaper

February 13, 2024
Learn More

We’ve developed this resource to help technical teams adopt an Open Banking approach by explaining a high-level solution architecture that is organization agnostic.

Insight
AI
Enterprise Automation
Articles

These are not your grandmother’s models: the impact of LLM’s on Document Processing

January 22, 2024
Learn More
These are not your grandmother’s models: the impact of Large Language Models on Document Processing

Explore the transformative influence of large language models (LLMs) on document processing in this insightful article. Discover how these cutting-edge models are reshaping traditional approaches, unlocking new possibilities in data analysis, and revolutionizing the way we interact with information.

Financial Services
API Management
Digital Banking
Articles

Finding the right API Management Platform

November 03, 2022
Learn More
Financial Services
API Management
Digital Banking
Articles

5 Factors to Evaluate Open Banking Readiness in Canada

September 28, 2022
Learn More
Financial Services
API Management
Digital Banking
Articles

Open Banking in Canada: How Banks and Customers Can Benefit

September 15, 2022
Learn More
Financial Services
API Management
Digital Banking
Articles

4 Ways APIs Can Improve Your Bank

June 08, 2022
Learn More
Financial Services
Banking Automation
Digital Transformation
Articles

Challenges in Digital Lending

May 12, 2022
Learn More
Financial Services
Advisory Services
Digital Transformation for Lenders
Articles

Lenders Transformation Playbook: Bridging Strategy and Execution

October 08, 2024
Learn More
Financial Services
AI
Artificial Intelligence
Articles

AI’s Mid-Market Makeover in Financial Services

October 07, 2024
Learn More
hero

Mid-sized financial services institutions (FIs) are facing significant challenges during this period of rapid technological change, particularly with the rise of artificial intelligence (AI). As customer expectations grow, smaller banks and lenders must stay competitive and responsive. Canada’s largest financial institutions are already advancing in AI, while many others remain in ‘observer’ mode, hesitant to invest and experiment. Yet, mid-sized FIs that adopt the right strategy have unique agility, allowing them to adapt swiftly and efficiently to technological disruptions—even more so than their larger counterparts.

Financial Services
Automation
BPI
Case Studies

Process Improvement and Automation Support the Mission at Trez Capital 🚀

July 29, 2024
Read Now
Trez Capital

Trez distributes capital based on very specific criteria. But with over 300 investments in their portfolio, they process numerous payment requests and deal with documents in varied data formats. They saw an opportunity to enhance efficiency, improve task management, and better utilize data insights for strategic decision-making.

Financial Services
AI
Digital Transformation
Articles

Align, Assemble, Assure: A Framework for AI Adoption

May 09, 2024
Learn More

An in-depth guide for adopting and scaling AI in the enterprise using actionable and measurable steps.

Financial Services
Advisory Services
Artificial Intelligence
Articles

Blanc Labs Welcomes Two New Leaders to Advance AI Innovation and Enhance Tech Advisory Services for Financial Institutions Across North America

May 07, 2024
Learn More

Blanc Labs and TCG Process have partnered to transform lending operations with innovative automation solutions, using the DocProStar platform to enhance efficiency, compliance, and customer satisfaction in the Canadian lending market.

Financial Services
Banking Automation
Enterprise Automation
Articles

Blanc Labs Partners with TCG Process to Integrate their Automation and Orchestration Platform and deliver Advanced Intelligent Workflow Automation to Financial Institutions

May 03, 2024
Learn More

Blanc Labs and TCG Process have partnered to transform lending operations with innovative automation solutions, using the DocProStar platform to enhance efficiency, compliance, and customer satisfaction in the Canadian lending market.

Financial Services
Business Process Improvement
Enterprise Automation
Articles

BPI in Banking and Financial Services in the US & Canada

April 23, 2024
Learn More
Business Process Improvement in Financial Services in US & Canada

Banking and financial services are changing fast. Moving from old, paper methods to new, digital ones is key to staying in business. It’s important to think about how business process improvement (BPI) can help.

Financial Services
Banking Automation
Business Process Improvement
Articles

Business Process Improvement vs Business Process Reengineering 

April 08, 2024
Learn More

Business process improvement vs. reengineering is a tough choice. In this guide, we help you choose between the two based on four factors.

Financial Services
Business Process Improvement
Articles

What is the role of a Business Process Improvement Specialist? 

February 16, 2024
Learn More
Business Process Improvement Specialist in Canada

A business process improvement specialist identifies bottlenecks and inefficiencies in your workflows, allowing you to focus efforts on automating the right processes.

Financial Services
API Management
Open Banking
Financial Services

Open Banking Technology Architecture Whitepaper

February 13, 2024
Learn More

We’ve developed this resource to help technical teams adopt an Open Banking approach by explaining a high-level solution architecture that is organization agnostic.

Insight
AI
Enterprise Automation
Articles

These are not your grandmother’s models: the impact of LLM’s on Document Processing

January 22, 2024
Learn More
These are not your grandmother’s models: the impact of Large Language Models on Document Processing

Explore the transformative influence of large language models (LLMs) on document processing in this insightful article. Discover how these cutting-edge models are reshaping traditional approaches, unlocking new possibilities in data analysis, and revolutionizing the way we interact with information.

Financial Services
API Management
Digital Banking
Articles

Finding the right API Management Platform

November 03, 2022
Learn More
Financial Services
API Management
Digital Banking
Articles

5 Factors to Evaluate Open Banking Readiness in Canada

September 28, 2022
Learn More
Financial Services
API Management
Digital Banking
Articles

Open Banking in Canada: How Banks and Customers Can Benefit

September 15, 2022
Learn More
Financial Services
API Management
Digital Banking
Articles

4 Ways APIs Can Improve Your Bank

June 08, 2022
Learn More
Financial Services
Banking Automation
Digital Transformation
Articles

Challenges in Digital Lending

May 12, 2022
Learn More
Financial Services
Advisory Services
Digital Transformation for Lenders
Articles

Lenders Transformation Playbook: Bridging Strategy and Execution

October 08, 2024
Learn More
Financial Services
AI
Artificial Intelligence
Articles

AI’s Mid-Market Makeover in Financial Services

October 07, 2024
Learn More
hero

Mid-sized financial services institutions (FIs) are facing significant challenges during this period of rapid technological change, particularly with the rise of artificial intelligence (AI). As customer expectations grow, smaller banks and lenders must stay competitive and responsive. Canada’s largest financial institutions are already advancing in AI, while many others remain in ‘observer’ mode, hesitant to invest and experiment. Yet, mid-sized FIs that adopt the right strategy have unique agility, allowing them to adapt swiftly and efficiently to technological disruptions—even more so than their larger counterparts.

Financial Services
Automation
BPI
Case Studies

Process Improvement and Automation Support the Mission at Trez Capital 🚀

July 29, 2024
Read Now
Trez Capital

Trez distributes capital based on very specific criteria. But with over 300 investments in their portfolio, they process numerous payment requests and deal with documents in varied data formats. They saw an opportunity to enhance efficiency, improve task management, and better utilize data insights for strategic decision-making.

Financial Services
AI
Digital Transformation
Articles

Align, Assemble, Assure: A Framework for AI Adoption

May 09, 2024
Learn More

An in-depth guide for adopting and scaling AI in the enterprise using actionable and measurable steps.

Financial Services
Advisory Services
Artificial Intelligence
Articles

Blanc Labs Welcomes Two New Leaders to Advance AI Innovation and Enhance Tech Advisory Services for Financial Institutions Across North America

May 07, 2024
Learn More

Blanc Labs and TCG Process have partnered to transform lending operations with innovative automation solutions, using the DocProStar platform to enhance efficiency, compliance, and customer satisfaction in the Canadian lending market.

Financial Services
Banking Automation
Enterprise Automation
Articles

Blanc Labs Partners with TCG Process to Integrate their Automation and Orchestration Platform and deliver Advanced Intelligent Workflow Automation to Financial Institutions

May 03, 2024
Learn More

Blanc Labs and TCG Process have partnered to transform lending operations with innovative automation solutions, using the DocProStar platform to enhance efficiency, compliance, and customer satisfaction in the Canadian lending market.

Financial Services
Business Process Improvement
Enterprise Automation
Articles

BPI in Banking and Financial Services in the US & Canada

April 23, 2024
Learn More
Business Process Improvement in Financial Services in US & Canada

Banking and financial services are changing fast. Moving from old, paper methods to new, digital ones is key to staying in business. It’s important to think about how business process improvement (BPI) can help.

Financial Services
Banking Automation
Business Process Improvement
Articles

Business Process Improvement vs Business Process Reengineering 

April 08, 2024
Learn More

Business process improvement vs. reengineering is a tough choice. In this guide, we help you choose between the two based on four factors.

Financial Services
Business Process Improvement
Articles

What is the role of a Business Process Improvement Specialist? 

February 16, 2024
Learn More
Business Process Improvement Specialist in Canada

A business process improvement specialist identifies bottlenecks and inefficiencies in your workflows, allowing you to focus efforts on automating the right processes.

Financial Services
API Management
Open Banking
Financial Services

Open Banking Technology Architecture Whitepaper

February 13, 2024
Learn More

We’ve developed this resource to help technical teams adopt an Open Banking approach by explaining a high-level solution architecture that is organization agnostic.

Insight
AI
Enterprise Automation
Articles

These are not your grandmother’s models: the impact of LLM’s on Document Processing

January 22, 2024
Learn More
These are not your grandmother’s models: the impact of Large Language Models on Document Processing

Explore the transformative influence of large language models (LLMs) on document processing in this insightful article. Discover how these cutting-edge models are reshaping traditional approaches, unlocking new possibilities in data analysis, and revolutionizing the way we interact with information.

Financial Services
API Management
Digital Banking
Articles

Finding the right API Management Platform

November 03, 2022
Learn More
Financial Services
API Management
Digital Banking
Articles

5 Factors to Evaluate Open Banking Readiness in Canada

September 28, 2022
Learn More
Financial Services
API Management
Digital Banking
Articles

Open Banking in Canada: How Banks and Customers Can Benefit

September 15, 2022
Learn More
Financial Services
API Management
Digital Banking
Articles

4 Ways APIs Can Improve Your Bank

June 08, 2022
Learn More
Financial Services
Banking Automation
Digital Transformation
Articles

Challenges in Digital Lending

May 12, 2022
Learn More

Banking Automation: The Complete Guide

Financial Services | AI | Banking Automation | Gen AI | ML

Banking Automation: The Complete Guide

April 6, 2023
Banking Automation

Banks are process-driven organizations. Processes ensure accuracy and consistency across the organization. They are also repetitive. Over the past decade, the transition to digital systems has helped speed up and minimize repetitive tasks. But to prepare yourself for your customers’ growing expectations, increase scalability, and stay competitive, you need a complete banking automation solution.

Systems powered by artificial intelligence (AI) and robotic process automation (RPA) can help automate repetitive tasks, minimize human error, detect fraud, and more, at scale. You can deploy these technologies across various functions, from customer service to marketing.

Many, if not all banks and credit unions, have introduced some form of automation into their operations. According to McKinsey, the potential value of AI and analytics for global banking could reach as high as $1 trillion.

If you are curious about how you can become an AI-first bank, this guide explains how you can use banking automation to transform and prepare your processes for the future.

What is Banking Automation?

Banking automation involves automating tasks that previously required manual effort.

For example, banks have conventionally required staff to check KYC documents manually. However, banking automation helps automatically scan and store KYC documents without manual intervention.

Cost saving is generally one of RPA’s biggest advantages.

According to a Gartner report, 80% of finance leaders have implemented or plan to implement RPA initiatives.

The report highlights how RPA can lower your costs considerably in various ways. For example, RPA costs roughly a third of an offshore employee and a fifth of an onshore employee.

You can make automation solutions even more intelligent by using RPA capabilities with technologies like AI, machine learning (ML), and natural language processing (NLP). According to a McKinsey study, AI offers 50% incremental value over other analytics techniques for the banking industry.

With that in mind, let’s look closely at RPA and how it works.

Generative AI and Banking Automation

The latest trend in banking automation is the use of Generative AI.

According to Insider Intelligence’s ChatGPT and Generative AI in Banking report, generative AI will have the greatest impact on data-rich sectors such as:

  • Retail banking and wealth: Generative AI can create more accurate NLP models and help automated systems process KYC documents and open accounts faster.
  • SMB banking: Generative AI can help interpret non-numeric data, like business plans, more effectively.
  • Commercial banking: Generative AI will enable customers to get answers about financial performance in complex scenarios.
  • Investing banking and capital markets: Banks could use generative AI to stress test balance sheets with complex and illiquid assets.

Banks are already using generative AI for financial reporting analysis & insight generation. According to Deloitte, some emerging banking areas where generative AI will play a key role include fraud simulation & detection and tax and compliance audit & scenario testing.

What is RPA?

Robotic process automation, or RPA, is a technology that performs actions generally performed by humans manually or with digital tools.

Say you have a customer onboarding form in your banking software. You must fill it out each time a customer opens an account. You’re manually performing a task using a digital tool.

RPA can perform this task without human effort. The difference? RPA does it more accurately and tirelessly—software robots don’t need eight hours of sleep or coffee breaks.

You can implement RPA quickly, even on legacy systems that lack APIs or virtual desktop infrastructures (VDIs).

Implementing RPA can help improve employee satisfaction and productivity by eliminating the need to work on repetitive tasks.

You can use RPA in banking operations for various purposes.

For example, Credigy, a multinational financial organization, has an extensive due diligence process for consumer loans.

The process was prone to errors and time-consuming. The company decided to implement RPA and automate the entire process, saving their staff and business partners plenty of time to focus on other, more valuable opportunities.

The Need for Automation in Banking Operations

Banks need automation to:

  • Deliver better customer experiences
  • Increase online security
  • Improve decision making
  • Empowering employees

Below, are more reasons for your bank to automate operations.

Why Banks Need Automation

To Deliver Faster, Personalized Customer Experiences

New-gen customers want banks that can provide fast financial services online.

The 2021 Digital Banking Consumer Survey from PwC found that 20%-25% of consumers prefer to open a new account digitally but can’t.

Thanks to the pandemic, the shift to digital has picked up pace. A digital portal for banking is almost a non-negotiable requirement for most bank customers.

In fact, 70% of Bank of America clients engage with the bank digitally. The bank’s newsroom reported that a whopping 7 million Bank of America customers used Erica, its chatbot, for the first time during the pandemic.

A chatbot can provide personalized support to your customers. A level 3 AI chatbot can collect the required information from prospects that inquire about your bank’s services and offer personalized solutions.

A chatbot is a great way for customers to get answers, but it’s also an excellent way to minimize traffic for your support desk.

To Improve Cybersecurity

Cybersecurity is expensive but is also the #1 risk for global banks according to EY. The survey found that cyber controls are the top priority for boosting operation resilience according to 65% of Chief Risk Officers (CROs) who responded to the survey.

Using automation to create a cybersecurity framework and identity protection protocols can help differentiate your bank and potentially increase revenue. You can get more business from high-value individual accounts and accounts of large companies that expect banks to have a top-notch security framework.

Automating cybersecurity helps take remedial actions faster. For example, the automated system can freeze compromised accounts in seconds and help fast-track fraud investigations.

Of course, you don’t need to implement that automation system overnight. With cloud computing, you can start cybersecurity automation with a few priority accounts and scale over time.

For Better Decision Making

AI and ML algorithms can use data to provide deep insights into your client’s preferences, needs, and behavior patterns.

These insights can improve decision-making across the board. For example, using these insights in your marketing strategy can help hyper-target marketing campaigns and improve returns.

Moreover, these insights help deliver greater value to customers. By making faster and smarter decisions, you’ll be able to respond to customers’ fast-evolving needs with speed and precision.

As a McKinsey article explains, banks that use ML to decide in real-time the best way to engage with customers can increase value in the following ways:

  • Stronger customer acquisition: Automation and advanced analytics help improve customer experience. They help personalize marketing across the customer acquisition journey, which can improve conversions.
  • Higher customer lifetime value: You can increase lifetime value by consistently engaging with customers to strengthen relationships across products and services.
  • Lower operating costs: Banks can reduce costs by fully automating document processing, review, and decision-making.
  • Lower credit risk: Banks can screen customers by analyzing behavior patterns that signal higher default or fraud risk.

To Empower Employees

As you digitize banking processes, you’ll need to train employees. Reskilling employees allows them to use automation technologies effectively, making their job easier.

Your employees will have more time to focus on more strategic tasks by automating the mundane ones. This results in increased employee satisfaction and retention and allows them to focus on things that contribute to your topline — such as building customer relationships, innovating processes, and brainstorming ways to address customers’ most pressing issues.

Challenges Faced by Banks Today

Here are some key challenges that banks face today and how automation can help address them:

Inefficient Manual Processes

Manual processes are time and resource-intensive.

According to the 2021 AML Banking Survey, relying on manual processes hampers a financial organization’s revenue-generating ability and exposes them to unnecessary risk.

The simplest banking processes (like opening a new account) require multiple staff members to invest time. Moreover, the process generates paperwork you’ll need to store for compliance.

While you complete the account opening process, the customer is on standby, waiting to start using their account.

The slow service doesn’t exactly make a great impression. Customers want to be able to start using their accounts faster. If you’re too slow, they’ll find a bank that offers faster service.

Automation helps shorten the time between account application and access. But that’s just one of the processes that automation can speed up.

Technologies like RPA and AI can help fast-track processes across departments, including accounting, customer support, and marketing.

Automation Without Integration

Banks often implement multiple solutions to automate processes. However, often, these systems don’t integrate with other systems.

For end-to-end automation, each process must relay the output to another system so the following process can use it as input.

For example, you can automate KYC verification. But after verification, you also need to store these records in a database and link them with a new customer account. For this, your internal systems need to be integrated.

Connecting banking systems requires APIs. Think of APIs as translators. They help two software solutions communicate with each other. A system can relay output to another system through an API, enabling end-to-end process automation.

Increase in Competition

Canadians want more competition in banking. The competition in banking will become fiercer over the next few years as the regulations become more accommodating of innovative fintech firms and open banking is introduced.

An increase in competition will give customers more power. They’ll demand better service, 24×7 availability, and faster response times.

You’ll need automation to achieve these objectives and make yourself stand out in the crowd.

Benefits of Banking Automatios

Benefits of Automation in Banking

Once you invest in automation, you can expect to derive the following benefits:

Improves Operational Efficiency

An error-free automation system can supercharge operational efficiency.

You’ll have to spend little to no time performing or monitoring the process. Moreover, you’ll notice fewer errors since the risk of human error is minimal when you’re using an automated system.

Implementing automation allows you to operate legacy and new systems more resiliently by automating across your system infrastructure. This increases efficiency, consistency, and speed.

Makes Processes Scalable

Banks noticed how automation could be an excellent investment during the pandemic. As explained in a World Economic Forum (WEF) article:

“Through the combination of a distinct data element with robotics process automation, it is possible to generate client documentation from management tools and archives at a high frequency. Due to its scalability, high volumes can be managed more efficiently.”

The article provides the example of Swiss banks. During the pandemic, Swiss banks like UBS used credit robots to support the credit processing staff in approving requests. The support from robots helped UBS process over 24,000 applications in 24-hour operating mode.

In addition to RPA, banks can also use technologies like optical character recognition (OCR) and intelligent document processing (IDP) to digitize physical mail and distribute it to remote teams.

Cost Reduction

Automation helps reduce costs on multiple fronts:

a. Stationery

80% of banks still favor some form of print statements. The cost of paper used for these statements can translate to a significant amount. Automation and digitization can eliminate the need to spend paper and store physical documents.

b. Human error

Human error can require reworks and cause delays in processing customer requests. Errors can result in direct losses (like a lost sale) and indirect losses (like a lost reputation). Minimizing errors can help reduce the cost associated with human error.

c. Increased employee satisfaction

You’ll spend less per unit with more productive employees. Automation can help improve employee satisfaction levels by allowing them to focus on their core duties.

For example, a sales rep might want to grow by exploring new sales techniques and planning campaigns. They can focus on these tasks once you automate processes like preparing quotes and sales reports.

Working on non-value-adding tasks like preparing a quote can make employees feel disengaged. When you automate these tasks, employees find work more fulfilling and are generally happier since they can focus on what they do best.

Happiness makes people around 12% more productive, according to a recent study by the University of Warwick.

As Professor Sgroi explains, “The driving force seems to be that happier workers use the time they have more effectively, increasing the pace at which they can work without sacrificing quality.

Customer Satisfaction

Automation can help meet customer expectations in various ways.

Speed is one of the most difficult expectations to meet for banks. You want to offer faster service but must also complete due diligence processes to stay compliant. That’s where automation helps.

61% of customers feel a quick resolution is vital to customer service. As a bank, you need to be able to answer your customers’ questions fast.

How fast? Ideally, in real-time.

A level 3 AI chatbot can help provide real-time, personalized responses to your customers’ questions.

In addition to real-time support, modern customers also demand fast service. For example, customers should be able to open a bank account fast once they submit the documents. You can achieve this by automating document processing and KYC verification.

Better Risk Management

Automation can help minimize operational, compliance, and fraud risk.

Since little to no manual effort is involved in an automated system, your operations will almost always run error-free.

You can also automate compliance processes. For example, you can add validation checkpoints to ensure the system catches any data irregularities before you submit the data to a regulatory authority.

Automation can help minimize fraud risk too. Using AI and ML can help flag suspicious activities and trigger alerts. As this study by Deloitte explains:

Machine learning can also analyze big data more efficiently, build statistical models quickly, and react to new suspicious behaviors faster.

Using traditional methods (like RPA) for fraud detection requires creating manual rules. RPA works well in a structured data environment. But given the high volume of complex data in banking, you’ll need ML systems for fraud detection.

Blanc Labs’ Banking Automation Solutions

Blanc Labs helps banks, credit unions, and Fintechs automate their processes. We tailor-make automation tools and systems based on your needs. Our systems take work off your plate and supercharge process efficiency.

Our team deploys technologies like RPA, AI, and ML to automate your processes. We integrate these systems (and your existing systems) to allow frictionless data exchange.

Book a discovery call to learn more about how automation can drive efficiency and gains at your bank.