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Why Banks and Credit Unions Should Pick Technology Vendors with SOC 2 Type II Certification 

Financial Services | IT Partners | IT Security & Compliance | IT Strategy

Why Banks and Credit Unions Should Pick Technology Vendors with SOC 2 Type II Certification 

July 18, 2024

Are your technology vendors SOC 2 Type II compliant? If not, your bank or credit union could be another data breach case study in the making. Many financial institutions, including big ones like Bank of America, fall victim to data breaches every year because of a third party. 

According to IBM’s Cost of a Data Breach Report, data breaches cost an average of $4.45 million. Partnering with SOC 2 Type II certified vendors can significantly minimize the risks of data breaches. In this guide, we explain how. 

What is SOC 2 Type II Compliance? 

SOC 2 Type II is a framework that assesses the effectiveness of internal controls used by a service organization to protect customer data. The American Institute of Certified Public Accountants (AICPA) established SOC (Service Organization Control) 2 standards based on five trust service criteria (TSC): 

  • Security: The systems must be protected against unauthorized physical and logical access using firewalls and authentication. 
  • Availability: The systems must be accessible as per service level agreements (SLAs). This includes, but is not limited to, monitoring network performance and availability, site failover, and security incident handling. 
  • Processing integrity: The right data must be delivered at the right price and time. Data processing must be complete, timely, validated, accurate, and authorized. 
  • Confidentiality: Access to data must be limited to authorized parties using encryption, firewalls, and access controls. 
  • Privacy: The system’s collection, use, retention, disclosure, and disposal of information must conform with the company’s privacy notice and the criteria set according to AICPA’s generally accepted accounting principles (GAAP).


The Difference Between SOC 2 Type I and Type II Compliance 

SOC 2 Types I and II differ in terms of scope and duration of evaluation. Here’s how: 

  • SOC 2 Type I is like a snapshot of your organization’s controls at a specific point in time. It confirms that necessary systems and processes exist to meet the TSC, but doesn’t consider the effectiveness of those controls. Companies often use type I reports to show commitment to security and compliance at a specific point in time, such as during contract negotiations. 
  • SOC 2 Type II involves a more comprehensive audit conducted over six to 12 months. Since the audit spans over a longer time frame, it helps validate the effectiveness of controls rather than just verify their presence. Type II reports offer more value to companies that want to offer their customers ongoing assurance about the effectiveness of controls over time. 

If you’re a bank or credit union, partner with SOC 2 Type II vendors. The longer testing window and the focus on the effectiveness of controls are vital to minimizing security and other risks. 

How SOC 2 Type II Certification is Achieved 

To become SOC 2 Type II compliant, a business must implement controls, gather supporting evidence, and engage a CPA to conduct an audit. If the CPA is assured that the organization has complied with all the requirements based on the audit, they give the company an unqualified opinion. Of course, the process is easier said than done. Here’s a quick overview of what the process looks like: 

Identify Gaps 

The organization looking to get certified needs internal controls in one or more of the five TSC. Security is a mandatory TSC, but the organization can choose others if it makes sense for their business or customer needs. Next, they need to assess their current controls and processes against the TSC to find gaps. This gives them a starting point and a preview of the quantum of effort required for certification. 

Design and Implement Controls 

Each TSC has sub-criteria that require the organization to establish and test controls, and remediate where necessary. As simple as it may sound, designing controls and collecting evidence can be quite complex. That’s exactly why it’s best to assign the program to someone with adequate technical knowledge, such as a CTO. 

The CTO must monitor the designing of controls and implement them across the organization. This involves training staff, updating IT systems, and reengineering or modifying processes to effectively support new controls. The organization must document all control activities, policies, and procedures in detail. These documents are crucial to demonstrating compliance during the audit. 

After all controls are in place, the organization must conduct a pre-assessment to test the effectiveness of controls and fix any issues or deficiencies that come to light. 

Select an Auditor 

Once all the controls are in place, it’s time to engage an independent third-party auditor to perform the SOC 2 Type II audit. The company looking to get certified can hire one of the Big4 firms, a CPA firm, or an individual practicing CPA, but it’s important to choose a CPA who has experience with SOC 2 assessments and understands the company’s industry and compliance needs. 

The CTO should work closely with the auditor throughout the process. The auditor will require a minimum of six months to assess the design and operational effectiveness of controls and verify compliance with TSC. If the auditor finds deficiencies during the audit, the organization must be prepared to promptly address them. 

Obtain Certification 

Once all issues have been identified and remediated and the audit is completed, the auditor will issue a SOC 2 Type II report. The report assures customers and stakeholders that the company’s controls are effectively designed and operating consistently over time. Beyond this point, the organization must continuously monitor and review controls, conduct periodic assessments, and stay updated with regulatory changes to maintain compliance. 

The Importance of Working with a SOC 2 Type II Compliant Vendor 

Banks and credit unions handle massive volumes of sensitive financial data every day. It’s critical to ensure this data’s security during day-to-day operations. SOC 2 Type II certification assures you and your customers that your vendors have the infrastructure and internal controls in place to securely process sensitive data. Let’s dive deeper into why banks and credit unions need to seek vendors with SOC 2 Type II certification: 

Data Security 

Data breaches at financial organizations can have serious repercussions—they can erode customer confidence and invite thousands of dollars in penalties. That’s why you should work with SOC 2 Type II compliant technology vendors—their compliance with SOC 2 standards assures that internal controls are in place to secure data. 

Risk Mitigation 

Partnering with SOC 2 Type II certified vendors minimizes the risk of data breaches, regulatory penalties, and damage to reputation. The number of cases of data violations jumped to 744 in 2023 from 138 in 2020—in a world where data breaches are a major risk, working with vendors that have adequate security can significantly lower the probability of mishaps. 

Compliance Alignment 

Many SOC 2 Type II requirements overlap with requirements of standards and regulations like PCI DSS (Payment Card Industry Data Security Standard) and GLBA (Gramm-Leach-Bliley Act), and guidelines from FFIEC (Federal Financial Institutions Examination Council). 

Common compliance requirements include controls over areas such as data encryption, network security, and vulnerability management, as well as data protection measures like tokenization and secure transmission protocols. 

Operational Resilience 

SOC 2 Type II assesses the availability and processing integrity of the vendor’s systems. Certified vendors have robust measures in place to ensure uninterrupted access to critical systems and maintain the reliability and accuracy of data processing. This offers operational resilience and continuity and minimizes disruption, allowing banks to deliver frictionless services to customers. 

Enhanced Trust and Reputation 

Partnering with certified vendors shows your customers that you prioritize integrity, transparency, and accountability when looking for vendors. It makes customers feel more confident when sharing personal and sensitive data with your systems. Over time, this builds trust and enhances reputation among clients and the broader community. 

Select Technology Vendors You Can Trust 

Non-certified vendors pose a significant burden and risk to not just your bank or credit union but also to customers who choose to bring their business to you. Falling victim to a data breach can ruin your bank or credit union’s reputation and invite costly penalties from regulators. 

The best way to safeguard your business, clients, and reputation is to only trust SOC 2 Type II certified vendors like Blanc Labs with your data. If you’re looking for help with designing, building, and integrating future-ready core banking systems, book a free consultation with us today. 

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How Open Banking Will Empower Small Businesses in Canada

Financial Services | Consumer Driven Banking | Open Banking

How Open Banking Will Empower Small Businesses in Canada

June 6, 2024
small business owners benefitting from open banking technology

As the old saying goes, “cash is king” and with 85% of business owners saying they’re looking for faster and easier access to capital, it seems like this is still truer than ever in today’s economy. Factors like high inflation and slow lending processes are making it harder for small businesses to access growth and operating capital, while needing to respond to challenges and opportunities in an ever-evolving business landscape. Open Banking can help address some of these challenges. In this guide, we discuss how.

What is Keeping Small Businesses From the Capital They Need?

To understand how open banking helps small businesses access capital faster, we need to look at the challenges they currently face.

Margins Under Pressure

Small businesses find accessing capital difficult when lenders tighten their belts or become risk-averse. An unfavorable credit market can result from multiple factors, such as high interest rates or a global financial crisis.

Inflation is a major contributor to tightening the credit market. It increases the cost of labor, raw materials, and operating expenses. In fact, 49% of respondents cited the cost of goods as the biggest inflation-related concern in an Equifax survey.

If small businesses can’t pass on the increased costs to customers because of competitive pressures or customer resistance, inflation can put pressure on profit margins. This translates to a lower net income percentage and cash generation—banks don’t like to see either when lending to a business.

Slow Lending Processes

Banks require applicants to submit tax returns, financial assets, a business plan, and various other documents. Excessive paperwork leaves room for errors and missing information. This is a major reason small businesses don’t get loan approval and are often hesitant to apply at all.

Stringent Know Your Customer (KYC) checks and rigorous anti-money laundering regulations significantly slow down loan approvals. Banks in Canada take risk assessment seriously. While there’s a good reason for it, analyzing credit history, projecting cash flows, and valuing collateral take time.

Even after going through the process, the number of small businesses that secure funding is often as low as 13.5%. Moreover, applicants who do make it through the approval phase might receive approval for an amount lower than requested.

Lack of Complete Information

Banks often don’t receive complete information from applicants. This can skew their decisions. For example, an applicant’s business might have changed significantly since they filed their last return.

Suppose your business recently secured a huge long-term contract with a multinational corporation. The bank might not see it on your previous return and won’t factor it into their assessment. That’s why banks need access to real-time data when making a lending decision.

Some banks rely on the borrower’s personal credit score to make lending decisions. This means you may find getting loan approval more difficult if you belong to Black or Hispanic communities where low credit scores and credit invisibility are common.

How will Open Banking Technology Transform the Lending Process?

Open banking, or “consumer-driven banking,” is about to revolutionize how small businesses secure debt capital. A whitepaper by Equifax explains:

“Two use cases stand out among those lenders already using Open Banking: payment initiation and more accurate consumer lending decisions. Not far behind, at 24%, are organizations that are using Open Banking to improve estimation or verification of consumer income.”

Open banking is not available in Canada yet, but work is underway to implement it as soon as possible. Open banking will transform the lending process in the following ways, making it easier for small businesses to access debt capital from financial institutions.

Easy Access to Data for Lenders and Small Businesses

Banks rely on financial data to make lending decisions. Open banking does a great job of mobilizing financial data, and here’s how it helps both small businesses and lenders:

Offers Banks a Thorough Credit Picture

Open banking technology connects small businesses and financial institutions via a third-party provider—usually fintech companies and alternative lenders. Third-party providers have access to a wealth of financial information, including transaction history, income, and the applicant’s creditworthiness. This gives lenders ample data to assess a loan application.

Third-party apps use application programming interfaces (APIs) to access real-time financial data from multiple sources, including the applicant’s bank account. This eliminates the need for manual documentation and verification, minimizes administrative load, and streamlines the lending process.

Drives Fairer Outcomes for Applicants With Low Credit Visibility

Access to more accurate data also drives fairer outcomes for a diverse range of applicants. This is especially important for Canada, where 12.2% of small business owners or primary decision-makers belong to a visible minority.

Many of these owners, especially those who recently migrated to Canada, don’t have enough financial history that banks can use to assess their creditworthiness. Open banking can help these applicants by enabling them to supplement loan credit checks with transaction data.

Enables Small Businesses to Seek Funding More Strategically

Open banking products give small businesses a holistic view of their financial position. For example, small businesses can monitor their cash flows and profitability during times of economic turmoil and apply for a loan once their financial statements project greater resilience.

In countries where open banking has already been implemented, businesses have realized various benefits, including greater visibility over cash flow. The UK’s Open Banking Implementation Entity interviewed 900 SMEs, of which 77% reported that open banking provided them with better visibility of their financial position.

Streamlined Application and Approval Process

Funding that doesn’t arrive on time is often futile. If you need access to quick cash during a high-growth phase or cash crunch, you probably don’t want to wait weeks until, and if, the lender approves your application. Not to mention, the loan application process itself could take up to a week, depending on the lender you’re dealing with.

Open banking automates various tasks in the lending process, such as:

Customer Data Aggregation

Open banking APIs enable applicants to share financial data with the lender via the open banking app. There’s no need for applicants to submit documents and statements manually. Once data flows in through the API, advanced data analytics tools and algorithms categorize, structure, and analyze the data to assess creditworthiness.

Cash Flow Analysis

Your cash flow statement may give lenders an idea of your business’s ability to generate cash. However, analyzing the sources and applications of cash using a cash flow statement requires manual work.

Instead of manually going through the cash flow statement, lenders can run the data through an algorithm or data analytics tool. They can apply advanced data analytics techniques to customer’s cash flow data sourced through open banking to understand the customer’s sources of income, recurring expenses, and spending habits.

Integration with Loan Origination Systems

Open banking enables seamless integration with the lenders’ loan origination systems, facilitating automated data transfer. This means underwriters, loan officers, and decision-makers have all the data they need readily available, resulting in faster approvals.

Greater Transparency and Competition

Here’s how open banking enhances transparency and competition: 

Makes  Shopping for Loans Easier 

Open banking offers small businesses greater transparency over prevailing rates.  With better data portabilitybusiness owners could use a third-party  app to compare interest rates, terms, and features of a loan product across multiple lenders without having to approach them individually. 

Increases Efficiency and Innovation 

Open banking levels the playing field by lowering the entry barrier for new financial services startups. Open banking has been instrumental in facilitating new lending models like peer-to-peer (P2P) lending platforms and digital lending marketplaces where you can explore a wide range of financing options. 

 

Open Banking for Small Businesses: Immediate and Long-Term Benefits

Here are some benefits of open banking for small businesses: 

Faster Access to Capital

Small businesses often face various challenges when accessing traditional financing options like bank loans, thanks to stringent eligibility criteria and lengthy approval processes. According to Ellie Mae, the average time to close a loan from the day of application to the disbursement of funds is 52 days. 

Open banking makes it easier for small businesses to access capital via alternative financing options. Countries that have already implemented open banking are seeing massive benefits. For example, Infosys built an open banking solution for a non-banking financial company (NBFC) in India. The solution helped the NBGC disburse funds faster while remaining 100% compliant. 

Helps Build Long-Term Financial Fortitude

Financial prudence offers various long-term benefits. Many small businesses aren’t profitable and deal with cash flow challenges. Using open banking solutions to track financial data across multiple accounts can add financial fortitude to your business, which is critical to getting the best loan terms and quick approval. 

Open banking software can even help reduce costs. A survey reveals that open banking helps businesses save up to 150 hours and 36 minutes each year—a little over four full working weeks. This translates to greater profitability and favorable changes in key metrics like the interest coverage ratio, eventually improving the odds of getting a loan approved. 

Tailored Financial Products

Open banking offers personalized financial products and services that cater to a small business’s specific needs. 

Suppose a small business uses an open banking app that monitors the business’s cash flow. The app keeps forecasting cash flows in real-time and alerts you when it sees a possible cash crunch coming. 

It also recommends a working capital loan, a list of lenders offering great terms, and a repayment schedule so the business owner or decision-maker can understand the impact on cash flows. 

Fosters Innovation and Competition

Greater access to financial data gives fintechs the ammunition to develop unique solutions and  tailored offerings that address specific needs insmall business finance. 

Mastercard is already making strides towards innovating unique solutions. The company has partnered with payments platform Dwolla to help users securely send funds without sharing account or routing numbers. 

It’s also collaborating with the fintech company Jack Henry, which services small community and regional banks, to provide account holders with the ability to see all of their financial information across multiple accounts (including those outside their primary financial institution) in one place. 

 The UK has already seen a massive range of innovative solutions powered by open banking. For example, the UK has apps to help people easily pay tax—the UK government received over £10.5 billion in taxes through open banking payments, according to a report by the Joint Regulatory Oversight Committee published in February 2023. 

Empowers Customers

One of the most significant aspects of open banking is customer empowerment. Open banking promotes transparency and accountability in the financial ecosystem by putting control of data into the customers’ hands and letting them decide whether they want to share their data with a third party. Customers can choose to share data with lenders that offer the most competitive loan terms, driving competition among lenders. 

Open Banking Strategy and Implementation 

Financial Institutions can benefit significantly from creating an open banking ecosystem for small and medium-sized businesses.  The global impact potential of Open Banking adoption across all sectors of banking  has been estimated at between 1 and 5 % of GDP according to McKinsey. But getting started can be challenging. To ensure a successful outcome, a strategic and methodical approach is crucial. Here are some key steps to effectively implement open banking for your institution: 

  1. Define Clear Use Cases: Start by identifying customer’s needs and how open banking can enhance your current SMB service offerings. Evaluate how these initiatives align with your overall business strategy in unlocking new opportunities for growth.  
  2. Develop a Partnership Roadmap: Open banking is an ecosystem that thrives on collaboration. Map out potential partnerships with other financial institutions and third parties. Focus on enhancing data utilization and creating customer offerings. While choosing partners, make sure they align with your technology capabilities and business goals.  
  3. Standardize and Manage APIs: APIs should be managed with a comprehensive framework which includes protocols for access, security, maintenance, and governance. This framework will be critical in ensuring that your open banking ecosystem runs smoothly and securely, which complying to data protection standards.  

Are you ready to implement Open Banking Technology?

Partner with Blanc Labs to build an open banking platform or solution that will help you innovate, stay ahead of the curve, and thrive as the open banking ecosystem matures.  

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Align, Assemble, Assure: A Framework for AI Adoption

Align, Assemble
Assure

Executive Summary 

In the rapidly evolving landscape of artificial intelligence (AI), enterprises face significant challenges in differentiating their AI capabilities to achieve strategic objectives. This article provides a comprehensive approach to organizing internal structures across business, technology, and governance/risk/compliance domains to build a robust and differentiated AI capability. 

The first part of the article emphasizes the importance of Stakeholder Alignment. To ensure success, AI initiatives must align closely with the organization’s strategic objectives and core values. This alignment ensures that AI projects not only drive innovation but also resonate with the organizational ethos and mission. By integrating AI principles and strategies, enterprises can foster a culture that supports and accelerates AI adoption. 

The second section delves into the Operating Model, which is crucial for driving AI innovation and efficiency. This involves defining the ideal team structures and identifying the essential capabilities required across people, processes, and technology. A robust operating model includes a well-defined AI platform that supports strategic objectives and maximizes returns. It also emphasizes the importance of ideation, experimentation, and the productionalization of AI projects to ensure they deliver tangible business value. Effective resource allocation and management are key to maximizing the returns on AI investments. 

The third critical aspect covered is Governance, Risk, and Compliance. As AI technologies advance, so do the associated risks and regulatory requirements. It is imperative for enterprises to identify and manage potential risks linked to AI projects proactively. Establishing comprehensive compliance mechanisms ensures that AI applications adhere to all regulatory and ethical standards, thereby safeguarding the organization against legal and ethical pitfalls. 

To address these multifaceted challenges, this article introduces the Align | Assemble | Assure (AAA) Framework for AI adoption within enterprises. 

  1. Align: This phase focuses on ensuring that AI initiatives are in sync with the strategic objectives and core values of the enterprise. By developing a clear AI strategy and set of principles, organizations can provide a coherent direction for AI adoption that supports broader business goals. 
  2. Assemble: This phase is about building the necessary capabilities across the organization. It involves organizing teams effectively and ensuring the right mix of talent, processes, and technology. By developing an AI use case portfolio, roadmap, business case, and budget, enterprises can prioritize AI investments and drive projects that offer the highest return on investment (ROI). 
  3. Assure: The final phase focuses on risk management and compliance. This involves assessing AI risks comprehensively and ensuring compliance with internal policies and external regulations. Implementing an AI risk management framework and compliance measures ensures that AI initiatives are secure, ethical, and compliant with all necessary standards.

In the next section, we will explore in depth how the Blanc Labs AAA Framework for AI Adoption can be implemented using actionable and measurable steps.

Align

First, ensure that all AI initiatives are aligned with the company’s strategic objectives and core business values. This involves understanding the business landscape and determining how AI can solve existing problems or create new opportunities. By focusing on alignment, the enterprise ensures that every AI project drives meaningful impact and contributes positively to the overarching goals of the organization. 

Here’s how you can effectively execute this alignment:

Identify Strategic Objectives

Business Goals: Begin by clearly understanding the core goals of the organization. What are the key performance indicators (KPIs) or business outcomes that matter most? How can AI contribute to these areas? Thinking through this at the beginning of the process will help you make the right choices pertaining to resources, time and effort, resulting in the long-term success of your AI strategy.  

Value Alignment: Ensure that the planned AI initiatives resonate with the company’s values and culture. People are a consequential pillar in AI adoption. Aligning your goals and vision will establish a clarity of purpose, which will in turn drive employee motivation and participation. 

Stakeholder Engagement

Collaboration: Engage with stakeholders across various departments to gather insights and identify needs that AI can address. This includes executives, operational staff, and IT teams. AI can improve processes across the mortgage value chain, starting with lead generation and pre-approval at the loan origination stage, going all the way up to default management. Examples of how AI can add value include automating routine tasks to allow employees to concentrate on strategic activities, helping underwriters make complex decisions faster by analyzing research and data; using data to tailor customer experiences, which can boost sales, customer retention, and engagement; and developing comprehensive AI-driven services like chatbots or specialized products for small businesses, which can increase both new and existing revenue streams. 

Feedback Loops: Establish continuous communication channels to keep all stakeholders informed and involved in the AI integration process. This helps in adjusting strategies as needed based on real-world feedback and evolving business needs.

Market and Competitive Analysis

Benchmarking: Analyze competitors and industry standards to understand where AI can provide a competitive edge or is necessary to meet industry benchmarks. 

Innovative Opportunities: Identify gaps in the current market that AI could fill, potentially opening new business avenues or improving competitive positioning.

Risk Assessment and Mitigation

Identifying Risks: Part of alignment involves understanding the potential risks associated with AI deployments, such as data privacy issues, biases in AI models, or unintended operational impacts. 

Mitigation Strategies: Develop strategies to mitigate these risks upfront, ensuring that the AI initiatives proceed smoothly and with minimal disruption.

Scalability and Sustainability

Future-proofing: Consider how the AI initiatives align with long-term business strategies and technological advancements. Ensure that the solutions are scalable and adaptable to future business changes and technological evolution.

Regulatory Compliance

Legal and Ethical Considerations: Ensure that all AI deployments follow relevant laws and ethical guidelines, which is particularly important in industries like healthcare, finance, and public services. 

Assemble 

Next, assemble a dedicated cross-functional AI Center of Excellence (CoE). This centralized team should consist of experts in AI, data science, ethics, compliance, and business operations. The CoE acts as the hub for AI expertise and collaboration within the company, enabling the standardization of tools, techniques, and methodologies. It also facilitates the pooling of resources and knowledge, ensuring that AI projects across the organization benefit from a consistent approach and high levels of technical and ethical oversight. 

To delve deeper into the “Assemble” part of the “Align, Assemble, Assure” framework using the people, process, technology, and organization structure components, we need to consider how each of these elements supports the creation of a robust AI capability within an enterprise. 

People 

Assembling the right talent is critical. This includes hiring and nurturing: 

  • AI Specialists: Data scientists, machine learning engineers, and AI researchers who can develop and optimize AI models. 
  • Technology Experts: Cloud architects, cyber security engineers, solution architects, software developers and testers who can build and support AI applications 
  • Business Domain Experts: Project managers and business analysts who understand the specific challenges and opportunities within the industry and can ensure that AI solutions are relevant and impactful.
  • Support Roles: Risk, legal and compliance officers to oversee AI projects and ensure they align with business and regulatory requirements. 

 

Process 

Establishing clear processes ensures AI projects are executed efficiently and effectively: 

Development Lifecycle:  

Define a standard AI project lifecycle, from ideation and data collection to model training and deployment. Here is a detailed breakdown of the various stages of the project lifecycle, including challenges, solutions and how to measure impact: 

Evaluation and Planning: Define critical performance indicators to measure success. Detail both functional and non-functional requirements, outline the necessary output formats, develop a comprehensive monitoring strategy, and define AI literacy requirements for the system. Additionally, determine the necessary data inputs and set clear criteria for explanations. Select the appropriate Generative AI technology, determine how it will be customized, and outline a high-level support and accountability framework. Evaluate and address the risks associated with these activities proportionally, documenting significant effects and strategies for risk mitigation. 

Pro Tip: When setting up your evaluation framework, maintain a balance between technical precision and flexibility. This allows your team to adapt quickly to new insights or changes in technology without compromising the system’s integrity or performance. Regularly revisit and refine your performance metrics and requirements to ensure they remain aligned with your strategic goals and the evolving landscape of AI technology. 

Data Set Up: Access, clean, and transform data to ensure it is high-quality, well-understood, and relevant for the specific use case. Address data privacy, security, legal, and ethical concerns by putting in place robust safeguards and compliance measures for both the input and output of data, making sure that data owners have approved its use. Set up strict guardrails for the input of information to third-party generative tools and the output from the solution. This includes establishing processes for refining or filtering the output before it reaches the end user, and setting clear restrictions on how the output can be utilized. 

Pro Tip: Emphasize the importance of automation in cleansing and transforming your data. This not only saves time but also reduces human error, ensuring consistent data quality. Additionally, continually update and refine your data governance policies and generative AI guardrails to keep pace with technological advancements and evolving regulatory landscapes. This proactive approach will help maintain the integrity and security of your data, enhancing overall trust in your AI solutions. 

Development: Start by selecting the optimal tool that matches your requirements in terms of size, language capabilities, and pre-trained features, along with the most appropriate integration method, whether it’s an API or an on-premises solution. Customize your tool using various advanced techniques such as fine-tuning, which involves teaching the tool to perform new or improved tasks like refining output formats, and Retrieval Augmented Generation (RAG), which enhances prompt responses and outputs by incorporating external knowledge sources. Develop and refine a systematic approach to prompt engineering to create, manage, and continuously improve prompts. Focus on refining the solution to boost performance, accuracy, and efficiency through methods like adjusting parameters, tuning hyperparameters, improving data quality, conducting feature engineering, and making architectural adjustments. 

Pro Tip: Prioritize the scalability and adaptability of your tools and methods. As you refine and expand your AI applications, ensure that the tools you select can evolve with your needs and can integrate new features or data sources seamlessly. Regularly revisit your prompt engineering and customization strategies to keep them aligned with the latest advancements in AI technology, thus maintaining your competitive edge and maximizing the effectiveness of your solutions. 

Implementation and Management: Integrate the AI solution into the operational applications, ensuring seamless transition into production environments. Assign clear ownership to oversee the solution’s lifecycle. Develop a support structure that includes performance-based Service Level Agreements (SLAs) and operational guidelines aimed at fulfilling the established non-functional requirements, and introduce practices for consistent data management. Enhance organizational understanding and capability through targeted AI training programs. Ensure diligent registration of any new use of AI. Complete all the necessary documentation to provide clear explanations and transparency regarding the AI solution’s functionalities and decisions. 

Pro Tip: Establish a feedback loop between the operational performance and the development teams. This ensures that any insights gained from real-world application can be swiftly acted upon to refine the solution. Regularly updating your integration practices and operational protocols in response to these insights will help you maintain high standards of performance and reliability, ensuring that your AI system remains robust and effective in ever-changing environments. 

Monitoring and Maintenance: Implement continuous monitoring of the deployed AI solution to assess its performance, accuracy, overall impact (including any unintended biases), usage, costs, and data management practices. Promptly investigate and resolve any issues or anomalies that arise during operation. Utilize the insights gathered from the monitoring process to regularly update, maintain, and enhance the solution. Maintain vigilant oversight of any updates made to the AI system. Ensure all new applications of the AI are properly registered. Occasionally, updates pushed by the supplier might require a comprehensive review due to potential significant changes. Provide ongoing reporting to highlight the benefits and value added by the AI solution. 

Pro Tip: Consider implementing automated tools that can alert you to anomalies in real-time. Regularly scheduled reviews of the system’s outputs and operations can help preempt problems before they escalate, ensuring that the AI continues to operate efficiently and effectively. Moreover, documenting every adjustment and update not only aids in compliance and governance but also provides valuable historical data that can inform future enhancements and deployments. 

The Role of AI Quality Assurance and Testing

AI development demands rigorous and continuous testing. The role of Quality Assurance (QA) and Testing is to assess the relevance and effectiveness of the training data, ensuring it performs as intended. This process starts with basic validation techniques, where QA engineers select portions of the training data for the validation phase. They test this data in specific scenarios to evaluate not only the algorithm’s performance on familiar data but also its ability to generalize to new, unseen data. Evaluation metrics such as accuracy, precision, recall, and the F1 score are defined based on the specific use case, recognizing that not all metrics are appropriate for every scenario.

If significant errors are detected during validation, the AI must undergo modifications, similar to traditional software development cycles. After adjustments, the AI is retested by the QA team until it meets the expected standards. However, unlike other software, AI testing by the QA team does not conclude after one cycle. QA engineers must repeatedly test the AI with various datasets for an indefinite period, depending on the desired thoroughness or available resources, all before the AI model goes into production.

During this repetitive testing phase, also known as the “training phase,” developers should test the algorithm on various fronts. Notably, QA teams will need to focus not on the code or algorithm itself but on whether the AI fulfills its intended function. QA engineers for AI testing will primarily work with hyperparameter configuration and training data, using cross-validation to ensure correct settings.

The final focus is on the training data itself, evaluating its quality, completeness, potential biases, or blindspots that might affect real-world performance. To effectively address these issues, QA teams need access to representative real-world data samples and a deep understanding of AI bias and ethics. This comprehensive approach will help them pose critical questions about the AI’s design and its ability to realistically model the scenarios it aims to predict, ensuring robustness and reliability across various applications.

 

 

Technology

To deliver comprehensive and effective AI solutions, enterprises need to establish robust technology and tooling capabilities within their AI platforms. These capabilities span several domains, each critical for developing, deploying, and managing Gen AI, Cognitive AI and machine learning (ML) models.

Gen AI Development is foundational for creating full-featured generative AI applications. Enterprises must have the capability to customize and deploy models to meet specific business needs. This includes fine-tuning model inputs and engineering prompts to enhance performance and relevance. Additionally, managing the lifecycle of models during development is crucial, ensuring that models are continuously improved and updated. Orchestrating various AI models allows enterprises to integrate multiple AI systems seamlessly, optimizing the overall functionality and efficiency of the AI platform.

Gen AI and ML Operations focus on the day-to-day management and fine-tuning of AI models once they are in production. This involves managing the lifecycle of models and their versions to maintain consistency and reliability. Effective access management to models ensures that only authorized personnel can modify or utilize these models, enhancing security. Fine-tuning ML models and their training is essential to adapt to new data and evolving business requirements. Furthermore, managing data sources efficiently ensures that the models are fed with accurate and relevant data, which is vital for generating reliable outputs.

Gen AI and ML Governance is essential for maintaining the integrity and compliance of AI systems. Enterprises need to monitor models continuously to ensure they produce accurate and appropriate responses. Safeguarding models from inappropriate or malicious inputs is critical to prevent misuse and potential harm. Compliance with legal and regulatory frameworks is another significant aspect, ensuring that AI operations adhere to the necessary standards and regulations. Managing the data leveraged by models helps maintain data privacy and security, which is paramount in today’s regulatory environment.

Cognitive AI Capabilities are designed to mimic human cognitive functions, providing advanced interactions through APIs and SDKs. These capabilities include understanding and translating languages, recognizing images and sounds, and extracting and summarizing data. By integrating these cognitive functions, enterprises can enhance their AI applications to provide more natural and intuitive interactions, thereby improving user experience and engagement.

Establishing these comprehensive technology and tooling capabilities within an enterprise AI platform is crucial for developing robust, secure, and compliant AI solutions. By focusing on these areas, enterprises can harness the full potential of AI, driving innovation and achieving strategic business objectives.

Organization Structure 

Effective organization structure facilitates AI adoption and integration: 

  • Centralized AI Unit: An AI Center or hub, possibly under a Chief AI Officer, to centralize expertise and provide leadership. 
  • Cross-functional Teams: Integration of AI teams with other business units to promote collaboration and ensure AI solutions meet business needs.  
  • Change Management: Structures to support change management processes, helping the workforce adapt to new technologies and methods introduced by AI. 

Assure 

Finally, implement robust governance to assure the safety, compliance, and ethical integrity of AI deployments. This includes setting up frameworks for ongoing monitoring and evaluation of AI systems, ensuring they adhere to regulatory requirements and ethical standards. The governance process should also involve stakeholder engagement to maintain transparency and address any concerns related to AI projects. 

Responsible AI 

Responsible use of AI will require a commitment to ethical guidelines that prioritize: 

Transparency & Explainability: Create AI systems that are both transparent and clear in their functioning. As an organization, you should be able to pinpoint and clarify AI-driven decisions and outcomes. This will be especially important in the context of customers and stakeholders.  

Compliance: Designate responsible individuals for AI systems and ensure that the systems comply with regulatory standards. Conduct frequent audits to ensure the accuracy of your AI solutions, handle unforeseen outcomes, and check that the solutions fulfill legal and regulatory requirements. 

Equity and Diversity: Design, develop and deploy AI in an ethical, fair and inclusive manner. Proactively strive to identify and address biases that can emerge from training data or decision-making algorithms.  

Data Privacy: It’s imperative to safeguard personal data and prioritize individuals’ well-being, preventing any potential harm. Commit to respecting privacy rights, secure personal data, and mitigate potential risks and negative impacts on customers by obtaining consent and implementing responsible data practices.  

Security: Create AI solutions that can withstand attacks, malfunctions and manipulation. Implement safeguards to secure AI data, services, networks and infrastructure to prevent unauthorized access, breaches or data manipulation.  

Examples of Prohibited Use Cases: 

Using a risk assessment framework guided by the ethical AI principles mentioned above, here is an example of use cases that will not pass:  

  • Assessing, categorizing, or evaluating individuals based on their biometric information, personal attributes, or social behavior. 
  • Using subliminal, manipulative, or misleading techniques to sway an individual’s behavior. 
  • Taking advantage of people’s vulnerabilities (e.g., their age, disability, or social/economic status). 
  • Emotion recognition, as defined by your legal department.  
  • Collecting biometric data indiscriminately. 
  • Generating false content that seems to represent a particular person.

 

See Also: Artificial Intelligence and Data Act Canada

The proposed Artificial Intelligence and Data Act (AIDA) aims to establish standards for the responsible design, development, and deployment of AI systems, ensuring they are safe and non-discriminatory. This legislation will require businesses to identify and mitigate the risks of their AI systems, and to provide transparent information to users.

Under AIDA, the level of safety obligations for AI systems will depend on the associated risks, and businesses will need to adhere to new regulations across the design, development, and deployment stages. The government is working to create regulations that align with existing standards, aiming to facilitate compliance for businesses. A new AI and Data Commissioner will monitor compliance to ensure AI systems are fair and non-discriminatory. By introducing this law, Canada is among the first countries to propose AI regulation, aiming to balance innovation with safety, and ensuring international competitiveness while considering the needs of all stakeholders.

For more information, view the full act.

 

The diagram above shows how you can create your own AI risk assessment framework. Risk can be measured along four factors: personal information, decision-making, bias and external access.

In Conclusion

With the principle of “Align, Assemble, Assure,” the enterprise can methodically approach AI integration, ensuring that the efforts are strategically sound, well-supported by a specialized team, and maintained under stringent ethical and regulatory standards. This principle not only fosters innovation and efficiency but also builds trust and reliability in AI applications across the business.

Take the first step towards transforming your business with AI

Prithvi Srinivasan
Managing Director – Advisory Services

Prithvi Srinivasan, the Managing Director for Advisory Services, brings extensive expertise in technology strategy and digital transformation to drive mission-critical programs and advance financial institutions with AI and automation. His ability to transform complex strategies into successful transformations underscores his commitment to innovation and client value.

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May 6 (Toronto, ON)— Blanc Labs, a pioneer in Lending Technology, Artificial Intelligence (AI) and Intelligent Automation, is thrilled to announce the appointment of two new members to its executive team, Prithvi Srinivasan and Ali Khachan, both distinguished leaders in technology and consulting.

Prithvi Srinivasan, a former Partner at Deloitte Consulting, is joining Blanc Labs as the Managing Director for Advisory Services. Prithvi brings a wealth of expertise in technology strategy, digital transformation, and business operations excellence, and specializes in driving mission-critical transformation programs. Leveraging his extensive experience in aligning technology initiatives with business value, Prithvi is set to propel financial institutions forward using Blanc Labs’ expertise in lending technology, AI, and intelligent automation. His proven track record in driving successful enterprise transformations and optimizing technology estates underscores his commitment to fostering innovation and delivering value to clients. Prithvi excels in transforming complex strategies into actionable successes, ensuring technology not only meets but advances business objectives.

Ali Khachan, a tech startup leader and former Principal at Boston Consulting Group (BCG), joins Blanc Labs as Managing Director of AI. As a strategic operator with over 15 years of leadership at the nexus of technology and business, Ali has demonstrated a keen ability to drive transformational growth through AI and digital innovations. His expertise in scaling up ventures, spearheading digital transformations, and maximizing value creation for global enterprises will play a pivotal role in shaping the future of Blanc Labs as it continues to pioneer groundbreaking AI solutions.

“The addition of Prithvi and Ali to our executive team significantly strengthens Blanc Labs’ strategic capabilities and reinforces our position as a leading technology partner for the financial sector,” said Hamid Akbari, CEO of Blanc Labs. “Their exceptional expertise and visionary leadership will accelerate our strategic initiatives across Advisory Services, Data, Automation, Artificial Intelligence, and Generative AI solutions. I am confident that with Prithvi and Ali on board, Blanc Labs will achieve new heights in delivering exceptional value to our clients and shaping the future of digital transformation in the financial services industry.”

Both Prithvi and Ali will be speaking at the Canadian Lenders Association Bankers Summit in Toronto on May 15th. They will conduct a series of workshops focused on AI in Lending, demonstrating Blanc Labs’ commitment to fostering knowledge exchange and leading the charge in AI solutions for financial services. To register for the workshops, please reach out to Blanc Labs through their website.

 

ABOUT BLANC LABS

Blanc Labs is a preferred partner for enterprises looking to digitize and build the next generation of technology products and services. To help companies rapidly deliver on their digital initiatives, Blanc Labs has developed expertise and bespoke solutions in a wide variety of applications in financial services, healthcare, enterprise productivity, and customer experience. Headquartered in Toronto, Blanc Labs serves the Americas through operations in Toronto, New York, Bogota, and Buenos Aires. For more information on how Blanc Labs is building a better future, visit  www.blanclabs.com.

 

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E: shriyag@blanclabs.com

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May 3, 2024 (Toronto, ON) – Blanc Labs, a leader in Lending Technology, AI, and Business Process Improvement, is excited to announce a strategic partnership with TCG Process, leveraging their DocProStar platform to transform lending operations for mid-tier banks, credit unions, and other mortgage origination and servicing providers in Canada. This partnership marks a significant milestone in Blanc Labs’ mission to enhance operational efficiencies and unlock new revenue opportunities for lenders through cutting-edge technology.

Blanc Labs’ Intelligent Automation Methodology, designed by seasoned experts, pinpoints and addresses critical areas for improvement within document intensive workflows. The solution seamlessly integrates with existing technology infrastructure, enabling rapid deployment and immediate impact on operational efficiencies, with minimal investment.

“Rapid advancements in powerful new AI technologies like LLMs are further unlocking opportunities to move away from manual, data heavy workflows that cause frustrations for customers and lending teams alike,” said David Offierski, VP of Partnerships for Blanc Labs. “We are seeing a significant shift from the manual ingestion of customer information to a much more efficient and automated workflow solution, allowing stakeholders to improve both customer and employee experience while reducing operational costs.”

TCG Process’ DocProStar provides intelligent document ingestion, orchestrated processing and powerful AI capabilities that will enable Blanc Labs to quickly deploy advanced, cost-effective, and scalable solutions to meet the unique needs of lending teams.

The collaboration between Blanc Labs and TCG Process signifies a joint commitment to deliver innovative solutions, leveraging cutting-edge technologies to streamline lending processes. The opportunity is clear: to create a more seamless experience for customers, tailored to the unique needs of the Canadian lending market.

“Our partnership with Blanc Labs is more than just technology—it’s about shared expertise and collaboration. By combining our strengths, we will provide industry leading solutions that cater to the diverse needs of the financial services sector.” Joseph Capone, Chief Revenue Officer, TCG Process (Canada).

Hamid Akbari, CEO of Blanc Labs, said, “The use of technologies like DocProStar and our Kapti platform can greatly improve compliance, increase customer retention, reduce servicing cost, and boost revenue in the lending sector. Our deep expertise in lending technologies, and especially intelligent processing of mortgage documents, enhances our role as a transformation partner.”

Blanc Labs operates with agile, expert teams, ensuring that clients typically see a return on their investment within 12 months. The company remains dedicated to its role as a pivotal player in lending industry transformation.

 

 

ABOUT BLANC LABS

Blanc Labs is a preferred partner for enterprises looking to digitize and build the next generation of technology products and services. To help companies rapidly deliver on their digital initiatives, Blanc Labs has developed expertise and bespoke solutions in a wide variety of applications in financial services, healthcare, enterprise productivity, and customer experience. Headquartered in Toronto, Blanc Labs serves the Americas through operations in Toronto, New York, Bogota, and Buenos Aires. For more information on how Blanc Labs is building a better future, visit  www.blanclabs.com.

ABOUT TCG PROCESS

TCG Process, with headquarters in Switzerland, is an international organization that develops and integrates input management and intelligent process automation software. Its solutions are used in industries such as banking, insurance, healthcare, government, and public administration to digitize and automate document-driven processes. TCG Process sells both directly and via partners globally. Visit www.tcgprocess.com

 

For media inquiries, please contact:

Shriya Ghate

Senior Marketing Manager

Blanc Labs

E: shriyag@blanclabs.com

 

Tracy Weller-McCormack

Head of Marketing, Canada & Australia

E: tracy.mccormack@tcgprocess.com

 

 

 

The Transformative Influence of Large Language Models (LLMs) on Document Processing

BPI in Banking and Financial Services in the US & Canada

Financial Services | Business Process Improvement | Enterprise Automation

BPI in Banking and Financial Services in the US & Canada

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

Banking and financial services are evolving at immense speed. Transitioning from traditional, paper-based processes to digital and AI-powered processes is critical to survival. That’s why you need to think about business process improvement in banking and financial services.

Business process improvement comes with a price tag. You need experts on your team, a culture centered on continuous improvement, and a powerful set of automation tools. But these tools offer extensive benefits as well. For example, Accenture estimates that automation and augmentation can help save financial services firms $140 billion and banks $70 billion.

Revolutionizing Banking and Financial Services Through Business Process Improvement

Banking and financial services firms have grown tremendously through business process improvement. Look back at your own organization’s past. You likely had to radically redesign processes to bring about any revolutionary change in your organization. From developing a mobile app for your bank to building your ATM network, all changes were a result of improved, more efficient processes.

The next leg of growth in banking and financial services requires using technologies like AI and natural language processing (NLP) to reduce costs, increase efficiency, and improve customer experience.

These technologies will help you stay ahead of the curve and improve your workflow. However, implementing technologies like AI, Gen AI, and Robotic Process Automation (RPA) requires experience and expertise, so find the right partner for smooth implementation and minimal disruption.

Let’s now dive into how you can plan to improve business processes to prepare your financial institution for the future.

BPI vs BPM

Business Process Improvement (BPI) and Business Process Management (BPM) are two distinct but complementary approaches within organizational process optimization. BPI is primarily concerned with improving the efficiency and effectiveness of specific processes. It involves identifying, analyzing, and enhancing existing business operations to reduce costs, improve service delivery, or increase quality. On the other hand, BPM takes a broader view, focusing on the entire set of processes within an organization. It integrates all aspects of process management—from design and modeling to monitoring and optimization—with the goal of aligning processes with the strategic objectives of the organization. While BPI zooms in on process improvements, BPM includes holistic management of all processes to ensure coherence and alignment with overall business goals. 

Financial Processes That Need Improvement

There’s plenty of room for improvement in financial processes as we know them today. AI and RPA technologies have opened doors to a whole universe of process improvements that were previously unimaginable. Here are some examples of processes you should consider working on when implementing BPM:

Customer Onboarding

Onboarding sets the stage for your relationship with the client. Customers who have a positive experience when opening their bank account are 73% more likely to become the bank’s promoters.

Improving your onboarding process by implementing a fully digitized workflow eliminates the need to manage piles of paperwork, errors, and delays. A frictionless onboarding experience doesn’t just attract new customers; it also builds a solid reputation and loyalty among customers.

Customer Support

The modern customer wants their bank or financial institution to respond within seconds and be available 24/7. Not delivering on these expectations is essentially the same as handing your clients to competitors.

Intelligent Digital Assistants (IDAs), next-gen chatbots powered by AI, “are fully equipped with natural language understanding which aids in understanding and retaining context for polished conversations while carrying out a variety of tasks to fulfill a user’s requirements.” They act as “knowledgable bankers” who not only understand the unique journeys of customers, but are also able to recommend products, offers and next steps based on their knowledge of a customer’s past behavior and financial history.

Risk and Compliance Management

Tailoring business processes to minimize risks and comply with industry regulations helps prevent penalties as well as lower your compliance team’s workload. For example, you can create a digital workflow that provides real-time (or frequent) tracking for compliance requirements as well as detailed compliance reports.

Analytics can play a key role in bolstering your bank’s or financial institution’s risk assessment capabilities. AI-powered systems can ingest massive amounts of data your organization generates to identify patterns. The system can detect anomalies and predict risks using this data.

Loan Approvals

Loan origination systems are often plagued by labor-intensiveness, errors, and a ton of paperwork. Automating your loan origination system can transform your efficiency and the customer’s experience.

If your organization currently uses traditional processes, consider completely reengineering the process. Modernizing your lending process, right from eligibility checks to approval, is important not to develop a competitive advantage, but to survive in an environment where quick approvals and disbursals are the norm.

 

Implementing Business Process Management in Banking and Financial Services

Changing and managing business processes is easier said than done. Your team might need to unlearn and relearn. You might have to deal with reluctance and proactively offer training to help them get up to speed.

However, there’s an even greater challenge — implementing the right set of technologies and building the right infrastructure. That’s why you need a partner who has experience helping banks and financial services firms implement technologies to improve business processes.

With that in mind, here’s an overview of how you can implement business process management:

Step 1: Identify Key Processes

The first step is to identify key processes within your bank or financial institution that could use some improvement. The process could be onboarding, loan processing, risk assessment, or customer service.

Consider asking employees — people on the ground executing these processes — how you can improve. Identify their pain points and bottlenecks and prioritize areas for optimization based on your analysis.

For example, if your bank’s loan origination process is lengthy and has high error rates, fixing that should be your priority over streamlining your support processes.

Step 2: Map Your Processes

A process map gives you an overview of the entire workflow and the steps involved in the process, including stakeholders, decision points, and the flow of information. A visual representation of your process helps you understand its current state, identify inefficiencies, and find opportunities to improve the process.

Step 3: Optimize Processes

Once you’ve identified inefficiencies and redundancies, it’s time to eliminate them. The exact solutions to implement depend on the challenge you’re addressing. However, automation and standardization are the first steps towards optimizing processes.

If you’re thinking to yourself, “We’ve already automated repetitive tasks,” that’s not enough. Use AI to automate some tasks you previously thought were best handled by humans.

For example, don’t use scripted chatbots that make customers feel like they’re talking to a robot. Find a partner who can develop a chatbot powered by technologies like AI and Gen AI. AI-powered chatbots can personalize conversations and interact just like humans.

If you’re not using AI, you’re already late to the party — Bank of America has been using its AI chatbot, Erica, since 2016. Bank of America claims that Erica has been able to provide more than 98% of its clients with the answers they need.

Step 4: Monitor and Improve

Optimizing business processes is not a one-off task. It’s an ongoing journey. Measure the results your optimization efforts yield with process metrics like cycle time, error rates, and customer satisfaction.

You can use AI-powered data analytics to gain deeper insights into process performance and find areas that require further improvement.

For example, if you recently optimized your loan origination process, use data analytics to monitor processing time.

Has it improved to the extent you expected? If not, use data to find out why. Is the optimized process still prone to errors? Or is your team still going through the learning curve?

 

The Role of Automation in Improving Financial Processes

Automation plays multiple roles in improving banking and financial processes. Here’s a quick overview of why automation is vital to your business process improvement initiatives:

  • Say goodbye to repetitive tasks and errors: You don’t need to spend thousands of dollars on data entry, reconciliations, and reports. Automation can perform those tasks more efficiently than humans and doesn’t make mistakes. Moreover, software allows you to keep costs under control even as you continue to scale.
  • Enforce standardized processes: You can create all the SOPs (standard operating procedures)you want. But there will always be someone trying to take a shortcut. Automation helps you achieve consistency in executing standardized processes — you can impose rules through your automated system to eliminate deviations from a standardized process.
  • Greater efficiency: Automation helps you multiply productivity. The more productive your bank or financial institution is, the more loans you can process, accounts you can reconcile, reports you can generate, and customers you can onboard without compromising on accuracy.
  • Improved customer experience: One of the biggest roles of automation in business process improvement is tailoring your processes to meet the customers’ needs. Automation allows you to personalize processes, eliminate errors, offer convenience, and deliver fast experiences at scale.
  • Deeper insights: Automating data collection and reporting helps you derive value out of the massive volume of data financial institutions generate. AI-powered analytics help you spot patterns and detect outliers. For example, if there’s fraudulent activity in a customer’s account, AI can pick up on that. Analytics also helps you make data-driven decisions, predict customer behavior, and assess risk exposure.
  • Improved customer experience: Automation allows you to improve customer experience across channels. Your AI chatbot can deliver personalized responses, analytics can help you predict customer behavior, and streamlined onboarding helps you make a great first impression.

Revolutionize Financial Services with Business Process Improvement

Let’s face it. Redesigning business processes comes with risk. However, the risk-reward ratio is in your favor when you use the right technologies and work with a team of experts. Strategic business improvement can transform your customer experience and generate massive cost savings for your business. 

Blanc Labs is committed to helping partners succeed through the use of cutting-edge technologies. Our approach can help you redesign processes in a way that fits your business’s needs. 

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Key Insights on Consumer Driven Banking in Canada 2024

Key Insights on Consumer Driven Banking in Canada 2024

Blanc Labs has been a strong supporter of open banking, recognizing the multiple benefits it can bring for Canadian banking customers, as well as opportunities for innovation and competition in the financial services industry. Following the positive announcement of the Fall Economic Update in November 2023, where the federal government revealed its plan to introduce an open banking framework in 2024, Blanc Labs decided to conduct a survey in collaboration with the Canadian Lenders Association (CLA)—a not-for-profit body that represents 300 Canadian banks and fintechs—to get a better understanding of the priorities and pain points of the financial services sector related to open banking policy and to provide feedback to the Department of Finance before Budget 2024.

 

 

The survey was conducted among the Open Finance Roundtable, which is composed of fintechs, banks, card providers, consulting companies and research agencies, and received 32 responses. Here are some of the key highlights from the survey.

Blanc Labs has been a strong supporter of open banking, recognizing the multiple benefits it can bring for Canadian banking customers, as well as opportunities for innovation and competition in the financial services industry. Following the positive announcement of the Fall Economic Update in November 2023, where the federal government revealed its plan to introduce an open banking framework in 2024, Blanc Labs decided to conduct a survey in collaboration with the Canadian Lenders Association (CLA)—a not-for-profit body that represents 300 Canadian banks and fintechs—to get a better understanding of the priorities and pain points of the financial services sector related to open banking policy and to provide feedback to the Department of Finance before Budget 2024.

 

 

The survey was conducted among the Open Finance Roundtable, which is composed of fintechs, banks, card providers, consulting companies and research agencies, and received 32 responses. Here are some of the key highlights from the survey.

Insights Summary

Insights Summary

Open Banking matters to a diverse group of stakeholders

The questionnaire responses came from a broad cross section of participants showing a diversity of perspectives related to Open Banking.

The largest groups of respondents identified as FinTechs and Federally Regulated Financial Institutions.

We also heard from Commercial and Alternative Lenders, Payments Services Providers, Technology Services Providers and Consulting /Law Firms.

This group is bullish on Open Banking, and ready for it

63% were Positive to Very Positive in their reaction to Consumer Directed Banking being highlighted as a priority in the Federal Government 2023 Fall Economic Update.

87.5% believe Consumer Driven Finance/Open Banking will be Impactful or Very Impactful to their core business offerings, customer experience and growth strategy.

Just under 75% of respondents said they are strategically ready for open banking.

From a technology readiness perspective, 68% said they are Ready or Very Ready to move forward with Open Banking. This could include having adopted Open API Standards, working with an Open Banking Utility like Flinks, and building products and services that promote financial data portability.

Interested in learning more about Open Banking readiness from a technology perspective? Blanc Labs has created a free resource on Open Banking Technology Architecture.

 

Open Banking will deliver on its core promises

Benefit Banking Customers

90% believe that Open Banking will allow Canadians to have greater access to innovative products & services and help them achieve better financial outcomes.

Promote Competition

90% agree or strongly agree that consumer driven banking will enhance competition within the financial sector.

Consumer Driven Banking is bigger than Open Banking

97% of respondents said Payments Modernization is an important component to realize the positive impacts of a Consumer Driven Banking. Initiatives such as adopting Real-Time Payments and making changes to our payments landscape cannot take a backseat to Open Banking.

Fair Access and Transparency are ‘Must Haves’

Over ½ of respondents said Fair Access to Financial Infrastructure is the most important factor to promote a level playing field amongst ecosystem participants.

78% feel that it is important to have regular Public Reporting on Concentration and Competition in terms of how Consumer Driven Banking initiatives get rolled out in Canada.

Open Banking in Canada in 2024 and Beyond

Findings from the Blanc Labs x Canadian Lenders Association (CLA) survey underscores the enthusiasm and readiness of a diverse range of industry stakeholders towards the adoption of open banking, as well as a collective recognition of the potential benefits it holds for consumers and businesses alike.

With a majority expressing confidence in the impact of open banking on their core business offerings and growth strategies, coupled with a strong belief in the industry’s ability to deliver safer access to innovative financial products and services, the stage is set for a transformative shift in Canada’s financial landscape.

 

Blanc Labs is a trusted partner to forward-thinking financial services companies. Learn more about how we can assist your organization in shaping your open banking technology strategy and implementation.

Business Process Improvement vs Business Process Reengineering 

Financial Services | Banking Automation | Business Process Improvement

Business Process Improvement vs Business Process Reengineering 

April 8, 2024

Your business’s ability to change goes a long way toward contributing to long-term success. But how do you decide whether to make small changes over the long term or if a situation calls for a radical change?

To determine this, you must understand business process improvement (BPI) and reengineering (BPR). In this guide, we explain the meaning of BPI and BPR and when to use them.

What is Business Process Improvement?

Business process improvement is an ongoing process where you make small, continuous improvements to make processes more efficient.

BPI is like fine-tuning your car’s engine to make it run smoother and faster. You start by examining the engine’s current condition. Then you find areas that could use some maintenance and perform that maintenance to improve efficiency. Of course, BPI requires careful planning and execution, so it’s always smart to have a BPI specialist by your side.

Continuous improvement and data-driven decisions are key aspects of BPI. Instead of blindly chasing market trends and investing in expensive tech, you start with introspection. You use analytics to validate the need for change. And you make small changes over time to minimize disruption.

What is Business Process Reengineering?

Business process reengineering is a comprehensive process redesign exercise that helps a business improve efficiency and overall performance significantly.

Business Process Reengineering is the radical redesign of business processes to achieve dramatic improvements in productivity, cycle times, quality, and employee and customer satisfaction.

Bain & Company

There are times when your business might need a radical change, such as: 

  • When you want to build a competitive advantage 
  • To prepare for rapid growth 
  • After a merger or acquisition 
  • Organizations restructuring

Of course, this is an inclusive list. You might choose to reengineer a process to improve productivity, comply with new regulatory requirements, or introduce new technology. However, BPR is a far more extensive process than BPI. It requires effective change management and stakeholder engagement. 

BPI vs. BPR

 

While BPI and BPR share some common objectives — improved efficiency and optimal resource utilization — they differ in some key areas. Here are three key aspects where BPI and BPR differ:

Level of Change

BPI is about continuously asking yourself, “How can we make this better?” even when there’s no urgency to change a process. The focus is to identify inefficiencies, bottlenecks, and areas of waste within your current processes. For example, if you’re an online retailer, BPI could involve streamlining your order fulfillment process to reduce delivery times or using a more robust CRM to improve client relationships.

BPR involves a complete overhaul. It’s like tearing down an entire house and building it from scratch. Suppose you’re a retail company that wants to improve delivery times. But instead of optimizing the order fulfillment process, you redesign the entire supply chain, from sourcing to delivery.

Be careful, though. Companies often overwhelm themselves by overestimating their capacity for change. It’s hard to determine if a process redesign is viable without understanding your capacity for change. As David Michels and Kevin Murphy explain in their HBR article:

The current business landscape is evolving so rapidly and unpredictably that executives are full of questions about change. How much? They want to know. How fast? How sustainable? And sometimes, just how? In our experience companies can’t hope to answer these questions unless they understand their own capacity for change.

Harvard Business Review

Time Frame

Implementing BPI takes less time than implementing BPR. Think of BPI as a series of quick wins. You zoom into your process, find areas for improvement, make changes, and repeat. The exact time frame may differ based on the adjustments you want to make and could take weeks or months.

BPR is a marathon, not a race. It requires redesigning the process from scratch. A successful redesign might involve significant investments in technology and training. This requires careful consideration and meticulous execution. Naturally, redesigning and executing can take a long time, typically months or even years.

Risk and Disruption

There’s a significant divergence between BPI and BPR regarding risk and divergence. Since BPI involves making small changes, the level of disruption and risk is relatively lower.

Employees are less likely to resist these small changes because BPI builds on existing structures and practices. Plus, the changes are implemented gradually, so the transition is smoother and causes minimal disruption to your business’s day-to-day operations.

On the other hand, BPR involves challenging deeply ingrained practices and questioning conventions. Employees might have to step out of their comfort zone to execute changes of that magnitude, so there’s greater risk and disruption. Before you move forward with BPR, ensure that you and your team are prepared for that change.

We believe that most firms do not proactively manage change risk in a way that’s commensurate with the benefits of success and the costs of failure. Effectively managing change risk is a necessary ‘muscle’ to reduce, preempt, mitigate, and manage the challenges that come with (intents of) transformation, without bringing decision paralysis or stifling innovation in the organization.

‘Managing Change Risk’, Oliver Wyman

BPI vs. BPR: What Will Work Best for You?

Choosing between BPI and BPR is a crucial strategic decision. There are multiple factors to consider, such as:

Need for Change

What’s the current state of the process and its inefficiencies? Fundamentally flawed or outdated processes call for BPR. Eliminating fundamental flaws or updating your entire process with incremental changes can take a long time — not practical. However, BPI is a more suitable choice when the process is relatively sound but has some areas of inefficiency.

Suppose you’re a software development company. You’re struggling with lengthy approval cycles, siloed communication, and inconsistent quality standards because of an outdated development process. This warrants a complete process overhaul — you can’t afford to compromise on quality for long, can you?

Alignment With Strategy

Does the process align with your strategic goals? If a process no longer meets your business’s evolving needs or is preventing you from achieving your goals, it’s time to reengineer the process. Conversely, if your process is fundamentally aligned with your strategic objectives, but requires optimization to improve efficiency and customer satisfaction, BPI is the way to go.

For example, BPR is a better choice for an ecommerce company that wants to differentiate itself through personalized customer experiences and finds its current sales process rigid and transactional. But BPI makes more sense if the process is already customer-centric and requires additional personalization.

Risk Appetite

Assess your risk appetite before reengineering a process — can your business accept the disruption that comes with dismantling a key process and reimplementing it? For example, if a small manufacturer plans to transition from traditional batch production to lean manufacturing, the cost of implementing the new process and the halted production can translate to a major cost for the business.

Available Resources

BPI is less resource-intensive than BPR. Even when you’re running low on cash or don’t have the expertise to implement a radical shift in your process, you can make small improvements to your process over time.

 

 

Enhance Business Processes with Blanc Labs

Blanc Labs helps businesses like yours not only choose the right way forward but also offers comprehensive assistance to implement incremental changes strategically or re-engineer processes from scratch. If you need help navigating a change in business process, get in touch with us.

What is the role of a Business Process Improvement Specialist? 

Financial Services | Business Process Improvement

What is the role of a Business Process Improvement Specialist? 

February 16, 2024
Business Process Improvement Specialist in Canada

What is the role of a Business Process Improvement Specialist in Canada?

Business process improvement (BPI) involves analyzing current processes, identifying room for improvement, and redesigning processes to make them more efficient. The problem? Analyzing processes, using data to find inefficiencies, and redesigning and implementing processes with minimal disruption requires skill and experience. That’s where a business process improvement specialist steps in. 

You might tackle various challenges when working to improve your processes. According to Capgemini, the most prominent business process management challenges are functional silo culture and fragmented budgets. 

Redesigning processes while tackling these challenges can be overwhelming, but specialists are equipped with the experience needed to make the transition smoother. In this guide, we discuss the business process improvement workflow and how a specialist can make things easier for you.

The Need for Business Process Improvement before Automation

You’re investing in automation to improve business processes. Before you put money on the table, it’s vital to learn how this investment will impact your business’s efficiency and bottom line.

At its core, business process improvement is about driving efficiency and improving performance through streamlined operations. A critical analysis of business processes and workflows enables you to identify bottlenecks and inefficiencies, allowing you to focus efforts on automating the right processes.

Business process improvement is undeniably mission-critical to make your business future-ready, but it’s also important to:

  • Develop a competitive advantage: Prioritizing continuous improvement and standardizing processes can help build competitive advantages like cost leadership, differentiated products or services, better quality, scalability, and agility.
  • Improve efficiency: Zeroing in on processes you can automate or streamline improves efficiency and output. For example, you can use technologies like intelligent document processing (IDP) to streamline invoice processing. This frees up your finance team to focus on more strategic tasks like cash flow analysis.
  • Elevate customer experience: Modern customers have some ground rules. They want fast responses, consistent experiences, and personalized interactions. Modern lenders provide hassle-free digital experiences to SMB clients, where document collection is a single step and approvals take hours and not weeks.  

“The fact is that consistency on the most common customer journeys is an important predictor of overall customer experience and loyalty. Banks, for example, saw an exceptionally strong correlation between consistency on key customer journeys and overall performance in customer experience.”

The Three Cs of customer Satisfaction, McKinsey & Company

  • Foster a culture of innovation: Striving for continuous improvement encourages critical thinking, offers your team a platform for experimentation, and rewards innovation. For example, if you’re a financial institution trying to automate your loan origination process, a culture of innovation would encourage employees to take charge of every step, from process analysis to pilot implementation.

Business Process Improvement Workflow

Before you take the first step, see if you can get a business process improvement specialist on board.

Their experience and expertise go a long way in minimizing workflow disruption and efficiently designing and executing new workflows. With that in mind, let’s talk about how you can improve business processes.

Process Mapping

Process mapping involves creating a visual representation of your current business processes. You map every step, interaction, and decision point in your workflow from start to finish when mapping a process.

This map gives you a starting point to understand how the current process works. Identifying bottlenecks or ways to make a process more efficient is easier when you can view the process rather than just verbally discussing the steps in a process.

Root Cause Analysis

Time to play detective. Root cause analysis involves digging deeper into finding the underlying reasons behind a specific problem or inefficiency. For example, if you’re a financial company experiencing delays in processing customer payments, here’s what finding the root cause might look like:

  • Why are employees encountering difficulties processing the payments? Probably because employees are spending time fixing errors in payment records.
  • Why are there discrepancies in the payment records? Maybe the outdated system is causing technical problems or employees need more training.
  • Why are we using outdated systems and not investing in training? Lack of budget.

 

This is how root cause analysis takes you to a problem’s roots. In the example above, the finance team could request additional funds in the next quarter to invest in a system upgrade and training to process customer payments faster.

Blanc Labs’ Business Process Improvement Framework

Cause and Effect Analysis

Use techniques like fishbone or Ishikawa diagrams for a visual representation of the cause-and-effect relationship between factors impacting your business processes and problems.

Categorize problems into multiple buckets like people, processes, equipment, and external factors. This will help you gain insights into various elements that impact your business processes and prioritize the ones with the biggest positive impact.

Statistical Process Control

Numbers don’t lie — statistical process control (SPC) helps you understand your process through numbers. SPC enables you to identify trends, detect abnormalities in the process, and make data-driven decisions to improve your process.

Design of Experiments

Once you’ve identified a problem, you need a systematic and structured way to identify potential improvements and test them. Experimentation helps you do exactly that.

It’s the same as stress-testing your processes under various scenarios. You design an experiment, manipulate relevant variables, and measure their impact on the business process. This enables you to understand the impact of a change before you fully implement it, allowing you to minimize disruption.

How BPI and Intelligent Automation can improve the Borrowing Experience for Small Business Owners

BEFORE
AFTER

A Frustrating Lending Experience

Small business owner_loan approval

Alex applies for a loan with a traditional commercial lender to expand her cafe into a local chain. The onboarding process is frustrating and time-consuming, with lengthy paperwork and no guidance. The lender’s inaccurate reporting and static risk assessment results in conservative loan terms that fail to acknowledge her business’s recent growth and the positive trends in the local market. This jeopardizes Alex’s ability to secure an ideal property for her new location and erodes her confidence in the lender’s support for her business growth. Throughout the process, Alex experiences an impersonal service, devoid of the understanding and support crucial for an entrepreneur.

Small business owner_loan approval

A Transformative Lending Experience

Small business owner_lending

Six months later, Alex chooses a lender with a digital platform and automated loan decisioning for her next expansion. With streamlined onboarding, automated data extraction, and intelligent chatbot, the experience is transformative. Real-time updates, automated tracking, intelligent document processing, and dynamic risk assessment make loan processing efficient and user-friendly. Alex secures her loan promptly and finds the perfect location for her new café. The chatbot also offers personalized customer experience, making Alex feel valued.

Small business owner_lending

The Role of a Business Process Improvement Specialist

Process mapping, analysis, and re-engineering require a specialist. A specialist has the knowledge and experience required to minimize workflow disruption and effectively realize process efficiencies. Here’s how a business process improvement specialist helps:

Pain Point Discovery

Think of business process improvement specialists as Sherlock Holmes. They come in, zoom into your processes, and find pain points that hinder efficiency.

They don’t just observe. They conduct interviews and surveys, ask the right questions, and listen attentively to discover areas that are inefficient, error-prone, and not aligned with organizational goals. The discovery phase is vital — it sets the stage for targeted improvements.

Process Analysis

When the specialist finds room for improvement in a process, they pull up their sleeves and start dissecting it.

They map every step, decision point, and interaction in your process and use techniques like value stream mapping, data analysis, and flowcharting to take a closer look at how the process currently operates and where bottlenecks and inefficiencies lie. This lays the groundwork for informed and data-backed decision-making and process design.

Opportunity Analysis

Insights from process analysis equip the specialist to shift focus to opportunity analysis. They consider the benefits of addressing a pain point and improving the process versus the cost — do the monetary benefits of redesigning the process justify (and exceed) the cost of making those improvements?

Cost-benefit analysis requires input from multiple experts. For example, if a process redesign could improve customer experience, what would be the benefit, in monetary terms, of improved customer experience? The specialist might need insights from multiple teams like sales and accounting to understand the monetary impact.

They also consider the risks of redesigning the process. Will the redesign require significant changes? How long will it take the employees to get through the learning curve and achieve full efficiency? The specialist understands these risks and identifies ways to mitigate them.

Implementation Design

After factoring in the costs and risks associated with redesigning a process and verifying the viability of a process redesign, the specialist transitions into creating and implementing a more efficient process design.

The redesigned process might involve one or multiple changes like a more efficient workflow, new technology, or a redesigned organizational structure. For example, the specialist might use enterprise automation solutions to automate repetitive tasks, potentially multiplying your team’s productivity or include GenAI to enable the next level of customer service.

The specialist develops a detailed implementation plan including the details of redesign, clear timelines, responsibilities, and performance metrics. They collaborate with stakeholders during this phase to ensure buy-in and alignment with organizational objectives.

Business Process Improvement Integration

Process improvement isn’t a one-off activity. To truly reap the benefits of process improvement, the specialist must integrate the improvement initiatives into the organization’s culture.

The specialist can help you develop change management strategies to inculcate a culture rooted in continuous improvement; this is vital to engaging employees across the organization and encouraging them to contribute ideas that drive change.

For example, the specialist can train teams to build applications quickly using low-code platforms. This enables teams to solve problems independently and quickly. Of course, there are many ways to develop a culture of continuous improvement depending on factors like industry. For example, Bill Keen, CEO of Keen Wealth Advisors, explains:

By owning mistakes and building processes to prevent the mistakes that do occur from happening again, you will build trust among your customers and a culture of continuous improvement among your staff.

With training and efficient feedback mechanisms, you can sustain process improvements for a long time and ingrain them in your company’s DNA.

Business Process Improvement with Blanc Labs

We firmly believe that transformation happens over time and that process improvement is an ongoing journey. Our approach helps you practically redesign processes effectively and consistently, and in a way that fits your business’s unique needs.

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