Tag: automation

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Digital Transformation Vs. IT Modernization: What’s the Difference?

Digital Transformation vs IT Modernization_Blanc Labs

In today’s dynamic business landscape, organizations face numerous challenges such as economic volatility, supply chain complexities, evolving work styles, competing for talent, fickle consumer trends, market commoditization, sustainability concerns, and more. As stated in Forrester Research’s 2021 report, “In the 2020s, the one constant will be disruption.” CIOs play a crucial role in navigating these challenges and driving business transformation. The ability to embrace disruption will set leaders apart from laggards in this ever-changing landscape. 

In this context, it is important for technology executives to make the choice between modernizing legacy processes or instituting a complete transformation of their systems. Yet, many organizations struggle to understand the difference.  

In this article, we explore both digital transformation and modernization and why transformation is mission-critical for modern businesses. 

Digital Transformation Vs. IT Modernization 

Digital transformation has a broader scope and touches  almost every facet of a business. IT modernization’s scope is limited to upgrading existing systems. 

Don’t get us wrong. Modernizing your tech stack  is just as critical to your business as transformation. The 2023 CEO Priorities survey shows that 51% of CEOs think low digital maturity/technical capabilities are barriers to creating business value with AI. As companies try to achieve digital maturity, they’ll go through multiple IT modernization iterations. 

Let’s dig into the differences between digital transformation and IT modernization.

Digital Transformation in Practice 

A digital transformation is meant to change or evolve some of the DNA of an organization such that a company is better equipped to compete in a constantly evolving  environment where customer expectations are changing at breakneck speed.  Technology can and should play a central role in a digital transformation but technology alone will not equip a company to operate effectively in this “new normal”, this requires a careful choreography of people, processes, and technology.  

In addition to being better equipped to meet evolving customer needs and expectations, digital transformation can be your doorway to scaling your business by entering new markets, eliminating or minimizing process inefficiencies, and becoming more agile. 

Domino’s is an excellent example of how digital transformation can change your company’s growth trajectory. Back in the day, the pizza chain was a brick-and-mortar restaurant that promised to deliver pizzas in under 30 minutes. 

Competitors started offering a similar service. So Patrick Doyle, the CEO of Domino’s in 2011, decided to create an app that allowed customers to order pizza within seconds. Currently, Domino’s is testing delivery via autonomous vehicles to stay ahead of delivery services like DoorDash and Uber Eats. 

Essentially, digital transformation involves a fundamental shift in various business aspects, like internal processes and your business model. The goal is to achieve sustained growth and become a more competitive business. 

Modernization in Practice 

Modernization is often confused with digital transformation, but they are not the same. Modernization focuses on building on top of existing systems. For example, you could implement cloud computing and AI without changing legacy processes. 

Suppose you’re a bank that is looking to improve its mortgage origination process. You currently require staff to enter customer details manually. Over the next quarter, you want to implement an automated loan origination system that eliminates almost all the mundane tasks in the origination process. 

For this, you’ll use technologies like AI, natural language processing (NLP), optical character recognition (OCR), and robotic process automation (RPA) through third-party integration or by building a new solution. These technologies will enable you to automate tasks like document processing and customer onboarding. 

These technologies can help you re-engineer the origination process to make it more efficient—without disturbing your underlying mortgage process or the business model. 

Why Digital Transformation Matters 

Digital transformation is right for you if you’re in a rapidly evolving market and want to stay ahead of the competition. 

Since digital transformation involves a more comprehensive change in your business’s model and operational processes, it can be resource and time-intensive, especially in the absence of first-hand experience on the multi-faceted nature of transforming an organization.  Let’s go back to our mortgage example to understand the difference between transformation and modernization.  Consider if the mortgage lender wanted to move from being a traditional, broker-based lender to a digital direct lender and the relative time, cost and complexity required to stand up a whole new business model.   

IT modernization is relatively less resource and time-intensive. Modernization is an excellent place to start if you’re struggling to meet customer expectations or efficiency targets because of outdated technology. 

Revamping your technological systems will help you reduce costs, operate more efficiently, and scale your business. 

 Digital transformation matters to two types of businesses: 

  • Businesses that want to stay ahead of the curve by implementing the latest technologies in a fast-evolving market. 
  • Businesses that need to survive in a market where other businesses failed to implement new technologies on time. 

 

Digital transformation isn’t easy for either of these businesses to implement without an experienced team—only about 30% of companies navigate digital transformation successfully. 

However, once you’ve successfully completed digital transformation, your business stands to benefit on multiple fronts. 

The pandemic caused the most recent surge in digital transformation. Businesses were forced to adapt to an environment where employees prefer remote or hybrid work models, but they benefited greatly from the changes that followed. 

That’s exactly why more businesses are excited about digital transformation. In fact, according to the World Economic Forum, the combined value of digital transformation to society and industry will exceed $100 trillion by 2025. 

What Digital Transformation Benefits_Blanc Labs

Here are some benefits of digital transformation that highlight why it can be a game changer for your business this year: 

Improves Customer Experience 

Customer expectations have risen significantly over the past decade. They prefer businesses that offer a great experience in all customer-facing aspects. 

Enable  Data-Driven Decision Making 

Data analytics is one of the most critical capabilities you gain from digital transformation. With modern tech, it is typically much easier to securely access and manipulate data that can be used to unlock valuable insights about customers, competitors, and internal processes. 

Better Resource Management 

Digitally-powered businesses use hundreds of apps and store data in multiple places. The lack of interoperability and data silos can make business hard. Digital transformation involves integrating these digital tools, allowing you to consolidate dispersed data sets and apps. 

Improves Team Collaboration 

Adding the right digital collaboration tools to your toolkit can be critical to building a collaborative environment in the workplace. They allow teams to collaborate outside the office space or country. If your team is spread across time zones, you can use async communication tools for better collaboration. 

Increases Scalability 

Digital transformation gives you the flexibility to grow faster. It can help reduce time to market and make product or service improvements faster. You can also serve clients in a larger geographic area and communicate with your clientele more effectively. 

What Does it Take to Create Digital Transformation? 

Digital transformation needs more than just technical expertise. It’s a massive undertaking where multiple factors contribute to your success. 

Here are things to focus on when transforming your business digitally: 

Digital First Culture 

Transforming your business requires agility and an attitude to pursue the latest technologies proactively. Building a digital-first culture, where employees proactively look for opportunities to use digital solutions to help the business achieve its goals, is critical to successfully transforming your business. 

Culture is a critical part of Gartner’s ContinuousNEXT approach to digital transformation. The Gartner experts who coined the term cite culture as a major barrier — 46% of CIOs identify culture as the most significant barrier to digital transformation. 

A report by MIT and Capgemini explains that focusing on the following seven cultural attributes can be vital to building a digital-first culture: 

  • Innovation: The prevalence of behaviors that support taking risks, thinking disruptively, and exploring new ideas. 
  • Digital-first mindset: A mindset where everyone, by default, thinks of digital solutions first. 
  • Customer-centricity: The use of digital tools to improve customer experience, expand the customer base, and co-create new products. 
  • Open culture: The extent of partnership with third parties, including vendors and customers. 
  • Agility and flexibility: Decision-making speed, dynamism, and your company’s ability to adapt to evolving market demands and technologies. 
  • Data-driven decision-making: The use of data to make better decisions. 
  • Collaboration: The strategic creation of teams to make the best use of the company’s human resources. 

Change Management 

 Often, the most overlooked aspect of a digital transformation is the amount of change management and capability development required to enable team members to excel in their new or evolved roles. One takeaway that we’ve learned from our experience is the need to have a strong leadership commitment and a high level of conviction and alignment across the senior leadership team on the transformation objectives, priorities, and plan to undertake the transformation effort at an organization. . 

 When communicating a change, remember that the benefits of change may be evident to you. Yet, your team might see change as a signal to step out of a workflow they’re comfortable with and learn new skills. 

Resistance will snowball when one employee who feels that way communicates with colleagues. Change management can help prevent or at least minimize this resistance to change. 

Here are three critical elements of managing change: 

  • Plan before you start: Change management should start before digital transformation. Risk analysis and assessing the organization’s readiness are great ways to lay the foundation for your change management strategy. They involve identifying organizational attributes like culture and characteristics of change. 
  • Change management: This is where you go from planning to execution. You keep communicating your digital transformation plans, address concerns regarding the plan, and train employees. 
  • Feedback: Change management doesn’t end after executing your change management strategy. Seek feedback from employees about the change. If you see reluctance, take corrective actions to ensure resistance doesn’t snowball. 

Data-Driven Organization 

Digital transformation is highly data-driven. Managing data — storing and processing data and ensuring data integrity — are one of the first things you’ll need to work on when you start the digital transformation process. 

Data provides a unique insight into your operations. Once you’ve achieved a higher level of operational transparency and gained a deeper understanding of core business processes using data, you’ll be able to identify barriers to digital transformation. Data will also enable you to improve and optimize your transformation strategy continuously. 

Companies like Airbnb and Amazon hold massive volumes of data. These companies are great examples of data-driven organizations. This data allows them to personalize customer experiences and stay one step ahead of the competition. 

Emphasis on Quality 

When you’re adamant about delivering quality, you’ll need to ask yourself — is the business prepared to ensure a high level of quality during the digital transformation journey? 

Going all in at once is a bad idea. Digital transformation requires an incremental approach where you plan, test, and validate ideas every step of the way. This will allow you to stay prepared for potential pitfalls and optimize your strategy as you go. You’ll avoid complete disasters, which can result in loss of money, trust, and reputation. 

Taking an incremental approach makes your digital transformation journey smoother and ensures you maintain high quality throughout the transformation process. 

Begin Your Digital Transformation Journey 

Digital transformation can be challenging to navigate without an experienced partner. 

At Blanc Labs, we understand each organization has unique needs. We offer advisory and consulting services to gain a complete understanding of your most pressing challenges and help you start your digital transformation journey. 

Book a discovery call with us today to learn more. 
 

Book a Consultation

Articles

The Benefits of an Automated Loan Origination System

The benefits of an automated loan origination system collectively add immense value for you and your customers. 

Deloitte and the Institute of Management Accountants (IMA) surveyed finance professionals across the globe and found that respondents plan to implement or are already implementing robotic process automation (RPA) (22.8%) and artificial intelligence (AI)/machine learning (ML) (21.4%). 

Why should your organization be left behind? 

In this article, we explain the benefits of an automated loan origination system and help you understand how exactly it can impact your loan origination process. 

Automated Loan Origination Vs. Manual Loan Origination 

Manual loan origination is a loan origination system where you handle the customer’s application manually, from processing documents to assessing the customer’s credit risk profile. 

On the other hand, an automated loan origination system allows you to automate the end-to-end loan process, from application to documentation, underwriting, and administration. 

Automated loan origination systems typically use a combination of technologies like intelligent document processing (IDP), RPA, AI, and ML. 

Automating the loan origination process solves two critical challenges for lenders: 

  • Keeping the turnaround time under control 
  • Finding specialists who can reliably complete the pre-underwriting process


An automated loan origination system involves using software solutions. Your team will likely experience a learning curve, and that’s why you should work with a company that can ensure the learning curve is gentle. Blanc Labs partners with UiPath to provide automation solutions—learn how Blanc Labs hyper automated a client’s loan origination process. 

Benefits of Automated Loan Origination Before and After

The Benefits of Automation the Loan Origination 

Like with any other investment, you’re probably asking what you stand to gain after investing in an automated loan origination system. Let’s talk about the most prominent benefits of automating loan origination. 

Improved Productivity 

According to a McKinsey study, automating the KYC process can increase the number of cases processed by 48%. Automation also minimizes the risk of error, further improving productivity. 

Solutions powered by AI and ML can fast-track loan processing, allowing your team to process more applications per month. Your staff won’t have to handle paperwork manually or spend hours hunting for minor details in the customers’ documents. 

This allows your team to dedicate more time to other revenue-generating activities and exceeding customer expectations instead of mundane tasks. 

Think about the KYC (Know Your Customer) process as an example. You could have a team member collect KYC documents, verify them, and store them for future reference. Or you could use IDP to automate all these steps, allowing your team to focus on sales and support. 

Once you receive a digital copy of KYC documents from a loan applicant, you can use IDP to input the data into your system — with zero manual effort. 

An Accenture case study explains the impact of automation on one of their banking clients. The case study describes how Accenture helped them create new automated processes that improved productivity by over 40%. 

Accurate Decision Making 

The best automated loan original systems use your strategy and data in the system to make accurate decisions. Machine learning algorithms can even provide deeper insights for decision-making by eliminating data silos. 

For example, you might have applicants you can’t score based on traditional credit models. Machine learning models can help assess the risk of such applicants, allowing you to achieve financial inclusion objectives without breaching your risk threshold. 

According to a report by McKinsey, you can automate various parts of credit decisioning or make better decisions based on the data collected by the automated loan origination system. Here’s how an automated loan origination system can help improve credit decisioning: 

  • Credit qualification: Using automated systems to qualify a largely unbanked or underbanked segment by analyzing thousands of data points that were previously inaccessible (such as data from social media and browser history). 
  • Limit assessment: Determining the maximum amount to lend a customer by assessing data from financial statements, tax returns, and other documents using optical character recognition (OCR) as well as new data sources like email and e-commerce expenditure (with the customer’s permission). 
  • Pricing optimization: Analyzing an applicant’s risks with more data instead of simply relying on traditional credit scoring models allows for determining a more accurate rate of interest while keeping risk costs low. For example, ML models can use natural language processing (NLP) to draw insights from a customer’s interaction with the sales reps or determine a customer’s propensity to buy based on the types of financial products. 
  • Fraud management: Detecting fraud is critical when loan origination processes move fast. There are various ways to detect fraud effectively using AI. For example, you might use image-analytics models to interpret a person’s expressions before the brain has a chance to control them. 

 

You can create rules based on these insights to automate one or more parts of the loan origination process, and you can also change these rules over time. For example, the World Bank uses a Decision Authority Matrix to automatically leave low-risk decisions to RPA, while some critical decisions require the involvement of the President. 

Well-Defined Workflows 

Automated systems help create well-defined workflows. The system gives you more control and visibility over the process, allowing you to regularize processes like storing documents, manual approvals, and assessment of an applicant’s risk. The lending automation system relies on the information already in the system and trigger-based actions to accomplish this. 

With a well-defined workflow, the next step is always clear. But in some cases, there may be caveats. For example, the customer might have requested a loan for an amount larger than your brand can approve. You need to communicate this to the customer along with the amount your institution can lend. 

The best automated loan origination systems can use rule-based decision-making to automatically trigger a notification to the customer, informing them about the maximum amount that can be lent by your branch. 

You can also address other caveats using the rules-based mechanism. For example, you can configure the system to make complex calculations based on the underwriters’ criteria for a consistent approval workflow. 

Enhanced Scalability 

Scalability is one of the most significant bottlenecks for any lender that uses manual processes. Here are the problems with manual loan origination: 

  • Hiring fast enough to meet a sudden spike in demand is tough. 
  • Scaling back during an economic downturn can be challenging. 

 

The Origination Insight Report by ICE Mortgage Technology (a leading cloud-based provider for lenders) reported that, on average, lenders take about 50 days to close a loan. 

Lenders can overcome this bottleneck with automation. You can automate various parts of the process to increase scalability, such as: 

  • Collecting pre-qualification data: A team member might spend hours manually identifying pre-qualified candidates, but automating can earn all of that time back for your team member. Assessing forms using IDP and AI can help automatically select pre-qualified customers at scale. 
  • Streamline information management: Paperwork, whether physical or digital, can get messy in large volumes. Automation solutions can help you and your customers fetch the correct information quickly without shuffling through a stack of papers. This allows you to work faster and process more applications each month. 
  • Data extraction: You can extract data from physical and digital documents using IDP, AI, and NLP. These technologies can transmit the extracted data to business applications like a customer relationship management (CRM) or enterprise resource planning (ERP) system. Whether you’ve approved 100 applications or 1,000, you won’t have to spend a single minute migrating data manually when you use these technologies. 

Insights for Continuous Improvement 

An automated system collects a large volume of internal data while performing repetitive tasks. The same system can put this internal data in perspective by drawing insights from big data. 

An automated system can offer four types of analytics: 

  • Descriptive analytics: Involves looking at historical data to identify trends. This type of analytics helps you learn more about your customers — what customer traits influence loan performance? When lending to high-risk borrowers, which loan structure and tenure minimize the risk of default? 
  • Diagnostic analytics: Helps understand why something happened based on historical data. 
  • Predictive analytics: The system’s algorithm predicts what will happen based on data. 
  • Prescriptive analytics: Involves using AI, ML, and structured and unstructured data to answer how you can make something happen. Example: you can determine the geographic locations where you’re most likely to see success for a specific type of loan product. 

The best automated systems auto-generate reports and summaries, so you can quickly go to your dashboard and get key metrics for your loan origination process. 

Better Customer Experience 

Digital originators are quickly gaining market share and giving banks a run for their money. The reason? They match a modern customer’s need for convenience, speed, and transparency. 

The faster you process applications, the better your customers’ experience. The problem, though, is that the loan origination workflow is often extensive. You need to assess the applicant’s credit profile and collateral and check all the regulatory boxes. 

An automated loan origination system can do much of the heavy lifting for you. It can help make decisions based on the customers’ credit profiles, verify the validity of the collateral, as well as ensure compliance. 

You’ll be able to focus on delivering improved customer experiences by minimizing processing times and using your own time to focus on value-adding tasks. As McKinsey explains in one of its articles: 

“Instead of processing transactions or compiling data, [the operations staff] will use technology to advise clients on the best financial options and products, do creative problem solving, and develop new products and services to enhance the customer experience.” 

Automate Loan Origination with Blanc Labs 

Selecting the right partner to implement automated loan origination helps ensure you have the support you need to address the complexities of lending automation. That’s where Blanc Labs comes in. 

Blanc Labs can create a personalized automation system for your organization. The three steps Blanc Labs uses to help lenders include assessing your needs, streamlining your loan origination processes and related platforms, and creating an automation system using technologies like IDP, AI, and ML. 

Book a consultation or discovery session with Blanc Labs to learn how we can help automate your end-to-end loan origination process. 

Articles

10 Tips to Successfully Implement RPA in Finance

Automation has taken the finance industry by storm, and for all good reasons. Banking automation technologies like Robotic Process Automation (RPA) come with the promise of streamlining processes and increasing efficiency.  

According to Forbes, RPA has the potential to transform the way finance functions, from reducing manual errors to freeing up valuable resources. To help you maximize the benefits of RPA in finance, we’ve put together a list of 10 tips for successful implementation. But first, let’s take a step back and explore what RPA is.  

What is Robotic Process Automation (RPA)? 

RPA is the use of software robots to automate routine and repetitive tasks like document processing, freeing up employees to focus on strategic activities that can lead to better customer service or innovations that could meet customer expectations.  

The bots are programmed to follow specific rules and procedures to complete a task, just like an employee. They can interact with various software applications and systems, such as spreadsheets and databases, to collect and process data. The bots can also make decisions, trigger responses, and communicate with other systems and software.  

When a task is triggered, the bot performs it automatically, eradicating the scope of errors that may be produced through manual processes. The process is monitored and managed by a central control system, allowing adjustments and updates to be made as needed. 

Think of RPA as a digital workforce, working tirelessly in the background to complete tasks that would otherwise take hours to complete. With RPA in finance, your financial institution can increase efficiency, reduce costs, and improve the accuracy of its processes.  

The Use of RPA in Banking Automation 

There are many ways in which RPA can be used in banking automation. Here are some of them: 

Customer Service Automation 

RPA is capable of automating routine customer service tasks such as account opening, balance inquiries, and transaction processing, allowing bank employees to focus on more complex customer needs. 

Loan Processing 

RPA in banking and finance can streamline the loan processing workflow by automating repetitive tasks such as document collection and verification, credit score analysis, and loan decision-making. 

Fraud Detection and Prevention 

In 2022 alone, banks and financial institutions lost $500K to fraud. Technologies like RPA can analyze vast amounts of data to detect and prevent fraud in real-time, improving the accuracy and speed of fraud detection. It may also report any suspected fraud to the banking authorities as soon as it is discovered. 

KYC and AML Compliance 

Verification and compliance document processing can eat up a major share of your institution’s resources. RPA can automate the process of collecting, verifying, and analyzing customer information, helping banks to comply with KYC (Know Your Customer) and AML (Anti-Money Laundering) regulations. 

Back Office Operations 

RPA can automate various back-office tasks such as data entry, reconciliation, report generation, monthly closing, and management reports, freeing up employees to focus on more strategic initiatives. 

Payment Processing 

Manual data entry in payment processing can lead to manual errors and longer processing time. RPA can automate the payment processing workflow, including payment initiation, authorization, and settlement, reducing the risk of errors and improving efficiency. 

Risk Management 

Banks and financial institutions are constantly at risk from various sources. RPA in finance can help institutions identify, assess, and manage risks by automating data collection, analysis, and reporting, improving the accuracy and speed of risk assessments. 

Internal Compliance Monitoring 

RPA can automate the process of monitoring and reporting on compliance with internal policies and regulations, reducing the risk of non-compliance and improving overall compliance management. 

 The potential of RPA in banking and finance is unlimited. When combined with Intelligent Automation technologies, RPA can leverage Artificial Intelligence (AI) and Machine Learning (ML) to provide more intelligent process automation. While the technology in itself is efficient, financial institutions must know how to implement it for maximized benefit.  

10 Tips for Successfully Implementing RPA in Finance 

According to the Deloitte Global RPA survey, 53% of organizations who took part in the survey have already begun their RPA implementation. The number is expected to rise to 72% over the next year. Entering the RPA race can be quick, but managing and scaling it is a different ball game. Before getting started with automation initiatives, it is important to consider the following tips.  

Start Small 

While RPA might seem useful to rejuvenate all of your systems and processing, it is important to consider the business impact and start small. Beginning with a smaller project, for example, a single process or department can help build momentum and demonstrate the benefits of RPA. It also allows the organization to gain experience and develop a better understanding of the technology before scaling up. 

Define Clear Goals 

The key to successful RPA implementation rests in your goals. Decide what you want to achieve with RPA in consultation with your IT department. Having a clear understanding of the goals and objectives of the RPA implementation will ensure that resources are allocated appropriately and that the project stays on track. Aim for specific, measurable, achievable, relevant, and time-bound (SMART) goals.  

Involve Stakeholders 

Engaging stakeholders, such as the management, finance employees, and IT, can help build better design and smoother change management for the RPA implementation. It also ensures that the RPA system is well-integrated across departments and addresses the needs and concerns of all stakeholders. 

Assess Processes 

When a financial institution leverages too many bots to automate processes, it results in a pile of data. They may be tempted to use ML on the data and create a chatbot to make customer queries easier. However, it can lead to  a poorly planned ML project. Thus, a thorough assessment of the processes is critical to ensure that the RPA implementation does not get sidetracked. This assessment should include an analysis of the tasks, inputs, outputs, and stakeholders involved in the process. 

 

10 tips to implement RPA in Finance_infographic_Blanc Labs

Choose the Right Tools 

Selecting the right RPA tools and technology is critical to the success of the implementation. Decide the mix of automation technologies your institution requires before reaching out to a vendor. Factors to consider include the cost, scalability, and ease of use , as well as its ability to integrate with other systems and applications. 

Define Roles and Responsibilities 

Clearly defining the roles and responsibilities of the RPA team, including project governance, testers, and users, is important to ensure that everyone knows what is expected of them. Remember that automation is a gradual process, and your employees will still need to interfere if it is not properly automated.  

Ensure Data Security 

Protecting sensitive data and customer information is a key concern in finance. RPA needs to be implemented in such a way that data security remains unaffected. Discuss with your vendor about strong security measures to ensure that data is protected and that the confidentiality of customer information is maintained. 

Plan for Scalability 

There are thousands of processes in banks and financial institutions that can use automation. Thus, the RPA implementation should be planned with scalability in mind so that the technology and processes can be scaled up as needed. This helps to ensure that the RPA can be combined with AI and ML technologies as necessary and the implementation remains relevant in the long term. 

Monitor and Evaluate Performance 

Continuously monitoring and evaluating the performance of the RPA bots is critical to ensure that they are operating effectively and efficiently. Also, do not forget to keep HR in the loop so that employees are informed and trained about the changing processes and how to use them in a timely manner. Regular evaluations should be conducted to identify areas for improvement and to make adjustments as needed. 

Foster a Culture of Innovation 

Encouraging a culture of innovation and experimentation can help to ensure that the organization is prepared for the future. Consult your IT department and automate your entire development lifecycle to protect your bots from disappearing after a major update. Invest in a center of excellence that can create business cases, measure ROI and cost optimization and track progress against goals.   

Implementation Automation with Blanc Labs 

At Blanc Labs, we understand that every financial and banking institution has unique needs and challenges when it comes to RPA implementation. That’s why we offer tailor-made RPA solutions to ensure seamless implementation for our clients.  

Our RPA systems are designed to be flexible and scalable, allowing our clients to start small and grow as needed. We provide end-to-end support, from process assessment and design to implementation and ongoing assistance, to ensure that our clients realize the full benefits of RPA. 

Booking a free consultation with us is the first step toward successful RPA implementation. Our team of experts work closely with each client to understand their specific requirements and goals to build a customized RPA solution to meet their needs. 

Articles

Banking Automation: The Complete Guide

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

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

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

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

What is Banking Automation? 

Banking automation involves automating tasks that previously required manual effort. 

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

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

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

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

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

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

Generative AI and Banking Automation

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

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

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

 

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

What is RPA? 

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

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

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

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

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

You can use RPA in banking operations for various purposes. 

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

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

The Need for Automation in Banking Operations 

Banks need automation to: 

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

 

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

Why Banks Need Automation_Blanc Labs

To Deliver Faster, Personalized Customer Experiences 

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

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

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

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

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

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

To Improve Cybersecurity 

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

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

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

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

For Better Decision Making 

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

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

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

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

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

To Empower Employees 

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

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

Challenges Faced by Banks Today 

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

Inefficient Manual Processes 

Manual processes are time and resource-intensive. 

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

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

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

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

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

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

Automation Without Integration 

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

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

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

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

Increase in Competition 

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

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

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

Benefits of Banking Automation_Blanc Labs

Benefits of Automation in Banking 

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

Improves Operational Efficiency 

An error-free automation system can supercharge operational efficiency. 

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

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

Makes Processes Scalable 

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

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

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

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

Cost Reduction 

Automation helps reduce costs on multiple fronts: 

a. Stationery 

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

b. Human error 

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

c. Increased employee satisfaction 

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

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

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

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

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

Customer Satisfaction 

Automation can help meet customer expectations in various ways. 

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

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

How fast? Ideally, in real-time. 

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

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

Better Risk Management 

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

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

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

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

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

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

Blanc Labs’ Banking Automation Solutions 

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

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

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

Articles

IDP vs. RPA vs. OCR

IDP vs RPA Blanc Labs
Illustration by Storyset

Financial institutions deal with a lot of data from various sources like forms, emails, invoices, PDFs, etc. daily. Processing this unstructured data manually is time-consuming and requires a lot of effort. It can also be prone to errors, which can have costly consequences. This can take away from the time and energy that employees could be spending on more strategic tasks. 

Automation technologies like IDP (Intelligent Document Processing), RPA (Robotic Process Automation), and OCR (Optical Character Recognition) can take manual document processing off your hands.   

If you are wondering which one you should choose among IDP vs. RPA vs. OCR for the digital transformation of your financial institution, you are in the right place. Here we break down each banking automation technology to help you choose the best one.    

What is RPA? 

RPA is a technology that allows organizations to automate repetitive, routine tasks typically performed by humans. These tasks include data entry, document processing, customer service interactions, and back-office functions such as compliance, risk management, and accounting. 

What is possible with RPA, and where does it fall short? 

Banks are known to be heavily regulated, and compliance is a critical part of banking operations. This is where RPA can play a significant role by automating compliance-related tasks, such as KYC (Know Your Customer), AML (Anti Money Laundering), and other regulatory data management. It can also automate data migration, trade execution, data validation, data updates, and perform simple copy/paste functions.  

However, RPA in banking automation also has some limitations. RPA requires a developer or GUI window to operate. Thus, RPA can only be used to automate simple screen-related tasks. It is limited to automating tasks that are highly structured and rule-based and is not suitable for tasks that require human judgment or decision-making.  

Also, the entire automation process can break if there is an update in the user interface of a linked software. It is an outdated technology that relies on OCR and is not built for modern end-to-end integration.   

What is Intelligent Document Processing (IDP)? 

IDP is a next-generation technology designed to tackle the limitations of RPA. It is a system created to process documents just like humans. If you compare IDP with RPA for banking automation, you will find that IDP is the ideal combination of OCR, Artificial Intelligence (AI), machine learning, and natural language processing.  

IDP is independent of strict rule-based approaches. Due to its flexibility, it can reach and process unstructured data not reachable via RPA. IDP tools also reduce the margin for errors by validating the data and informing the team in cases that need human intervention. 

Here are some reasons why banks need Intelligent Document Processing.

How can IDP help in banking automation? 

IDP can be a valuable tool in banking automation in several ways: 

Account Opening 

You can use IDP to automate extracting information from account opening forms and other related documents. It can reduce the effort and time required for manual data entry and improve the accuracy of the data. 

Document Management 

IDP can index, classify and route documents to the appropriate systems or individuals. Thanks to intelligent document processing, financial institutions can manage documents effectively and quickly retrieve the necessary information. 

Compliance 

IDP can help automate extracting information from compliance-related documents for processes such as KYC, AML, and other regulatory requirements. This way, banks can comply with regulations more quickly and efficiently while reducing the risk of non-compliance. 

Loan Processing 

IDP can enable the extraction of information from loan applications and other related documents such as income statements, credit reports, and real estate appraisals. It can help automate the loan review process, making it faster and more accurate. 

Fraud Detection 

IDP can be used to extract information from documents and match it with other sources to detect potential fraud. In this way, banks can reduce the risk of fraud and losses. 

Read more: The Top Use Cases for Banking Automation

IDP vs RPA 

The choice of automation for document processing boils down to IDP vs. RPA. RPA and IDP are two different technologies used in automation but are sometimes confused with the other.   

The main difference between RPA and IDP is that RPA does not have the native intelligence of AI. RPA cannot consume and analyze data on its own. RPA is limited to mimicking repetitive actions performed on computer screens with a mouse and a keyboard. It is helpful for tasks that don’t require high-level decision-making and is largely outdated. It is often said that AI is ‘the brain’ while and RPA is ‘the hands.’ 

On the other hand, IDP takes automation up a notch by automating documents and absorbing and understanding data to extract actionable insights. Thus, IDP can be considered the future of banking automation. 

RPA works better with structured documents (e.g. claim forms, tax forms ) where IDP works better with unstructured documents (e.g. contracts, handwritten notes). Ideally, an organization should use a combination of RPA and IDP to achieve better operational efficiency. 

What is OCR? 

OCR is a technology used in both RPA and IDP, that reads, extracts, and converts data from images and scanned documents into text for electronic automation and importation. When integrated with automation solutions like IDP or RPA, OCR can efficiently process structured data, eliminating the need for manual data entry and thus minimizing errors. OCR technology also enhances image quality to produce more accurate results.  

While OCR is a step towards automation, it is not very effective in processing unstructured data that most banking institutions deal with every day in large volumes.   

IDP vs RPA vs OCR

IDP vs RPA_Blanc Labs

Blanc Labs’ Document Processing Solutions for Banks 

Blanc Labs’ helps financial institutions like banks, and credit unions fast-track their way to digital transformation. We can help you integrate powerful automation technologies into your processes to increase productivity and reduce manual labor and the scope for errors.   

Our team provides a customized combination of machine learning and artificial intelligence for automating complicated tasks like document processing so that you can save your resources and provide faster and better financial services. 

If your financial institution deals with a ton of documents every day, let us help you put your processing on auto. Book a discovery call with us today, and we will create a seamless document processing solution unique to your needs. 

 

News

Blanc Labs and Daylight are teaming up to help enterprise teams simplify rules-based complex processes

Posted on

Blanc Labs, a technology services company specializing in digital transformation for financial services and healthcare is partnering with Daylight to deliver digital solutions focused on simplifying logic and/or rules-based processes. 

Complex processes are elaborate labyrinths of different checks and balances. 88% of senior IT leaders in North American agree that optimizing complex processes is  both very costly and requires significant resources*. Blanc Labs and Daylight strategic partnership will focus on: 

  • Empowering businesses to easily build digital user experiences that replicate the rules of their business processes
  • Digitize and automate paper-based processes
  • Quickly build connections to legacy applications to deliver a modern end-user experience without the need to rip and replace
  • Optimize ROI from investment in automation by putting business technologists in the driver’s seat

 

“We are committed to helping organizations transition into the digital age by leveraging our deep sector expertise, ecosystem partners, and world-class tech talent to reduce risk and achieve strategic objectives,” said Hamid Akbari, CEO of Blanc Labs. “We believe our partnership with Daylight will be a game-changer for companies looking to do more with less”.

The partnership will focus on developing and delivering end-to-end solutions without displacing the existing tech stack or disrupting IT. 

“Both teams are passionate about empowering teams with the ability to build their own solutions and take charge of improving processes and scaling digital transformation initiatives… I’m excited to see the impact we can make together,” said Art Harrison, CGO of Daylight.

*2022 Daylight Market Survey: 100 IT leaders in North America (Enterprise Orgs with 5000-10000 employees)

About Blanc Labs  

Blanc Labs offers technology solutions that help enterprises become ready for the future. Blanc Labs has developed expertise and bespoke solutions in a wide variety of applications, including financial services, healthcare, enterprise productivity, and customer experience, to help companies rapidly deliver on their digital initiatives. Headquartered in Toronto, Blanc Labs serves the Americas through operations in Toronto, New York, Bogota, and Buenos Aires.

For more information, visit www.blanclabs.com 

 About Daylight  

Daylight makes it easy for your business teams to simplify and digitize your current processes through rapid iterations while addressing IT concerns like security, privacy, scalability, and integration. From modernizing legacy systems to improving the flow of data and information between people, processes, and systems, we empower your business users, and IT teams to streamline inefficient processes and free up valuable resources to complete more projects.

For more information, visit daylight.io

 

Articles

Top Use Cases for Banking Automation

Top Use Cases Banking Automation_Blanc Labs
Illustration by Storyset

Did you know that the World Bank uses Banking Automation including robotic process automation (RPA) for many of its functions? That’s how powerful it is. 

Modern businesses rely on automation to reduce costs and improve efficiency, but how can banks use automation? In this article, we explain the most common use cases of banking automation. 

What is Banking Automation? 

Banking automation involves handing over repetitive business processes in financial institutions like banks and credit unions to technologies like robotic process automation (RPA), artificial intelligence (AI), and machine learning (ML). 

Why Banks Need Intelligent Automation

As a banking professional, you know that a good chunk of your daily tasks is repetitive and mundane. Banking automation eliminates the need for manual work, freeing up your time for tasks that require critical thinking. 

Here are seven reasons why banks needs intelligent automation:

  1. Better Customer Experience
  2. Automated KYC
  3. Faster Mortgage Application Processing
  4. Accurate Report Generation
  5. Anti-Money Laundering Prevention
  6. Audits and Compliance
  7. Faster Decision Making

Below we dive deeper into banking automation use cases so you can get a closer look at how automation can transform your workflow.

1. Customer Experience 

A robust Customer Experience has never been more important. As the world moves online, you’ll need to re-engineer your Customer Experience to make it friction free, faster and more efficient. 

Consider a customer’s first experience with the customer onboarding process. If this isn’t a painless experience, you risk turning away a customer in the first interaction. 

Sure, you might need to invest some money to improve the customer experience and make it seamless and efficient, but the potential ROI is excellent. Think about it. Automation will eliminate much of the manual and low-value in-person interaction, saving your sales reps plenty of time to focus on running effective sales campaigns. 

Automating processes reduce the potential for errors, allowing you to onboard customers faster. Automation also reduces costs because it eliminates the manual labor and paperwork associated with customer onboarding. 

Moreover, your customers will be able to use their accounts faster, which improves customer experience. As a McKinsey report explains: 

“Automation and artificial intelligence, already an important part of consumer banking, will penetrate operations far more deeply in the coming years, delivering benefits not only for a bank’s cost structure, but for its customers.”

2. KYC

Most banks perform KYC (Know Your Customer) by manually verifying customer details. The problem? Manual verification can take plenty of hours. 

The KYC process doesn’t end at verification. You must manage KYC documents for a long time to comply with regulatory requirements. Using automation in banking operations can help free up the hours you spend on manual verification. 

Moreover, automation also eliminates the risk of human error. By eliminating room for error, automation ensures improved customer experience, increased quality assurance, and the number of cases processed each month, according to a McKinsey study.

3. Mortgage Application Processing

Mortgage application processing involves plenty of paperwork. Manually checking details on each document is time-consuming and leaves room for error. On the other hand, intelligent document processing (IDP) helps streamline document management. 

Remember those desks full of paperwork? That’s a thing of the past. Modern banks use IDP to manage documents digitally. IDP helps automate the generation of customer risk profiles and mortgage document processing, reducing processing time to a few days. 

An Accenture study found that 47% of customers prefer opening a new bank account online using a computer, while 37% prefer using the bank’s app or website. 

The shifting consumer preferences point to a future where loan requests and processing are online and automated. Now is a great time to prepare your bank for that future.

4. Report Generation

All financial institutions need to generate reports for various purposes. For example, you might need to generate a report to show quarterly performance or transaction reports for a major client. 

RPA can help generate reports automatically. The system can auto-fill details into a report and prepare an error-free report within seconds. An automated system can perform various other operations as well, such as extracting data from internal or external systems and fact-checking the reports.

5. Anti-Money Laundering (AML) Prevention

In Canada, banks need to ensure they are complying with the statutes of the Proceeds of Crime (Money Laundering) and Terrorist Financing Act, 2000. Depending on your location, compliance requirements might include ongoing risk-based assessment, customer due diligence, and educating staff and customers about AML laws. 

A single AML investigation can take 30 minutes or more when assigned to an employee. However, automation can complete the same investigation much faster and minimize errors. 

Using automation ensures you don’t spend too much money on AML investigations and stay compliant, so you don’t have to pay hefty fines.

6. Audits and Compliance

The cost of maintaining compliance can total up to $10,000 on average for large firms according to the Competitive Enterprise Institute. 

Maintaining compliance is expensive but less so than being non-compliant. For example, banks must ensure data accuracy when producing loan facility letters. However, instead of requiring employees to spend time meticulously verifying customer data, you can use intelligent document processing to save time and guarantee data accuracy. 

Banking automation can help you save a good amount of money you currently spend on maintaining compliance. With automation, you can create workflows that satisfy compliance requirements without much manual intervention. These workflows are designed to automatically create audit trails so you can track the effectiveness of automated workflows and have compliance data to show when needed. 

For example, you can set up a system to auto-freeze compromised accounts. Once the account is frozen, RPA can automatically complete the steps in your fraud investigation process. The system also creates an audit trail in the process. 

Unlike humans, RPA can be active 24/7. Using RPA in banking can help ensure the accuracy of compliance processes, ensuring you’re compliant at all times without investing a lot of human resources towards compliance.

7. Decision Making

Managers at financial institutions need to make decisions about marketing, operations, and sales, but relying on raw data or external research doesn’t provide full context. RPA can help compile and analyze internal data to track client spending patterns and preferences. 

AI and RPA-powered automation can help make decisions about timing marketing campaigns, redesigning workflows, and tailor-making products for your target audience. As a result, you improve the campaign’s effectiveness, process efficiency, and customer experience. 

For example, when introducing a mortgage loan product, you can use RPA’s data analysis capabilities to identify location-specific and borrower-specific risks. RPA can compile a summary of the risks on a document, allowing the credit manager to study risk profiles without the associated manual work. 

 

Blanc Labs’ Banking Automation Solutions 

Blanc Labs works with financial organizations like banks, credit unions, and Fintechs to automate their processes. 

We can create tailor-made automation software solutions based on your banks’ needs to minimize manual work and improve process efficiency. Our team can help you automate one or multiple parts of your workflow using technologies like RPA, AI, and ML. 

Book a discovery call with us to see first-hand how automation can transform your bank’s core operations. We’ll create an automation solution specifically for your organization that works in tandem with your current internal systems. 

Articles

The Transformative Power of Banking Automation

Automation for banks
Image credit: vectorjuice on Freepik

McKinsey expects machines to be responsible for up to 10% to 25% of a bank’s functions. The reasons? Banking automation minimizes the need for your team to work on repetitive tasks, allowing them to focus on high-profile and strategic aspects of the business. 

Automation also improves accuracy, which can save you a ton of money — a major reason why 80% of finance leaders have implemented or plan to implement Automation (including Robotic Process Automation). 

Curious about how banking automation can help? We explain everything you need to know about how automating your banking workflow can help reduce costs and improve efficiency. 

What is Banking Automation?

Banking automation involves using software powered by multiple technologies like AI (artificial intelligence) and ML (machine learning) to automate repetitive tasks. Automation has three primary benefits: 

  • Frees up your team’s time for more strategic tasks 
  • Improves process accuracy 
  • Improves the Customer Experience (CX) and the Employee Experience (EX) 

 

For example, you can automate your account opening process. A customer requests a new account via the chatbot on your website. The chatbot provides an application form. The applicant fills out the form, and it’s sent to your RPA robot. The robot performs the basic procedures, including checking the credit score and KYC verification. 

Next, the robot scans the applicant’s documents using OCR (optical character recognition) for data extraction. The robot matches the information in the documents and the application form. It flags any details that don’t match and sends them for manual approval. 

The robot continues to validate uploaded documents using NLP (natural language processing). It finds key data points in the document’s free text, categorizes them, and uses them in the automated process. 

The robot then updates the bank’s backend system to create a new business account, provided the customer’s data meets the bank policy. Once approved, the customer receives an automated welcome email. 

Why Banks Need Banking Automation 

Banks need automation to compete in the modern banking environment. Now, that’s a broad statement, so here are specific reasons why a modern bank needs automation: 

  • Allowing employees to focus on tasks that require a human touch: Most banks were set up long ago. Manual forms and workflows were a foundational pillar for legacy banks, and as a result, employees spend countless hours on things like data entry and account verification. Automation allows employees to “hand over” repetitive tasks to software, freeing up their time for high-profile tasks that require a human touch. 
  • Record management: RPA can generate and check expense records for compliance. It auto-logs all transactions and prepares the necessary financial records to get an overview of your business’s financial performance and position. 
  • Meeting customer expectations: The need for speed is a key driver of a modern customer’s experience. If you’re taking too long for basic operations like opening a bank account, you’ll lose customers fast. Automation can help speed up your processes and help deliver on your customer’s expectations. 
  • Faster customer support: Your customers hate waiting hours to get an answer. Automating your support using RPA helps you respond faster. You can answer customers’ questions at scale using a chatbot. Also, you can use an AI-powered chatbot to answer questions you haven’t added as an FAQ. 

 

These factors make automation more of a necessity than a nice-to-have — you need automation to compete neck-and-neck with other banks. 

How Banking Automation Can Transform Your Bank 

Transforming your bank’s value network with automation offers many benefits in various business aspects, including finance, legal, and customer experience. Here are the benefits of using RPA in banking: 

Banking Automation Leads to Efficiency 

You can improve productivity by up to 80%, especially if you identify the most impactful productivity levers. The efficiency improvement is a result of two factors: 

  • Low manual effort: Employees have more time available once they hand over repetitive tasks to software. They can do more in the same amount of time, helping you scale your operations. 
  • Improved accuracy: Errors are expensive because you spend time and resources on correcting the errors. Fewer errors = improved productivity. 

 

A great example of efficiency is automated document processing. As a banker, you probably spend a good number of hours reading documents and inserting relevant data into your systems, depending on your role at the bank. However, you don’t have to spend all those hours manually entering data if you use intelligent document processing. 

Better Customer Experience 

An average company takes over 12 hours to respond to customer service requests. That’s a recipe for dissatisfied customers, especially if you’re a financial institution. 

Your customers expect their money to be in the hands of a reliable entity, and guess what you communicate when you don’t answer customers for over 12 hours? 

Using RPA to automate your customer support helps minimize response times. In most cases, the chatbot can provide real-time answers to the most commonly asked questions. 

Speed is also critical for other client-side processes. For example, you want to be as fast as possible in opening accounts, processing personal investment requests, or enabling additional services for an account. Automating these processes (while ensuring accuracy) helps improve customer experience. 

Compliance and Risk Reporting 

According to Deloitte, the cost of compliance for retail and corporate banks has increased by over 60% since the pre-financial crisis spending levels. Non-compliance is even more expensive, but automation can help lower your spending on compliance. 

RPA builds compliance into your processes. Automating compliance ensures you’re always meeting regulatory requirements without requiring teams to spend extra time double-checking for compliance. 

Automation also creates an audit trail and automatically generates risk reports that give you added insights. The system can identify and flag suspicious activities so that you can investigate them. 

Reduced Costs

It’s easy to see how banking automation using RPA can reduce costs. Reduced administrative load, saving time on repetitive tasks, and speeding up processes all yield dividends. 

For example, Radius financial group reduced loan processing costs by 70% by using AI to automate their process. 

Banking automation also removes human error, so you’ll spend less on fixing those mistakes. 

Without automation, you’d need to invest a large amount of money in building more teams as you scale. However, automation empowers you to scale faster. You can continue investing in training current teams and save on costs you’d incur to accommodate a larger workforce. 

Automation and Adaptability 

Banking automation helps banks adapt faster to a client’s needs or the business environment. 

For example, the increasing popularity of Fintech is one of the most significant concerns for banks. Fintechs are quickly gaining market share at the expense of legacy banks. Customers appreciate how a fintech offers better, faster services. 

Fintechs aren’t the only factor banks need to consider, though. Your bank might want to integrate banking solutions with a new partner’s ecosystem to offer additional services like tax consulting. Or your bank needs to process offshore transactions faster, especially when the transaction is subject to jurisdictional restrictions on the amount of transfer allowed. 

Adaptability is critical for banks to succeed, and automation can make adapting to changes seamless. Implementing an automation solution will improve your adaptability to changes and allow you to quickly catch up with your modern competitors. 

The Bottom Line 

Over the past five decades, banking has gone from paper-based to almost entirely digital. Next up? Automation. 

Automation makes banking frictionless for both internal and external stakeholders — it’s a win-win. The only problem banks face with automation is the lack of a reliable partner who can guide them through the transformation journey. Book a discovery call with us, and we’ll answer all your banking automation questions. 

Articles

Transforming a Bank’s Value Network with Automation

By Abhijit Chakarvarty

Michael Porter’s value chain has been one of the top seminal business management ideas that saw business operations with through a new lens. Just like the value chain resulted in concepts like value creation and value pricing leading to phenomenal growth in global business scale and operations in the last 50 years, we are now seeing a similar scenario in the financial services industry with intelligent automation.  

At the turn of the century, we saw a new concept emerge that resulted in changing the business dynamics in the Y2K. This new business concept came to be known as value network, a series of interactions between individuals, entities, organizations, departments, and systems that collectively work towards benefitting the entire group or ecosystem. This new concept had an astounding impact on how businesses and markets operated and paved the course of today’s business ecosystem. For instance, the rise of Apple and its ecosystem can be attributed to this shift.  

A similar shift is also taking place in the financial services industry, where the digitization, embedment, and now decentralization of the payments ecosystem with the commercialization of blockchain, cryptocurrencies, procure to pay (P2P) lending are being touted as the next big thing. 

Given the pervasive technical and innovative initiatives that are emerging at breakneck speed, it is a necessity necessary to keep transforming and innovating. This is especially relevant for the financial services industry which have millennials as customers and will soon begin catering to GenZ.

To digitally transform a bank’s value network let’s start by stating the three core areas of a bank’s value network namely, network promotion & contract management, service provisioning & billing, and platform operations. 

With a two-sided value network, the bank fundamentally connects a borrower with a depositor and thus, becomes the enabler of value creation for such a network. In doing so, a bank delivers core banking and back-office operations, payments and lending functions, and risk and treasury management activities.  

For each of these areas, hundreds of functions and duties must be seamlessly executed with precision. Today, the increase in business volumes and scale of operations has led to bankers asking, “What if these complex and time-consuming operations can be boosted with robots (bots) assisting humans to accelerate speed, increase productivity, and assure the precision of key banking functions?”  

Automation Banking Benefits

Some of the key operational areas where bots can and, in many cases, are assisting humans to realize the true potential of an enterprise are customer service, compliance accounts payable, credit card processing, mortgage processing, fraud detection, know your customer (KYC) process, general ledger, report automation and account closure process. 

Automation Process heatmap

By embracing bots, banks can improve the customer experience while reducing costs and improving efficiency. Increased automation combined with more efficient processes makes the day-to-day easier for teams and individual contributors as they will spend less time on tedious manual work, and more time on profitable projects. Let humans contribute to high-value innovation, and robots help in maintaining and running operations to ensure an efficient and effective enterprise. To realize the true value of bots, and for a bank to embark on its digital transformation journey, the right approach, executive sponsor, business alignment, process discovery & design, pilot, roadmap, and a center of excellence (CoE) is essential to succeed. By using tactics such as data alignment, problem framing, road mapping, and piloting new robots, a bank will be well poised to reach its automation goals.

Blanc Labs has deep industry knowledge and proven experience working with leading banks to gain efficiencies through intelligent automation solutions. We take a holistic approach, helping financial services companies build the necessary foundation and setting them up for long-term success. 

Book a consultation with Blanc Labs to discover the impact of our Intelligent Automation solution. 

 

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