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Category: Technology

The Transformative Power of Banking Automation

Financial Services | Customer Experience | Enterprise Automation | IDP | RPA

The Transformative Power of Banking Automation

January 10, 2023
The Transformative Power of Banking Automation
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.

Top Use Cases of Intelligent Document Processing

Financial Services | Digital Transformation | Enterprise Automation | IDP | Lending Technology

Top Use Cases of Intelligent Document Processing

November 22, 2022
IDP

Currently, most enterprises have a workflow rampant with manual document-heavy processing.

However, businesses are quickly digitizing their document-processing workflows. 50% of B2B invoices across the globe will be processed without manual intervention according to a Gartner study. The reason? Manual document processing is more expensive than the cost of the documents themselves.

For example, the average cost of processing a single invoice was $10.89 in 2021. Manual document processing is also prone to human errors like fat finger errors. In a world where 90% of the data is unstructured, you need a tool that can automatically convert unstructured data into structured data to supercharge your productivity.

This guide explains how you can use intelligent document processing to save your business plenty of money, time, and resources.

What is Intelligent Document Processing?

Intelligent Document Processing (IDP) is a technology that automatically extracts unstructured data from multiple document sources, including images, online forms, and PDFs. IDP is also known as Cognitive Document Processing (CDP).

IDP converts this unstructured data into structured data using multiple technologies, including natural language processing (NLP), machine learning (ML), optical character recognition (OCR), and intelligent character recognition (ICR). Together, these technologies make IDP intelligent.

OCR is often used interchangeably with IDP. However, that’s not true. IDP uses OCR as one of the technologies to extract data.

How Does Intelligent Document Processing Work?

Here’s how a document is processed using IDP:

  • Conversion: An IDP platform starts by capturing your document through a scanning device. Once it converts a physical document into a digital one, it starts ingesting data.
  • Document image processing: The document’s image is processed for optimal OCR and archival.
  • Reading text using OCR: OCR helps the machine accurately read the scanned document’s text.
  • Identify language elements with NLP: IDP platforms use NLP to find language elements using methods like feature-based tagging and sentiment analysis.
  • Machine learning algorithm classifies information: A combination of machine learning and other techniques is used to classify the information in the document.
  • Extracting elements using AI: IDP uses AI to extract information elements like contact numbers, addresses, and names.
  • Validation: IDP platforms validate information using third-party databases and lexicons for data validation. Data points are flagged when the platform can’t validate them so someone from the team can review them manually.

Top Intelligent Data Processing Use Cases in Banking

Reading and writing financial documents make up a large portion of a bank’s workflow. As a bank, you need to process data fast to offer best-in-class services to your customers without making errors.

IDP helps banks guarantee accuracy and efficiency to their clients. In addition to data extraction’s key role in a bank’s workflow, banks can also use IDP platforms for fraud detection.

Here are some of the most common use cases of IDP for banks.

Mortgage Underwriting

Customer satisfaction with mortgage originators reduced by five points on a 1,000-point scale in 2021 according to a study by J.D. Power driven by record mortgage origination volume. Banks need to automate their mortgage workflow to scale as the demand grows. After all, customer satisfaction is one of the most significant differentiators in the mortgage industry.

The mortgage workflow involves collecting various documents. Extracting data from these documents is one of the major factors slowing down the workflow. This is where an IDP tool can help streamline your mortgage workflow.

An IDP tool helps you speed up the underwriting process with automation. It automatically reads and extracts relevant data and relays it to your bank’s credit evaluation system.

Claims Processing

The P&C Customer Satisfaction Survey reveals that the claim filing process is the biggest driver of customer satisfaction.

However, the claims processing workflow can be complex. Claims data comes in various formats—customers might send data as word files, PDFs, and images. Plus, you might receive the data via multiple channels—you might receive it via email, chat, or over a call.

Unifying this data without manual effort is a massive challenge. Traditionally, banks used OCR to process physical documents. However, the lack of accuracy required manual review.

An IDP tool is a great alternative to OCR for claims processing. Thanks to technologies like NLP, computer vision, and deep learning, it provides greater accuracy than traditional OCR.

Customer Onboarding

Customer onboarding is one of the most resource-intensive processes for a bank. Banks spend an average of $280 to onboard a single client according to Backbase—the cost can add up when you’re onboarding hundreds or thousands of customers every month.

Many of these expenses go towards processing documents, including the bank’s forms, credit reports, or tax returns. Sure, you can try automating this workflow. However, the automation will break down as soon as a new document type is introduced or you change your form’s template.

An IDP tool can help tame your customer onboarding costs. Your customers will appreciate a fast onboarding experience, and you’ll save money, increase productivity, and make an excellent first impression.

Financial Document Analysis

Banks handle thousands of financial documents every day. From financial statements to tax returns, carefully studying financial documents is critical to a bank’s operations.

Financial analysis is a cognitively heavy task. Why make your team spend time on mundane tasks like manipulating data when you can use an IDP tool to automate this process and enable your team to concentrate on their more complex deliverables.

Using an IDP tool helps analysts automatically structure and populate relevant financial data into their system. You’ll do your analyst team a favor by eliminating a lot of their manual work, allowing them to focus on analysis.

KYC Process Automation

KYC (Know Your Customer), Re-KYC, and C-KYC are critical for compliance. Banks might need to refer to a customer’s KYC details at various stages during a customer’s journey.

However, handling hand-written KYC forms is a hassle. Migrating a customer’s KYC data comes with challenges like human error and work overload. Committing errors when underwriting a mortgage or onboarding a customer costs money, but failing to comply with KYC requirements may increase the legal, compliance and regulatory risks.

Using IDP ensures accuracy, so you never have to lose your reputation and pay a fine for failing to comply with KYC norms.  The McKinsey KYC Benchmark Survey found that by increasing end-to-end KYC-process automation by 20%, an organization could enjoy the following positive outcomes:

  • Increased quality assurance by 13%
  • Improved customer experience (by reducing customer outreach frequency) by 18%
  • Increased the number of cases processed per month by 48%

The Bottom Line

Banks process a colossal amountnumber of documents and data each day. Getting new customer data into the system, processing claims, and analyzing financial statements are heavily data-driven tasks that involve dozens of documents from hundreds of customers.

The probability of committing errors is high. Banks also need a large team just to process documents and structure the data in those documents.

Banks need an IDP tool to automate this process and remove the risk of error from the process. It also integrates with applications to make migrating the data easier. An IDP tool also validates data and alerts team members in exception cases, when it requires a human to review accuracy.

It is important to select an IDP tool that offers the right solutions for your industry. Better yet, find a partner who can create a custom IDP solution tailor-made for you.

Why Choose Blanc Labs Intelligent Document Processing?

Blanc Labs partners with financial organizations like banks, credit unions, and fintechs to automate operations.

We can help you create robust automation solutions that minimize manual effort, reduce errors, and improve productivity. Our team helps you use the most advanced technologies including AI and ML to automate complex, resource-heavy processes like document processing.

Book a discovery call with us if your financial organization deals with plenty of documents daily. We’ll come up with a tailor-made solution to minimize the friction in your document processing workflow.

Finding the right API Management Platform

Financial Services | API Management | Digital Banking | IT Management

Finding the right API Management Platform

November 3, 2022
API management

APIs are an integral part of today’s digital world. They are used for secure data exchange, integration, and content syndication. As APIs become more ubiquitous in enterprise businesses, it becomes necessary to manage them efficiently.

Banking and Payments ecosystems are converging with Open Banking and Finance. Whether regulatory or market driven, these digital interactions are happening already – and growing exponentially. Doing APIs and API Management right are central to the growing interdependence and interoperability between Fintechs, Banks and Consumers. Stakeholders are demanding secure access to financial data to drive better customer experiences. A key enabler to that end are the systems that surround APIs.

What is API Lifecycle Management?

API Lifecycle Management is the process of building, controlling, distributing, analyzing, and reusing APIs. It also can include capabilities around intelligent discovery; one pane of glass visible across multiple API gateways and API management systems; bringing to life the visionary end state of monetizing and marketing all these capabilities to external parties to operationalize the concept of “API as a product”. Thus, there are many API Management solutions in the market offering a variety of features. But at the very minimum, an API Manager should allow users to do the following:

Discover APIs

Before you can more effectively govern their lifecycle, you need a simple and configurable tool to find, filter and tag all your API assets into a centralized repository. Simplify complexity and/or get better visibility and facts to position your organization to “open itself up” to the new business realities and opportunities emerging.

Design, build, and Test APIs

The API Management tool should provide everyone, from developers to partners, the ability to create APIs under a unified catalog and test their performance.

Deploy APIs

API Management tools should also allow you to publish APIs on-premises, on the cloud or in a hybrid environment. Additionally, the API Manager may give you a choice between managing the API infrastructure in the tool itself or on your own.

Secure APIs

By providing a central point of control, most API Management tools will ensure that you have full visibility of all your APIs across environments so you can mitigate any vulnerabilities.

Manage APIs

API Management tools should give you a central plane of visibility into APIs, events, and microservices. Most API management tools will allow you to govern APIs across all environments (on-premise, hybrid, cloud) and also allow you to integrate with other infrastructures, including AWS, Azure, and Mulesoft. A good API management tool should also provide multiple predefined policy filters to accelerate policy configuration.

Analyze APIs

An API Manager should give you real time metrics in a unified catalog. By providing data on the business performance or operations across your APIs, you can make better decisions leading to improved business results.

Extend and Reuse APIs

By giving you a single, unified catalog, an API Manager can eliminate duplication and extend the life of APIs through reuse.

The need for API Management

API management centralizes control of your API program—including analytics, access control, monetization, and developer workflows. It provides dependability, flexibility (to adapt to shifting needs), quality, and speed. To achieve these goals, an API Manager should, at the minimum, offer rate limits, access control, and usage policies.

Essential features of an API Manager tool

1. API Gateways

A gateway is the single entry point for all clients and is the most critical aspect of API management. An API gateway handles all the data routing requests and protocol translations between third-party providers (TPP) and the client. Gateways are equally important when securing API connections by deploying authentication and enforcement protocols.

2. Developer Portal

The primary use of the developer portal is to provide a hub, specifically for developers, to access and share API documentation. It is an essential part of streamlining communications between teams. Typically, developer portals are built on content management systems (CMS), allowing developers to explore, read, and test APIs. Other features of a developer portal could include chat forums for the internal and external developer community and FAQs.

3. API Lifecycle Management

As the name suggests, API Lifecycle Management provides an end-to-end view of how to manage APIs. API Lifecycle Management is a means to create a secure ecosystem for building, deploying, testing and monetizing and marketing APIs.

4. Analytics engine

The analytics engine identifies usage patterns, analyzes historical data, and creates tests for API performance to detect integration issues and assist in troubleshooting. The information gathered by the analytics engine can be used by business owners and technology teams to optimize their API offerings and improve them over time.

5. API monetization and marketing

API management tools can provide a framework for pricing and packaging APIs for partners and developers. Monetizing APIs involves generating revenue and keeping the API operational for consumers. Through usage contracts, you can monetize the microservices behind APIs. An API management tool will offer templatized usage contracts based on predefined metrics, including the number of API calls. This empowers innovative external players to help drive your business in ways you have not dreamed up yet – and still do it securely.

How successful is your API management?

Now that we know the features of an ideal API management software, how do you evaluate its success for your API efforts? Here are a few ways to track your progress:

Speed
How rapidly can you launch your APIs to meet your business goals? Latency and throughput are ways to measure the speed of deployment. Other areas to measure speed would be onboarding and upgrading APIs.

Flexibility
Flexibility is the breadth of options available to developers when adopting APIs. The greater the flexibility, the higher the cost and effort to manage the API.

Dependability
How available your APIs are to developers. One way to measure dependability is downtime. Quota is another way to restrict how many API calls can be made by a developer within a certain timeframe. Enforcing quotas makes API management more predictable and protects the API from abuse.

Quality
Stable APIs with consistent performance reflect higher quality. It is a way to measure a developer’s satisfaction with the API.

Cost
The above four factors contribute to cost. If your API management software provides a better view of all your APIs, it will reduce duplication and costs. Reuse of APIs is another way that you can save costs.

How are you managing API complexity?

If you are a business leader concerned about how to meet market demand through the creation and deployment of APIs, or you would like to monetize and reuse your existing APIs and reduce costs, then you need structured API management.

In partnership with Axway, Blanc Labs offers a way to manage your APIs to bring maximum business value. Axway’s API Management Platform enables enterprises to manage and govern their APIs for developing and applying their digital services.

Book a discovery call with Blanc Labs to learn more. 

Developing the next generation of talent at Blanc Labs’ Digital Academy

Partners | Leadership | STEM | Talent

Developing the next generation of talent at Blanc Labs’ Digital Academy

October 19, 2022
Digital Academy

In August of this year, we launched the Digital Academy at Blanc Labs, where 100 students in Colombia had the opportunity to learn from our experts on topics that we consider key to our business.

The students that joined the program as Associates, gained knowledge of fundamental concepts of agile methodologies, cloud computing, full-stack development, and RPA (Robotics Process Automation).

The Digital Academy community recently shared their top takeaways from this experience.

Promoting a culture of learning at Blanc Labs

“Walking alone through the world of technology is not easy. I am sure many of us have encountered some barriers, such as not understanding what we hear in a video tutorial, or you end up having lots of questions. When we are reading the technical documentation, it may become even more complex. These situations make me appreciate my technology education teachers and the people who share their knowledge with me,” says Gustavo Camargo, a Software Engineering Associate, who is committed to achieving his dream of working in the IT industry.

Martin Bec, who shared his experience as a Full-stack Developer in our latest bootcamp, says: “Teaching and sharing  knowledge is part of my lifelong learning way of living. I encourage others to clear up their doubts and I appreciate the opportunity to learn. My own learning approach significantly affects how I lead others to strengthen their career in IT.”

Working in technology requires a combination of technical skills and soft skills

By being exposed to various virtual collaboration opportunities, students work on their communication, relationship-building, teamwork, and cultural awareness skills. One of their main challenges is to overcome the language barrier, identifying how to strengthen their learning in a second language in their spare time and the IT top skills they require for a booming professional career.

“With agile methodologies, I learned that good planning is key, and I apply that thinking to my personal life. Fulfilling projects requires perseverance, coherence, and the team’s motivation to continue. There may be changes along the way, but the agile methodology is flexible with this, and you learn how to prioritize your work and focus on progress”, says Jennyfer Belalcazar, Systems Engineering Student.

According to a Gartner study published in March 2022, an agile developer must master methods, techniques, behaviors, and various fundamental aspects of Engineering.

  • Methods such as Scrum and Kanban, implementing Agile pilots, pivoting, and adjusting the strategy, and evaluating risks and results for the business, are highly valued
  • Understanding metrics, and User Stories are essential to promote feedback with stakeholders and gain in-depth knowledge to overcome project challenges
  • Customer focus, continuous learning, and collaboration significantly impact interactions and work styles
  • The adoption of best practices, and the importance of test-first thinking, are fundamental for execution. The incorporation of agile architecture and the training of Database Administrators with a set of multidisciplinary skills impacts Agile teams’ performance

As complementary activities to their learning experience, Associates have created sessions to strengthen their conversational skills in English and they engage in activities to improve their personal brand and prepare for job interviews.

As Associates evolve in their learning experience, they gain the most valued skills in this industry. Most students combine their Digital Academy experience with technical education, short courses, and other IT programs, particularly in development, programming, and Data Science.

Building a culture of learning, fostering technology education, and empowering our team is fundamental to the success of our projects.Discover how Blanc Labs can bring an agile and strategic approach to your digital transformation project. Get in touch. 

Blanc Labs CEO Hamid Akbari Speaks On What It Takes To Scale Up Successfully

Technology | Digital Transformation | Leadership | Podcast

Blanc Labs CEO Hamid Akbari Speaks On What It Takes To Scale Up Successfully

October 7, 2022

You don’t have to be a #Fortune500 company to start thinking strategically about the future of your business. Technology services firms that commit to strategic methods and sustainable growth mechanisms early on can experience exponential profitability.

The way forward is not always clear, but technology services firms can take it one step at a time. Hiring great people, adapting technological breakthroughs, and staying connected with the needs of their customers all contribute to success.

In this podcast hosted by Collective 54, our CEO, Hamid Akbari, talks about what it takes to scale up a company in today’s competitive landscape.

Three Reasons Financial Institutions Are Losing Out to FinTechs

Financial Services | Digital Banking | Digital Transformation | Open Banking | Technology Architecture

Three Reasons Financial Institutions Are Losing Out to FinTechs

June 16, 2022
Fintech

…And How to Keep Up with Digital Natives 

by Bob Paajanen and Charles Payne

The way we bank has changed forever. While FinTechs have the latest technology innovations, what they don’t have is decades-worth of relationships with customers and large swaths of Big Data. Financial institutions need to recognize this advantage, leverage their data, streamline processes, and thereby empower their relationship managers if they want to compete with their new-age rivals.

Mismanagement of Data

Most financial institutions have multiple customer-facing systems that operate in their own silos. As many as 50% of banks and credit unions state that they have trouble accessing their internal data. Without a single unified view of their customer, banks and credit unions are unable to collect, process, or indeed deploy insights that will enable them to cross-sell products and services to their customers.

The services gap left by financial institutions is especially felt in commercial banking where FinTechs are sweeping up SMBs with targeted products and quicker access to funds. A prominent example of this trend is Shopify, which started out as an e-commerce platform, but is now the tenth-largest provider of financial services to SMBs. Another example is Stripe, which has created an end-to-end lending API (application program interface) as its next offer to SMBs.

Paper-heavy processes, and disparate data management systems are some of the major causes of this issue. As the finance industry moves toward open banking, it is imperative that financial institutions unlock the value of their data and translate it into actionable insights so they can improve their languishing businesses.

why financial institutions are losing out to fintechs
Source: 11:FS ‘Fintech filling services gaps’ Designing digital financial services that work for US SMBs 

Lack of Efficiency

A 2019 Gartner report estimated that process automation, including document processing, could save financial institutions 25,000 hours of avoidable work per year. With advances in technology in the last three years, it is not hard to imagine that this number may have gone up even further.

Most of the productivity loss mentioned above has been attributed to human error. This is hardly surprising when many financial institutions continue to use paper-heavy loan origination models. Without automation, document processing is rife with efficiency and security issues including document mishandling, collaboration on email (generating multiple copies of the same document), versioning issues, loss of time to find the documents when required, a lack of compliance, and a lack of remote access.

Since the pandemic, consumer expectations have changed dramatically. Close to 60% of customers today are open to completing their mortgage applications entirely online without support on the phone or in person. Even more pressing than the platform, is the need for speed, with customer satisfaction falling 15 percentage points for approvals that take longer than 10 days.

With unprecedented demand for mortgages, financial institutions must speed up intake, underwriting and decisioning processes faster if they want to keep the customer’s business.

Costs

Inefficient loan origination processes lead to rising costs. On average, loan origination costs $7-9k per application. That is over and above the cost of productivity loss, estimated to be $878,000 (for 25,000 hours lost per year) for a company with a 40-person finance team. This cost is invariably passed on to the customer who may end up paying higher fees and charges compared to what they might pay if they opted for a non-banking entity.

rising cost of loan origination

The FinTechs Are Coming… And how to slow them down

As a result of service gaps and inefficiencies, customers from both commercial and retail banking have been veering towards nonbanking entities for loans. 50% of Canadian SMBs in 2021 felt that they couldn’t maintain their growth strategies “due to a lack of capital.” Today, nonbanking entities, account for more than 70% of total originations. By using automated processes and digital interfaces, non-banking entities or FinTechs are 25% cheaper than the industry average and can deliver a decision 30% faster compared to other financial entities.

In the age of Open Banking, it is important that financial institutions update their legacy processes and unlock the potential of their data if they want to survive.

The automation journey begins with intelligent document processing. Blanc Labs provides a 360-degree IDP (Intelligent Document Processing) solution that can:

  • Automate workflows for document collection, digitization, and analysis
  • Replace manual effort through intelligent data capture
  • Connect with third party data providers for analysis and insights
  • Analyze document data, provide status alerts, and flag fraudulent entries
  • Secure documents in a drop box
  • Deploy on-premises, in the cloud, or as a hybrid model

Book a demo or discovery session with Blanc Labs to learn about the impact of our IDP solutions for banking. 

Extraction: The Next Step in Intelligent Document Processing  

Partners | AI | Banking Automation | IDP | ML

Extraction: The Next Step in Intelligent Document Processing  

May 31, 2022
Next Steps in IDP

By Luciano Lera Bossi, Alejandro Nava and Parsa Morsal

One of the starting points of digital transformation, especially for financial institutions, is intelligent document processing or IDP. We previously explored classification as the first step in IDP. In this article, we will explore the next crucial step, extraction.

What is document extraction?

Document data extraction is a process of extracting data from structured or unstructured documents and converting them into usable data. It is also called intelligent data capture. With the rapid progress in document imaging technology such as the incorporation of natural language processing (NLP) and optical character recognition (OCR) as well as advanced analytics, we can now enable IT systems to understand the data that was thus far only on paper.

Powered by machine learning models and NLP, IDP systems can now bring the benefits of AI to document processing. The intelligence and detail offered by IDP systems today can be used for many functions including compliance and fraud. The level of granularity, accuracy, and speed offered by IDP systems today, can hugely impact the scale of digital transformation for your organization.

Document processing and the banking industry

The financial industry is no stranger to the benefits of IDP. In a recent study of 200 banks in the US, it was found that 66% of the respondents eliminated the need for manual processes for a typically labor-intensive industry thanks to IDP; and 87% cited accuracy and extraction as the key reasons for incorporating IDP into their systems. Given the emphasis on accuracy and extraction, it is important to understand how intelligent document processing coupled with OCR and NLP can give desired results.

OCR vs IDP

OCR as a document processing technology has been around the longest. OCR is used to extract handwritten or typed text in documents which can then be converted into data. While OCR has been synonymous with data extraction for many years, it is not without its challenges. Without intelligent processing of the data in understanding what the data is for, OCR may give inaccurate results. There can be errors in detecting a text block in an image (error in word detection), there may be errors in interpreting words correctly if there are differences in text alignment or spacing (error in word segmentation) or there may be errors in identifying a character bound in a character image (error in character recognition).

However, when combined with intelligent processes such as NLP and machine learning analytics, time-intensive processing tasks can be sped up with minimal errors. The biggest differentiator between OCR and IDP is that IDP can also handle documents that may be structured, semi-structured, or unstructured.

Structured Documents

Structured documents generally focus on collecting information in a precise format, guiding the person who is filling them with precise areas where each piece of data needs to be entered.  These come in a fixed form and are generally called forms. Examples of structured documents include tax forms and credit reports.

Semi-structured Documents

Semi-structured documents are documents that do not follow a strict format the way structured forms do and are not bound to specified data fields.  These don’t have a fixed form but follow a common enough format.  They may contain paragraphs as well. Example of semi-structured documents could be employment contracts or gift letters.

Unstructured Documents

Unstructured documents are documents in which the information isn’t organized according to a clear, structured model. These files are all easily comprehensible by human beings, yet much more difficult for a robot. Examples of unstructured documents include mortgage commitment statements and municipal tax forms.

Textual and Visual data extraction in IDP

The two main aspects that efficient IDP solutions tackle are textual data extraction and visual data extraction. In textual data extraction, the entity extraction technique is applied to recognize text in a document. This is a machine learning approach where the software is exposed to thousands of documents and the machine “learns” to identify information and segregate it based on certain semantic parameters. Entity extraction can involve a variety of tools and techniques including neural networks to visual layout understanding. By using entity extraction methods, you can avoid going down the template route and thereby use the software on various kinds of documents.

In visual data extraction, IDP solutions can be designed to understand elements such as signatures, tables, checkboxes, logos, etc. Visual data extraction is more complex than textual data extraction as it involves detecting, analyzing, and extracting information from the regions with visual elements accurately while also denoising content that is not relevant. Using machine learning, advanced visual extraction models can also understand the structural relationship of the visual data and its relevance.

Choosing the right IDP solution that can handle both text and visual elements accurately across varying document types will ensure that there is no need for your back office to comb through documents once again.

Explore Kapti, our intelligent document processing software to find out how the power of machine learning and automated document workflows can transform your organization’s document processing experience.

4 Ways to Avoid A Failed Automation Journey 

Financial Services | Banking Automation | Enterprise Automation | IDP

4 Ways to Avoid A Failed Automation Journey 

May 25, 2022
4 Ways to Avoid A Failed Automation Journey

by Saurabh Bhatia

In recent years there has been a growing desire among financial institutions to automate processes as they move upstream to meet customer requirements. Before important decisions like loans and underwriting decisions are even made, financial institutions are deploying automation at the start of the process to provide a seamless digital-first experience.

Research shows that automation is one of the fastest and most efficient ways for financial institutions to acquire, enhance and deliver information, reduce costs and save manual labor. Then why is it that most automation initiatives fail?

4 Ways to Avoid A Failed Automation Journey

A survey by EY states that 30-50% of initial RPA projects failed to realize their expected returns. The diagnosis suggests some challenges the enterprises typically face in their automation journey which potentially cause the RPA failure. Here we explore 4 ways in which enterprises can avoid automation journey failures:

1. Give importance to change management and training 

2. Create automation champions within the organization

3. Use the right tools to understand what needs to be automated 

4. Keep employee experience at the core of the automation vision 

Let’s dive in!

 

Give importance to change management and training

Automation cannot be successful without proper implementation of change management. Even if automation is a technical matter, it relies heavily on human relations. Intelligent Process Automation (IPA) is different than your typical IT project such as ERP/CRM etc.

These projects require engagement from business users because, in essence, the role of the very same individual will evolve with the adoption of automation. Organizations that have been successful in their automation journey have put a real emphasis on the training and mobility of their teams when implementing automated processes. One of the most common examples of this is the changes in the target user interface. Any changes to the UI interface of an RPA application or system will most likely halt the automation which can put projects in a critical condition. Therefore, some organizations ask their automation core team to regularly check for changes in the ecosystem of the dependencies (in this case the UI interface) to avoid any failures.

Create automation champions within the organization 

Automation is here to stay and is evolving rapidly. However, many organizations still see their automation initiatives as a project and not as a journey. Automation today has moved away from being just a technology project and is more about data transparency and technology capability. Most organizations don’t approach automation with the rigor it requires, assuming the business workforce need only attend a few training courses and that they can, without the support of IT, generate enough extensive automation to scale a program.

IT is a critical partner throughout the transformation process. Their role is to ensure that the system is scalable, reliable, secure, and performs well. To make automation scalable, organizations should have a core team who are experts in the automation space. Successful organizations use such a core team to articulate the business value of automation well and get buy-in from key stakeholders within their organization. The core team articulates the need, advantages, and roll-out plan to each stakeholder before moving ahead with automation.

Behaviours Driving Intelligent Automation Success & Failure

 

Use the right tools to understand what needs to be automated

Not all business processes are considered fit for automation. Choosing the wrong pilot process without understanding the needs can become one of the major reasons for failed automation initiatives. The success of any automation program strongly depends on a deep understanding of how processes will get handled on-ground.

Organizations are moving towards discovery tools such as process mining, task mining, and task capture which identify automation and improvement potential in end-to-end business processes and unleash the true value of automation.

You can use “The Three Rs of Automation Discovery”, to guide your approach towards successful discovery and automation implementation.

Keep employee experience at the core of the automation vision

In recent years we have realized that automation is not about replacing human beings but helping them be more efficient and using them for strategic work rather than manual. Automation projects require even more engagement from these individuals (users) to ensure the stability of the automation program.

It is important that organizations have full management support to communicate and reassure their teams that automation is more about reducing boring/repetitive tasks so that they can focus on more interesting and fulfilling work. Think about a contact center agent in a bank who struggles daily with clients because they had to go through 15 or 16 applications to do simple resolutions. They will be better off with an easier interface where they can focus more on the clients rather than swivel chair operations.  Automation can help these contact centers to reshape the experience not only of the customer but also of the team members, which will also lead to better talent retention rate.

The Bottomline

There is no question that Intelligent automation has demonstrated exceptional results, from predicting behavior to streamlining operations. But its implementation needs to be thoughtful, effective, and pragmatic to ensure its long-term success. There are other factors that can cause a project to fail including the lack of testing and not following the best development practices. However, these 4 reasons are primary and should be taken into consideration before starting your automation journey.

Blanc Labs has proven experience working with organizations to identify and implement intelligent automation solutions. We take a holistic approach, helping organizations build the necessary foundation and setting them up for long-term success in a hyper-automation environment.

 

Book a demo or discovery session with Blanc Labs to discover the impact of our Intelligent Automation solution.

The Three Rs of Automation Discovery

Technology | Banking Automation | Digital Transformation | Enterprise Automation

The Three Rs of Automation Discovery

April 29, 2022
Automation Discovery

By Saurabh Bhatia

Before you begin the process of automation at your company, you need to check for the Three Rs of Automation Discovery which will ensure the long-term success of automation implementation. In this article, we will look at:

Automation Discovery’s 1st R: Reimagine the vision

Automation Discovery’s 2nd R: Return on investment calculation

Automation Discovery’s 3rd R: Reusing Automation

Why are The Three Rs of Automation Discovery so important?

 

So you’ve decided that you want in on the automation game. Great! Now you’re in the all-encompassing process of discovery and implementation. This is where you, the organization that is looking to adopt automation, needs to articulate your business needs, asses how automation will impact your operations, and then determine a successful implementation roadmap with your tech partner. Here are three components, “The Three Rs”, that should guide your approach towards a successful discovery and automation implementation.

Automation Discovery’s 1st R: Reimagine the Vision

Begin by reinventing the way you look at your operations and its processes. It goes without saying that you should start with standard process automation first to demonstrate its value. But during the discovery phase, explore all tools that will compound the value of automation for your organization. For example, if you are looking to automate the mortgage lending process, take a step back and examine the added benefit your organization will get from adding power BI dashboards or analytics systems that provide more actionable insights or discovery tools which identify which other processes and tasks could be automated.

Keep in mind a vision of an organization fueled by hyperautomation as you explore various options in addition to standard process automation namely, intelligent document processing, business intelligence reporting, process mining, chatbots, etc. There is a full stack of options you can explore to heighten the benefits of technology and establish that future state of hyperautomation.

Automation Discovery’s 2nd R: Return on Investment Calculation

Understandably the most common driver in decision making is about the returns you will see with the option of automation (or any other technology solution). Determine how you will calculate ROI prior to beginning work on the solution. We recommend creating a business case with a very clear prioritization matrix and roadmap of automation and its benefits. This will determine the focus both long term and short term.

Pro Tips:

  • Determine which licenses and automation tools are most useful and cost effective for the overall solution
  • Adopt licenses and tools and build your infrastructure to support the scalability of automation (and sunset those that are no longer in use)
  • Don’t forget, to consider monetary metrics which deeply impact the business in your calculations

Automation Discovery’s 3rd R: Reusing Automation

Some organizations feel like they’re starting from scratch every time they introduce a bot to their processes. In reality, you reutilize some parts of your previous assets (from one bot to another) to make automation faster. For example, if you have multiple processes, teams and departments using the same application or program, we encourage you to create reusable assets with the first bot so when you introduce a second bot, you are reutilizing the same assets with the same application or program. This fuels enterprise scale adoption as a team or functional area and can demonstrate the value of automation to other departments, which will encourage further adoption of the technology.

Pro Tips:

  • Divide your projects into components and create reusable libraries, which makes it easier to reuse automation for further processes
  • When designing the bots, focus on smaller components within them but always keep in mind how this will affect future projects in a positive way

Why are The Three Rs of Automation Discovery so important?

  1. By reimaging your vision, you create a collective, growth oriented and collaborative mindset within the organization as it pertains to digital transformation
  2. The right ROI calculations help you determine which processes will garner better returns both short term and long term
  3. Reusing automations also makes your implementation scalable with faster adoption across teams and departments

Automation is transforming the way we run businesses, transact, and engage in the world. The key to achieving our vision and maximizing the possibilities of technology in our organizations is rooted in having the right approach. And the three Rs in automation is great place to start.

Find out more about enterprise automation, book a meeting with us today to see how we can accelerate your digital transformation journey.

Mastering Quality Assurance

People & Culture | Leadership | Software Development

Mastering Quality Assurance

March 22, 2022
Quality Assurance

I grew up in a small town in the Southern part of India, called Udupi. Today, Udupi is a thriving metropolis known for its trademark cuisine, educational institutions and historical sites. When I was growing up, it still had the charm of a small town and provided the perfect environment for my childhood.

The focus at our home was heavily on academics. My father would tell me to study, get a degree and then chase my goals. I realized very early on that I wanted to be an engineer one day. The action of putting together various elements to create a complete entity was fascinating to me.

My introduction to Quality Assurance

After graduating with a degree in computer science engineering at PES University, an institution on the forefront of technology education and research, I worked as a Quality Assurance (QA) Specialist for a company in India. The role of a QA specialist is to ensure that the product, at every stage of its development and presentation to the client complies with the company’s quality standards. I found myself adept at finding as many issues in the product as possible and it gave me tremendous satisfaction in knowing that my review helped my team succeed in delivering the best viable product to the client.

After four years of being a QA Specialist in India, I made the bold and exciting move of immigrating to Canada. This transition was not entirely seamless. Navigating the job market was challenging for a new entrant such as myself – the cultural nuances through the interview process in itself was a factor. But in November 2019, I found Blanc Labs and joined the team. I was drawn to the sector and the tech mindset, which was very forward thinking. I had never been in such an agile company going through a rapid scale up before. The entrepreneurial culture imparted a growth mindset in me, and I was excited to explore that, and the ability to create more impact on the overall performance of the company.

Exciting new challenges

Taking a deeper dive into my responsibilities as QA Specialist, I had to check the application (built by the developers) against the client’s requirements (provided to me by the business analyst), ensuring there are no gaps/issues with functionality built. Though this seems straight forward, at the time, the developer to QA ratio was 10:1 (a more normalized number being 3:1). In addition, I had to learn the commercial lending process and delivery quality very quickly.

Always the eager student, I took it upon myself to learn as much as I could about the requirements, the stories, the questions, and the testing at very sprint. I am proud to say we saw no delays on any projects or deliveries.

The other challenge that I faced was my perception of the client. I’d always been taught to see the client as an entity that is superior to the company I represented. Their word was law and their needs and wants superseded my opinions. At Blanc Labs, we are completely collaborative with our clients in every project. My manager and mentor taught me that hierarchy should never get in the way of project delivery and success. Our clients are open and receptive to our insights and with that, I have been able to partner with them more effectively.

What does it take to succeed?

Today, I am proud to share I have grown to lead a team of QA Specialists. When I think about what it takes to be effective at what I do, it boils down to these things:

  • Become an eternal student: You have to understand the goal and recognize the outcome. You have to know the application in and which helps the process easier.
  • Stay focused: The quality of an application depends on you and so you need to be attentive to find every issue/ gap and ensure that the product is functioning and delivering in the way the client requires.
  • Agile delivery: With agile, QA is brought in early in the process to uncover any gaps, adding more focus to more effective delivery.
  • Demonstrate leadership: Irrespective of whether I was an individual contributor, or now, where I lead a team of QA specialists, I always take a leadership approach by establishing a foundation of standard practices across all projects, and encouraging those around me to learn and adapt to new tools, for example, to focus more on automation testing, which helps to improve test coverage.

 

I feel at home at Blanc Labs. Here, I am encouraged to learn, grow, and pursue new levels of excellence every day. Leadership has been instrumental as they have nurtured me to rise to new heights and for that, I am grateful. When I think about the success in my career, I go back to the three values that I admired in my father: dedication, responsibility, and focus. I realize that life has come full circle and I carry on the legacy of his work in everything I do and every frontier I choose to explore.

To learn more about the values with which we are growing our team, please explore our mission and vision.