Skip to Main Content
Services
Innovation & Design
Technology Strategy and Implementation
Systems Integration 
API Management
AI, Analytics & Automation
Business Process Improvement
Enterprise Automation
Intelligent Document Processing
Low Code/No Code Development
Generative AI
Industries
Financial Services
Digital Banking
Core Banking
Composable Banking
Consumer-Driven Banking & Open Finance
Lending
Commercial Lending
Residential Lending
Payments
FinTech
Banking As a Service
Healthcare
Data Interoperability
Careers
Back
Work with us
Financial Services
Healthcare
Company News
Innovation & Design
Systems Integration 
API Management
Business Process Improvement
Enterprise Automation
Intelligent Document Processing
Low Code/No Code Development
Generative AI
Digital Banking
Core Banking
Composable Banking
Consumer-Driven Banking & Open Finance
Lending
Commercial Lending
Residential Lending
Payments
FinTech
Banking As a Service
Data Interoperability
Who We Are
Partners
Careers
Work with us
Category: Banking Automation

Why Banks Need Intelligent Document Processing

Financial Services | Banking Automation | Digital Transformation | Enterprise Automation | IDP

Why Banks Need Intelligent Document Processing

June 2, 2022
IDP for Banks

By Charles Payne and Donald Geerts

In the last two years, we have witnessed a consumer engagement revolution. The pandemic has seen a rush toward digital channels in all facets of life, including the banking industry. The need for instant gratification and round-the-clock support means that lenders must process customer or broker requests faster while balancing security, compliance, and risk management. Data released by the Canada Mortgage and Housing Corporation (CMHC) suggests that in the first half of 2021, the mortgage industry in Canada saw its fastest growth in the last 10 years. Given the rising demand of the market, the “need for speed” in the loan origination and decisioning process is at the top of the list.

Staying ahead of the competition requires a digital transformation that often begins with intelligent document processing as the first step. Financial institutions must partner with the right intelligent document processing (IDP) solution provider that will deliver both speed and accuracy to meet consumer expectations.

why banks need intelligent document processing

Tedious and time-consuming processes

The process of mortgage approval or renewal involves many, many documents. Before a mortgage is even approved, a mobile mortgage lender must collect and organize documents (sometimes handwritten), send them to various personnel in the financial organization to be vetted, and finally return to the customer with a yes or no—a process that can take up days or weeks. If a bank takes too long to respond to a borrower, they may turn to offers from other lenders. Such a situation is easily avoided with the help of intelligent document processing. Once a document is received, the right IDP program can classify it, extract data from the document, and store the data in a way that is accessible around the clock, not just to employees of the lender but to RPA (robotic process automation) processes as well. If additional documents are required, the RPA process can notify the mortgage agent or borrower. If the application is complete, then the RPA can send the data ahead for auto-decisioning. Using IDP in combination with RPA can ensure a quick turnaround on an application without consuming too much time.

Organizations with no digital document processing reported 10x more at-risk customers and 2x more at-risk revenue compared to other companies. (Forrester, 2020)

Inability to scale

One way to address the growing demand for mortgages is to hire, train and retain more employees. However, increasing the size of the team may result in a higher time to value (as new employees will take time to ramp up to desired levels of efficiency) and increased costs too. Lenders can benefit from IDP solutions that may be scaled up quickly with a marginal infrastructure cost.

Just digitization isn’t enough

Many lenders today receive applications through mortgage portals. While the first step of digitization of documents is taken care of, banks do not follow through to ensure the proper classification, extraction, and storage of these documents. As a result, an employee must still go through the documents to verify and authenticate their contents to ensure they are adequate for an application. It is no surprise that knowledge workers lose 50% of their time preparing documents and therefore, experience a 21% loss in productivity because of document issues.

Security and risks

Worldwide, the digital fraud attempt rate grew by 52.2% in 2021 compared to two years earlier. Banks or financial institutions that do not have intelligent document processing capabilities may be caught off guard or may not be able to respond in time to stop transactions. IDP, on the other hand, can reduce the incidence of fraudulent transactions by assessing large volumes of historical data accurately and in real-time. By identifying the patterns, an automated system can immediately flag a suspicious transaction and stop it if necessary.

KYC is another area where IDP software can help by minimizing human error. The IDP program can read submitted documents, verify the identity and details of the customer by searching through data repositories and even assign them a risk score, thereby helping the lenders meet regulatory standards.

Unaligned with consumer demands

Unsatisfactory products and fees, slow response to problem resolution, and a lack of convenience are some of the top reasons why financial institutions are are losing out to FinTechs and digital-only banks. One of the biggest contributions IDP can make is to automate repetitive manual tasks and free up lenders employees’ time in activities that will increase customer satisfaction—building trust & rapport and enhancing product offerings.

Automate document processing with Blanc Labs

There are many reasons why banks need intelligent document processing, and Blanc Labs provides a 360-degree IDP 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.

Challenges in Digital Lending

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

Challenges in Digital Lending

May 12, 2022
Digital Lending

Digital lending has evolved over the last ten years and the pandemic has only exacerbated the need for intuitive, enjoyable, dynamic, and accessible lending systems for both lenders and borrowers. In the age of Apple and Amazon, borrowers demand a seamless experience that does not involve speaking to a human being or filling out paper forms.

While traditional banks and monoline lenders are overhauling their systems to address these challenges, FinTech companies are making use of the gaps left by the big banks.

The Era of Digital Lending

According to the Canada Banker’s Association, 49% of Canadians do their banking digitally, but more importantly, 75% of Canadians intend to maintain the digital banking habits they picked up during the pandemic. Compared to five years ago, FinTech companies in the US today account for more than 38% of the personal loan space. Traditional banks, on the other hand, saw a loss of 12% of the personal loan space during the same period.

Why is this? The reason is a lack of simplicity, speed, and accessibility.

Leading FinTechs today can provide multiple quotes within minutes and fund loans within a matter of day. Apart from speed, online lenders today offer a seamless, fully digital experience as well as advanced features including security and risk assessment that does not involve a long-drawn-out credit check process.

                                                                   U.S. Digital Lending Platform Market Size

Digital Lending Challenges Faced by Lenders Today

Creating a fully automated, digital-first lending solution can be a complex process, especially if you don’t have the right tools and automation in place.

Automated self-service, compliance, fraud and cyber-security, document processing are just some of the many challenges that traditional financial institutions must overcome to match the experience offered by FinTechs today.

Here is our point of view on some of these key challenges:

1. Complicated and Slow Loan Origination Process

Can you think of living in a time before same-day delivery or tap payments? Neither can borrowers.

Companies that don’t offer instantaneous loan decisions run the risk of losing their customer to a FinTech that is faster and can provide quick decisions. Relying on antiquated loan origination processes that require filling multiple paper forms, visiting the bank in person, and taking days to evaluate risks and make funding decisions, will spell trouble. One study shows that 42% of respondents abandoned their applications because the process was too long and complicated, and 62% said they were unsatisfied with the digital experience, due to “too many touchpoints” and “the necessity of going to a physical location.”

Nimble FinTechs on the other hand are assessing credit risk and offering funds at the speed of light. One study by Smarter Loans found that 53% of respondents received their funds a mere 24 hours after applying for it, “suggesting that same-day-funding is becoming a standard in the industry.”

Thankfully, banks can implement digital native loan origination platforms that can automate the end to end loan origination process;  or they can address bottlenecks in it like underwriting, which will make the process more streamlined for both borrowers and lenders.

2. Partial measures instead of end-to-end solutions

Delivering an end-to-end solution is a mammoth task that needs significant resources and time.   The world of lending is full of large projects that took twelve to eighteen months to deliver value and this is not going to disrupt the FinTech community. Success for this is now measured in mere months.  Moreover, automating one part of the customer journey and ignoring the rest can cause more complications in the long run and can re-introduce manual intervention. Instead of a piecemeal approach, consider a unified lending solution with a modular structure that addresses all steps from information collection to underwriting, servicing, and reporting.  It is important to get the end state vision right first and then you can make incremental changes building towards your best customer journey if you elect to do things in recommended phases.

3. Document Intake and Data Storage

While traditional banks and brokers have been busy processing loans through paper-based or hardwired systems, FinTech companies are using automated processes to process loans faster and more transparently. Intelligent Document Processing (IDP) can automate the document intake process and apply AI (artificial intelligence) plus ML (machine learning) to extract data with more accuracy while converting unstructured data into structured data, making the data more useable. This can save you money and reduce human data entry error.  In most cases, this data can be prepopulated into origination and adjudication engines to drive faster straight-through processing and time to decisioning the loan.

                           Productivity loss due to manual document management

4. Data Silos and Lack of Personalization

During a digital transformation project, it is important to design the system in a way that the multiple components within that system can speak to each other and convey relevant data. If for some reason this does not happen, then it simply consumes more time—time that can be used for strategizing and planning. With so many systems in  silos, banks may not get a true 360-degree view of their business with a customer, therefore making it difficult to create personalized offers and recommendations for that customer. Ideally, banks should have a unified, transparent view of deposits, loans, and personal accounts if they want to keep the customer engaged and cross-sell new lending products over time to grow their share-of-wallet.

5. Regulations

Borrowers that come through the digital lending channel hand over a lot of sensitive information and so it makes good sense that lenders hardwire a regulatory compliance framework into their platform. Luckily, there are experts that can help business leaders stay on top of banking regulations and data privacy laws. The regulatory environment is rapidly changing and new industry driven changes around Open Banking are emerging as well. These dynamics are going to redefine and further embolden  FinTechs, drawing clear lines around how the participants in the banking ecosystem will work together.  Full assurance on regulatory reporting and compliance with industry standards is table stakes in any solution that meets this demand.

A Unified Lending Solution for Lenders

Blanc Labs provides a three-stage approach for digital lending which includes:

– Consulting assessment of your needs

– Streamlining processes and platforms

– Intelligent documentation processing (IDP)

Book a demo or discovery session with Blanc Labs to discover the impact of our digital lending solutions.

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.