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2023 Fall Economic Update on Consumer-Driven Banking đŸ„ł

Financial Services | Digital Banking | Fintech | Open Banking

2023 Fall Economic Update on Consumer-Driven Banking đŸ„ł

November 29, 2023

When we attended the CLA Lenders Summit a few weeks ago, it seemed like everyone was ready to sign the death certificate for Open Banking in Canada. Very little, if any, material progress had been communicated on behalf of the government to create a regulatory framework or policy mandate to make good on the promise or timelines defined by an Advisory Committee on Open Banking Report which became the mandate of Abraham Tachjian, who was appointed as Canada’s Open Banking lead, by the Liberal government in 2022.

Fast-forward to Wednesday November 21st, 2023 when Finance Minister Chrystia Freeland provided her 2023 Fall Economic Update, our team, as well as many of our clients and industry collaborators were taken by surprise when the Liberals laid out a framework and timeline for Canada to implement a Consumer-Driven Banking approach.

Aside from a snazzy rebrand of the open banking moniker, the policy statement on Consumer-Driven Banking outlined the goal of “adopting legislation and fully implementing the necessary governance framework by 2025”. It would seem from the update, part of the governments motivation for moving ahead with consumer-driven banking is a focus on the affordability crises facing many Canadians. The Consumer-Driven Driven Banking policy statement was listed under the header of “Making Life More Affordable” in the economic update.  The update for Canada now seems to be following a similar path to how policy is being shaped and implemented in the US.

Our Take:

As long-term believers in the benefits of Open Banking, we are thrilled to learn of the renewed commitment to making consumer-directed banking a reality in Canada.  While there is still a lot of work to be done as well as the additional hurdle of new  legislation being tabled during an election cycle, we are committed to the potential  benefits of Consumer Directed Banking for banking customers and the significant opportunity for innovation and collaboration in the Canadian financial services sector.

You can read the full Fall Economic Statement here but if you are short on time, ChatGPT did a pretty good job of summarizing the statement in bullets, below.

 

Introduction to Consumer-Driven Banking:

    • Allows secure transfer of financial data via API.
    • Aims to replace unsecure screen-scraping.
    • Enables access to data-driven financial services.

Benefits of Consumer-driven Banking:

    • Consumers gain secure access to innovative financial tools.
    • Greater control over financial data for improved outcomes.
    • Small businesses experience reduced administrative burden.

Policy Objectives:

    • Safety and soundness of the financial sector.
    • Consumer financial well-being and protection.
    • Economic growth and international competitiveness.

Core Framework Elements:

    • Governance: Oversight and management of the system.
    • Scope: Types of data, participants, and expansion pace.
    • Accreditation: Requirements for participating in data sharing.
    • Common Rules: Privacy, security, and liability guidelines.
    • Technical Standards: Establishment and oversight of data flow.

Course of Action (Legislation in 2024):

    • Phased approach to scope, oversight, and screen-scraping elimination.
    • Key elements codified in legislation.
    • Mandate to a government-led entity for supervision and enforcement.

Governance (Effective Oversight):

    • Government-led entity to supervise and enforce the framework.
    • Model for provincial entities to “opt-in” to governance.
    • Strong governance framework to ensure compliance.

Scope (Phased Implementation):

    • Initial phase includes federally-regulated financial institutions.
    • Opt-in option for credit unions and third parties.
    • Reciprocal access for all entities to promote data portability.

Accreditation (Trusted Data Sharing):

    • Formal framework for entities collecting consumer data.
    • Regular reporting for accreditation maintenance.
    • Exemption for federally-regulated banks and credit unions.

Common Rules (Transparent Foundation):

    • Privacy, security, and liability obligations.
    • Compliance as a condition for data access.
    • Complements existing legislation.

Privacy (Protection Measures):

    • Participants must comply with legislative frameworks.
    • Specific privacy rules for financial data sharing.
    • Consent dashboards for real-time consumer control.

Liability (Clear Structure):

    • Statutory contractual relationship between participants.
    • Liability moves with the data and rests with the party at fault.
    • Internal policies and procedures for complaint handling.

Security (Protecting Consumer Data):

    • Clear security requirements for accredited entities.
    • Oversight of security standards in legislation.
    • Ongoing reporting obligations for data protection.

Single Technical Standard:

    • Mandate for a single technical standard.
    • Legislation to outline principles and oversight.

Next Steps for consumer-driven banking:

    • Department of Finance aims to implement the framework by 2025.
    • Ongoing engagement with industry stakeholders.
    • Legislative framework development and phased implementation.

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Team Member Spotlight – Noel John, VP of Client Engagement and Delivery

Financial Services | IT Management | Leadership

Team Member Spotlight – Noel John, VP of Client Engagement and Delivery

October 30, 2023

Blanc Labs’ recently appointed Noel John as VP of Client Engagement and Delivery.  We are thrilled that Noel has joined the team and brings with him a strong background in client engagement leadership.

Noel joins Blanc Labs from a fortune 500 publicly traded global technology and consulting company, where he spent close to 20 years on various leadership roles including leading a specialized QEA practice for Canadian BFSI customers. As a trusted partner for clients, he aids them in achieving their business objectives. His approach is rooted in the belief that true transformation requires active listening and a partnering approach through all phases of the journey.

Noel John
VP Client Engagement & Delivery, Blanc Labs

My focus is on building a One-Team culture in the customer-partner ecosystem, encouraging cross-functional cooperation, building high performance teams, and growth strategies that lead to driving successful outcomes.

5 Questions with Noel John

Get to know our amazing team members.

Q: Noel, you have an extensive background in client engagement and delivery, what do you think are the biggest drivers of success?

I have found that bringing a client centric approach to everything you do has proven to be a tried and trusted driver for success. You need to understand the client’s business, their future plans and the industry trends. You need to be their trusted partner to drive the required change.

 Q: Technology is always evolving, and it seems like we are in a period of rapid acceleration. What technology trends are you watching closely and/or building capability to serve clients?   

Artificial Intelligence has become de-facto topic in a huge number of client conversations. AI is not just a technological advancement but it’s poised to transform the whole business i.e it’s transforming how clients conduct their business.

We are still in the very early stages of this evolution but we now have all the ingredients like data, compute power, storage etc. Human creativity combined with the AI capabilities will unleash enormous opportunities for consumers and businesses.

These are some of the most exciting spaces to be working with clients because enabling this transformative technology will require a highly collaborative approach between business and technology teams, as well as partner support.

Q: What attracted you to Blanc Labs? Why did you decide to join this organization at this point in your career?

While I spent most of my career so far with large fortune 500 company, I was hungry to have new experiences, learn new skills and contribute along the way.

Blanc Labs provided this opportunity to run your portfolio like a start-up. I am looking forward to making a meaningful impact leveraging Blanc Labs’ entrepreneurial and innovative culture.

Q: Noel, thanks for the thoughtful responses.  We are super excited to have you join the team and work with you.  Last question, tell us something about yourself that folks in your professional network might not know about you.

I love to be outdoors during all four seasons, hiking in summer and skiing in winter.   

I also own a motorcycle and love to take weekend trips to cruise the backroads of Ontario.  This time of year is particularly special as you get to see the amazing fall colors on the trees.  Safe motoring and see you on the road! 

 

You can reach Noel John at noelj@blanclabs.com or LinkedIn.

Blanc Labs Noel John

Innovation Is The Key To Digitally Transform Financial Services

How EQ Bank is Using Financial Data Integrations to Supercharge Their Residential Lending Process

Case Studies

How EQ Bank is Using Financial Data Integrations to Supercharge Their Residential Lending Process

When Our Clients Win, We Win.
Financial Services | Digital Banking | Integration | Residential Lending
and and

Summary

Equitable Bank is Canada’s seventh largest Schedule I bank and is ranked the number one Canadian Bank on the 2023 Forbes list of World’s Best Banks. Managing more than $50 billion in assets and serving more than 5 million Canadians, the bank offers a diverse suite of residential lending, commercial lending, and savings solutions, including high-interest savings products and guaranteed investment certificates.

As a challenger bank focused on delivering better banking experiences, Equitable Bank wanted to set a new standard for the mortgage application process that is fast, seamless and error free.

Working with Blanc Labs as a technology strategy and systems integration partner, EQ decided to implement Flinks Data Aggregation & Connectivity tools to transform their lending process by developing a new Statement Share tool.

The Statement Share tool overhauled EQ’s mortgage approval process, simplifying the identity and funds verification process for both customers and underwriters.

 

*Instant Bank Verification (IBV) and Financial Data Enrichment tools can accelerate the underwriting process by up to 30%*. Stats based on a sample size of Flinks’ clients

30%* Improvement in underwriting speed
When Our Clients Win, We Win.

The need for an improved mortgage approval journey

Buying a house is a major milestone for most people, often the biggest purchase they’ll ever make. The process involves various steps, including getting approved for a mortgage, which can be quite stressful on its own.

Financial institutions require a lot of data and documentation to move forward with their mortgage underwriting process. Unfortunately, this puts the burden on customers to gather and share all of that information.

The process of sharing documents is not a pleasant one. It involves downloading reports from bank portals, scanning or printing them, emailing them to the mortgage officer or handing in physical copies, and notifying the broker.

Paul von Martels
Vice President, EQ Bank

When clients send their bank statements directly to us by email, they’re sending them in PDF format—which requires manual work to process and to review for inconsistencies.

EQB had an additional layer of complexity. Their customers, most of whom are small business owners, have multiple bank accounts which were used for both business and personal purposes. This made the information sharing process even more confusing and cumbersome.

EQB wanted an elegant solution that would make the mortgage application process simpler for the customer and less complicated for the mortgage underwriters. The result was the Statement Share tool.

The Statement Share tool

Enhancing the Customer Experience

The Statement share tool uses Flinks’ data connectivity to provide customers witha digital interface where they can share their banking information securely and submit an application with just a few clicks. The tool sources information directly from banks, making the process reliable and error free. The tool also has the provision to notify the broker that the application is complete. Since introducing the tool, EQB has seen a significant uptick in its use by customers.

Improving Employee Productivity

Within the back office, the tool is a boon to mortgage underwriters who can easily verify the income and identity information. Blanc Labs integrated the Flinks API with the bank’s mortgage engine without having to rip or replace legacy components. This led to better employee productivity and experience.

Ashley-Yantzi
Ashley-Yantzi
Ashley Yantzi
Vice President of Residential Lending, EQ Bank

We use the Statement Share tool, created by Blanc Labs using Flinks APIs, at deal origination. There are various use cases for us, but the tool is a crucial part of our verification process that assesses whether what borrowers have stated in their applications is true. Thanks to the API, we are seeing statements and factual data directly from their banks.

In Conclusion

Equitable Bank’s Statement Share tool, powered by Flinks’ data connectivity and integrated by Blanc Labs, exemplifies the commitment to enhancing customer experience and optimizing employee efficiency. By streamlining the mortgage application process and reducing complexities, Equitable Bank has successfully evolved the way people navigate the path to homeownership, making it a smoother and more enjoyable journey for all parties involved.

If you are interested in evolving your financial ecosystem to improve your customer experience and employee productivity, reach out to us at Blanc Labs and let’s explore the possibilities together. Contact us today and start unlocking the potential of open APIs for your business.

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Blanc Labs Expedites the Development of Mortgage Product for Canada’s Top Brokerage

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Blanc Labs Expedites the Development of Mortgage Product for Canada’s Top Brokerage

59% of organizations looking to add BaaS capabilities are currently in the testing phase
Financial Services | Integrations | Services

Defining the Opportunity

Questrade, Canada’s leading discount brokerage had an aggressive target date to launch and debut its residential mortgage product to originate loans through an in-house, proprietary Loan Origination System (LOS) . The LOS solution needed to collect loan application data and documents from the borrower and co-borrowers. The challenge was to buy or build the document automation layer of the solution in a short period of time.

Questrade partnered with Blanc Labs to leverage their experience as a technology partner with experience in building digital lending products.

A big goal of the digital direct mortgage offering was to automate as much of the document collection and document management function by offering a secure upload workflow for the borrowers and secure document storage for underwriters and internal team members. The solution also had to enable a seamless document viewing and proofing workflow for mortgage officers to define the loan conditions.

Ultimately, Questrade selected  Blanc Labs’ for their expertise in the Canadian mortgage industry as a long-term partner which dramatically accelerated the timeline to design, build and launch the award-winning with Quest Mortgage platform in 2020 .

Challenge: Aggressive delivery target
Challenge: Limited internal resources
of banking leaders are prioritizing BaaS capablities

Approach and Solution

To deliver the requirements, Blanc Labs collaborated with the online brokerage’s stakeholders in two phases: Discovery and Design, and Solution Delivery and Integration.

 

Phase 1: Discovery and Design

During several agile design workshops, Blanc Labs’s multidisciplinary team of subject matter experts and specialists in user experience (UX), product, and engineering worked closely with the online brokerage’s senior executives and stakeholders representing both business and technology teams. The goal was to understand the requirements and imagine the total solution while keeping in mind the capabilities of Blanc Labs’s document automation product, Kapti.

Kapti is an automation software for document capture and processing. With Kapti, users can automate the document collection workflow through a web-based application and APIs. Kapti also uses proprietary machine learning (ML) technology to intelligently classify and split multi-page documents to extract, analyze, and deliver critical data from documents to generate decision-making insights. For more information, visit www.kapti.io.

The result was incorporating Kapti’s Application Programming Interface (API) and web-based user interface (UI) in the following arrangement:

    • Use Kapti headless as an API-first product to initiate document request flows

    • Use Kapti UI for document upload by borrowers and mortgage officers

    • Use Kapti UI for document proofing by mortgage officers

    • Integrate Kapti with the online brokerage’s Google Cloud Platform (GCP) to store uploaded documents

    • Integrate Kapti with the online brokerage’s enterprise virus software to scan each document for malware

    • Integrate Kapti with the online brokerage’s single-sign-on and identity manager for borrower and employee login

    • Deploy Kapti as a container on the online brokerage’s private GCP cloud (GKE: Google Kubernetes cluster)

Phase 2: Solution Delivery and Integration

Blanc Labs had a major advantage over other vendors and options: All the features and requirements listed during the discovery phase were part of Kapti’s out-of-the-box specification. This meant that the solution delivery didn’t need any development—Kapti just needed to be installed and configured to fulfill its duties.

During this phase, Blanc Labs worked on two streams of product and tech to deliver the solution. The Kapti product team worked closely with the online brokerage’s business and mortgage operations teams to configure the document types and user experience flows. In parallel, the Kapti engineering team worked with the online brokerage’s technology and infrastructure architecture teams to deploy the product and integrate it with the final state cloud solution ecosystem.

Blanc Labs had a major advantage over other vendors and options: Its product. Kapti, just needed to be installed and configured— extra development wasn’t necessary.

Approach

Everything We Make Starts With People

1 From career growth and compensation, to company financials and decisions – the communication is incredible and truly honors an open door policy.

Edward Kholodenko
Software Engineer

2 From career growth and compensation, to company financials and decisions – the communication is incredible and truly honors an open door policy.

Edward Kholodenko
Software Engineer

3 From career growth and compensation, to company financials and decisions – the communication is incredible and truly honors an open door policy.

Edward Kholodenko
Software Engineer

4 From career growth and compensation, to company financials and decisions – the communication is incredible and truly honors an open door policy.

Edward Kholodenko
Software Engineer

1 From career growth and compensation, to company financials and decisions – the communication is incredible and truly honors an open door policy.

Edward Kholodenko
Software Engineer

2 From career growth and compensation, to company financials and decisions – the communication is incredible and truly honors an open door policy.

Edward Kholodenko
Software Engineer

3 From career growth and compensation, to company financials and decisions – the communication is incredible and truly honors an open door policy.

Edward Kholodenko
Software Engineer

4 From career growth and compensation, to company financials and decisions – the communication is incredible and truly honors an open door policy.

Edward Kholodenko
Software Engineer

1 From career growth and compensation, to company financials and decisions – the communication is incredible and truly honors an open door policy.

Edward Kholodenko
Software Engineer

2 From career growth and compensation, to company financials and decisions – the communication is incredible and truly honors an open door policy.

Edward Kholodenko
Software Engineer

3 From career growth and compensation, to company financials and decisions – the communication is incredible and truly honors an open door policy.

Edward Kholodenko
Software Engineer

4 From career growth and compensation, to company financials and decisions – the communication is incredible and truly honors an open door policy.

Edward Kholodenko
Software Engineer

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Building An Enhanced Commercial Lending Credit Risk Platform for EQ Bank

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Building An Enhanced Commercial Lending Credit Risk Platform for EQ Bank

Unstructured Data Processing
Financial Services | Commercial Lending | Integrations | Services
and

Summary

Equitable Bank (EQB) approached Blanc Labs to envision, build, and implement a highly complex commercial lending credit risk platform. Blanc Labs has been an integral part of EQB’s digital transformation journey. In this case study, we provide a brief overview of EQB’s digital transformation journey, share highlights from its recent work with Blanc Labs on a new commercial lending platform, and identify the key factors that have made the collaboration between Equitable Bank and Blanc Labs so successful.

$6.7 Trillion Potential savings by 2025 for businesses that adopt automation.

Challenges

Equitable Bank is Canada’s challenger bank, ranked No 1 for two years running (2021-23) in the Forbes list of the World’s Best Banks. Since 2014, it has strategically focused on being a leader in digital banking, embracing an ambitious digital transformation agenda centered around its lending and deposit businesses. The bank knew that to survive and thrive in an increasingly digital world, it needed to get better control over its data and use innovative technologies more effectively to create value both inside the bank and for its brokers and end customers.

To digitally transform their operations, EQ Bank approached Blanc Labs to create a customized commercial lending credit risk platform for improving its data governance, underwriting and decisioning processes, and its client and employee experience.

Our Approach

Blanc Labs took an Agile approach to developing the bank’s commercial lending platform.

Concept to First Release

EQ Bank was determined to launch its commercial lending platform as quickly as possible. The bank and project team set a target to release Version 1 of the platform within 12 months, with the understanding that additional releases would follow to address gaps, improve functionality, and enhance the user experience.

To meet the tight timelines, the team designed and built the platform in parallel with additional discovery related to the requirements of the bank’s three commercial lending business units. The strategy was to ensure that the business line with highest volume and most standardized deals would be the primary focus on the first release, followed by the business line with small to medium sized deals on the second and finally the business line with deals representing low volume, high dollar value and more complex credit structures to be addressed in the third release. To expedite the entire process and drive more value, the team introduced feedback sessions with senior management to share design work visually and get immediate feedback. This process not only made feedback more efficient, but also helped align all stakeholders on prioritization.

The team completed the design and build work for Release 1 in mid-2019, conducted appropriate testing, and deployed the first release of the platform on schedule.

Darren-Lorimer
Darren-Lorimer
Darren Lorimer
Senior Vice President and Group Head, Commercial Banking at EQ Bank

What we have built with Blanc Labs as our partner, is a data-centric model which is unique in the Canadian marketplace. As we continue to optimize the build, we will realize many benefits over the years.

Building a Release Train

As confidence in the project rose, stakeholders became increasingly more involved and collaborative. At this point, employing a very efficient and disciplined release cycle was paramount. To make the release process more effective and efficient, the project team introduced the concept of a release train. This meant that the timing of each release was predefined, but the scope of each release was flexible and agile. When fully implemented, the release train resulted in high utilization of all team members and a more predictable cycle of activities and releases.

By November 2021, the bank had fully migrated all loans to the new platform and all lines of businesses were using the platform. This was a critical milestone for EQB as it meant the bank was now well positioned to begin reaping the rewards of the new platform with better data governance, enhanced risk management and a better employee and customer experience.

Establishing a foundation for future growth

With the platform now fully in use, new releases are expected to target niche lending scenarios and improvements to the user experience. Future releases will focus on shortening the end to end customer journey. The platform is expected to be fully mature by 2023.

Dan-Broten
Dan-Broten
Dan Broten
CTO, EQ Bank

The solution we created with Blanc Labs was an early adopter of our cloud-only, digital platform architecture. The platform approach provided capabilities for the team to incrementally build the solution using agile techniques while also providing consistent security and operational resilience.

Key Results

Blanc Labs was able to work closely with Equitable Bank to build a customized, data centric commercial lending platform that produces a consistent and accurate risk assessment leading to better decision making. Over time, the improved collection and accessibility of data will allow Equitable Bank to refine their risk rating models and further improve their risk management.

Stay ahead of the curve with our advanced solution engineering capabilities.

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Using RPA in Banking

Financial Services | AI | Banking Automation | Digital Banking | Enterprise Automation

Using RPA in Banking

May 8, 2023
Using RPA in Banking

 

All banking or financial institutions can relate to the struggle of managing piles of structured and unstructured data daily. This task requires repetitive and manual effort from your employees that they could otherwise dedicate to high-value work. It can also be time-consuming and prone to errors, ultimately hampering your bank’s customer experience. Fortunately, automation technologies are proving to be a boon for the finance sector.

The finance domain is experiencing a major transformation, with banking automation and digitization at the forefront. According to a study by McKinsey, machines will handle between 10% to 25% of banking functions in the next few years, which can free up valuable time and resources for employees to focus on more strategic initiatives.

What is Robotic Process Automation (RPA)?

RPA is an automation technology governed by structured inputs and business logic. RPA in banking is a powerful tool that can automate repetitive and time-consuming tasks. It allows banks and financial institutions to gain a competitive advantage by automating routine tasks cost-effectively, fast, and without errors.

Banks, credit unions, or other financial institutions can set up robotic applications to handle tasks like capturing and analyzing information from documents, performing transactions, triggering responses, managing data, and coordinating with other digital systems. The possibilities for using RPA in finance are innumerable  and can include a range of functionalities such as generating reports, sending auto emails, and even auto-decisioning.

How RPA works

Robotic Process Automation works by automating repetitive and routine tasks that are currently performed manually. Software robots, also known as ‘bots,’ are designed to mimic human actions and interactions with digital systems. These rule-based bots can be configured to perform specific tasks, such as document processing, data entry, transaction execution, complete keystrokes, and more.

Once a bot is configured, it can be triggered to run automatically or on a schedule, freeing up human resources to focus on customer service or other higher-value or strategic activities. The bot interacts with the relevant systems and applications, capturing and analyzing data, navigating systems, and automating workflows as needed.

One of the key advantages of RPA in finance is that it is non-intrusive, meaning that it operates within existing systems and processes, without requiring any changes to the underlying infrastructure. This means that no changes are made to the underlying applications. RPA bots perform tasks in a similar manner  to employees- by signing into applications, entering data, conducting calculations, and logging out. They do this at the user interface or application surface layer by imitating mouse movements and the keystrokes made by employees.

This makes it easier to implement and reduces the risk of disruption to existing operations. As per Forbes, RPA usage has seen a rise in popularity in the last few years and will continue to see double-digit growth in 2023.Many people use the terms ‘RPA’ and ‘Intelligent Automation’ (IA) interchangeably. Both are banking automation technologies that improve efficiency, but are they the same?

Are RPA and Intelligent Automation the same?

No, RPA is not IA and IA is not RPA. While RPA is a rule-based approach for everyday tasks, intelligent automation uses Artificial Intelligence (AI) and Machine Learning (ML) technologies to automate more complex and strategic processes. IA encompasses a wide range of technologies which includes RPA. IA enables organizations to automate not just manual tasks but also decision-making processes and allows for continuous improvement through self-learning.

A combination of IA and RPA can unlock the true potential of banking automation. When RPA is combined with the powers of AI, ML, and natural language processing, it dramatically increases the software’s skills to execute advanced cognitive processes like understanding speech, carrying out conversations, comprehending semi-structured tasks such as purchase orders, invoices and unstructured documents like emails, text files and images.

Thus, RPA and its combination technologies are fully capable of taking your banking and financial business to new heights.

What are the benefits of RPA in Banking?

The global RPA market is projected to grow at a CAGR of 23.4%, from $10.01 Billion in 2022 to $43.2 Billion in 2029. Evidently, more industries worldwide are realizing the importance of RPA. Here are some benefits of using RPA in banking and financial institutions.

Improved Scalability

Robots can work faster and longer than humans without taking breaks. RPA can also be scaled to meet changing business needs, making it an ideal solution for organizations that are looking to grow and expand their operations and provide additional services.

Enhanced Compliance and Risk Management

RPA can help banks and financial institutions improve their compliance and risk management processes. For example, the software can be configured to monitor transactions for potential fraud and to ensure compliance with regulatory requirements. It can also inform the bank authorities in case any anomaly is found.

Improved Customer Service

RPA can enable faster and more personalized service to customers. For example, the software can be configured to handle routine customer inquiries and transactions, reduce wait times and improving the overall customer experience.

Increased Efficiency

RPA can automate repetitive and manual tasks, redirecting human resources to other higher-value and strategic activities. This can result in faster processing times, improved accuracy, and reduced costs. According to a study by Deloitte, banking institutions could save about $40 million over the first 3 years of using RPA in banking.

Better Data Management

RPA can automate the collection, analysis, and management of data, making it easier for banks and financial institutions to gain insights and make informed decisions. This means faster account opening or closing, loan and document processing, data entry, and retrieval.

Top Use Cases of RPA in Banking

RPA can be applied in several ways in the banking and finance industry. Here are some examples of RPA use cases in banking and finance:

Accounts Payable

RPA can automate the manual, repetitive tasks involved in the accounts payable process, such as vendor invoice processing, field validation, and payment authorization. RPA software in combination with Optical Character Recognition (OCR) can be configured to extract data from invoices, perform data validation, and generate payment requests, reducing the risk of errors and freeing up human resources.  This system can also notify the bank in case of any errors.

Mortgage Processing

Mortgage processing involves hundreds of documents that need to be gathered and assessed. RPA can streamline the mortgage application process by automating tasks such as document verification, credit checks, and loan underwriting. By using RPA to handle routine tasks, banks, and financial institutions can improve processing time, reduce the risk of errors, and enhance the overall customer experience.

Fraud Detection

According to the Federal Trade Comission (FTC), banks face the ultimate risk of forgoing money to fraud, which costs them almost $8.8 billion in revenue in 2022. This figure was 30% more than than what was lost to bank fraud in 2021 .  RPA can assist in detecting potential fraud by automating the monitoring of transactions for unusual patterns and anomalies. Bots can be configured to perform real-time ‘if-then’ analysis of transaction data, flagging potential fraud cases as defined for further investigation by human analysts.

KYC (Know Your Customer)

RPA can automate the KYC onboarding process, including the collection, verification, and analysis of customer data. RPA software can be configured to handle routine tasks such as data entry, document verification, and background checks, reducing the risk of errors and faster account opening, thus resulting in enhanced customer satisfaction.

Thus, using RPA in your bank and financial institution can not only save time and money but also boost productivity. Banking automation gives you a chance to gain a competitive edge by leveraging technology and becoming more efficient.

Blanc Labs Automation Solution for Banks

Blanc Labs helps banks, credit unions, and financial institutions with their digital transformation journey by providing solutions that are RPA-based. Our services include integrating advanced automation technologies into your processes to boost efficiency and reduce the potential for errors caused by manual effort.

We offer a tailored approach that combines RPA, ML, and AI to automate complex tasks, such as mortgage processing and document processing, allowing you to conserve resources, speed up decision-making  and provide quicker and improved financial services to your customers.

If your bank processes a huge amount of data everyday, we can help you. Book a discovery call with us and let us explain how we can increase the efficiency of your bank’s core functions. Our team will analyze your current processes and propose a tailor-made automation solution that can operate seamlessly and in conjunction with your existing systems.

How to Automate Loan Origination Systems

Financial Services | AI | Banking Automation | Digital Banking | Lending Technology

How to Automate Loan Origination Systems

May 1, 2023
Loan Origination Systems

Loan origination automation is critical because the loan origination process is labor-intensive and prone to human error.

Translation?

The process takes expensive human capital that you can dedicate to other, more strategic tasks. It’s also prone to human error, which increases your costs and puts your reputation at risk.

Automating the process takes humans out of the equation, minimizing the cost of human capital and the risk of human error.

In this article, we explain how to automate the process using an automated loan origination system.

What is the Loan Origination Process?

Loan origination is the process of receiving a mortgage application from a borrower, underwriting the application, and releasing the funds to the borrower or rejecting the application.

When a customer applies for a mortgage, the lender initiates (or originates) the process necessary to determine if a borrower should be lent funds according to the institution’s policies.

The process is extensive and takes an average of 35 to 40 days. The origination process involves five steps, as explained below.

Prequalification

Prequalification is a screening stage. This is where lenders look for potential reasons that can adversely impact a borrower’s capability to repay the loan.

Typically, lenders look for things like:

  • Income: Does the borrower make enough money to be able to service the loan payments, and is that income consistent?
  • Assets: Should the borrower’s income stop for some reason; do they have enough assets to remain solvent given their existing liabilities?
  • Debt: Is the borrower overleveraged? Are the debts secured or unsecured?
  • Credit record: Has the buyer made loan payments on time in the past?

These factors help the lender determine if they should spend time processing the application further.

Preparing a Loan Packet

Lenders create a packet (essentially a file of documents) for prequalified borrowers.

The packet includes the borrower’s documents, including KYC, financial statements, and other relevant documents that provide an overview of the borrower’s debt servicing capability.

Lenders also include documents that highlight the reasons that make an applicant eligible or ineligible to be considered for the loan.

For example, the lender may include the borrower’s debt-to-income ratio, properties and assets at market value, and income streams to provide an overview of whether the borrower is a good candidate for the loan.

Some lenders take extra steps to double-check the applicant’s claims.

For example, lenders might hire a valuer or research property rates to verify your real estate investment’s current market value. The valuer’s report is added to the packet for the underwriter’s reference.

Negotiation

Many borrowers, especially those with an excellent credit record, browse their options before accepting a lender’s offer.

The borrower might want to negotiate a lower rate or ask for a fixed rate instead of a floating rate.

Term Sheet Disclosure

A term sheet is a summary of the loan. It’s a non-binding document that contains the terms and conditions of the mortgage deal.

The term sheet includes the tenure, interest rate, principal amount, foreclosure charges, processing fees, and other relevant details.

Loan Closing

If the negotiations go well and the borrower accepts the offer, the lender closes the loan.

The lender creates various closing documents, including final closing disclosure, titling documents, and a promissory note.

The borrower and lender sign the documents, and the lender disburses the funds as agreed.

3 Ways to Automate Loan Origination

Now that you know the loan origination process, let’s talk about automating parts of this process to make it more efficient.

Digitizing Loan Applications

You can create an online portal where applicants can initiate a loan application and upload their KYC and other documents.

The documents are automatically transferred to your internal systems for prequalifying the applicant.

IDP extracts and relays the applicant’s data from the documents to your system.

Once the data is in the system, robotic process automation (RPA) can be used to determine if an applicant should be prequalified.

You can use a machine learning (ML) algorithm for deeper insights.

ML can help identify characteristics that make a person more or less likely to service the loan until the end of the term, allowing you to make smarter decisions.

Assembling Loan Documentation

Cloud-based RPA can collect documents from the online portal and organize them in one location. Not only are digital copies faster to collect, but they’re easy to store and search.

Think about it. You’ve received an application, but it’s missing the cash flow statement for last year. You’ll need to email or call the applicant to upload the documents, wasting your and the applicant’s time.

Lenders typically have a document checklist. Automating checklists is easy with RPA — when the applicant forgets to upload a document, the RPA can trigger notifications to the applicant.

The system can also notify the loan officer if the applicant becomes non-responsive.

Speeding Up Underwriting

Borrowers want faster access to funds, but lenders must complete their due diligence.

Lending automation can help reduce the time between application and approval.

With technologies like artificial intelligence (AI), ML, and RPA, automation systems can assess an applicant’s creditworthiness within seconds.

RPA can help with basics like checking the minimum credit score and income levels. RPA can also flag any areas that indicate greater risk, such as excessive variability in the applicant’s cash flows.

Moreover, loan origination is a compliance-heavy process. It’s easy to forget a small step when you’re overwhelmed with loan applications.

RPA ensures all compliance steps are taken care of. If they’re not, the system can trigger alerts for the underwriter as well as the superiors.

AI and ML can provide deeper insights. These technologies can use big data to identify patterns that make a borrower more likely to default, allowing you to make smarter decisions fast.

Moreover, AI and ML can help you look beyond credit scores and find people that are more creditworthy than their credit scores suggest.

As Dimuthu Ratnadiwakara, assistant professor of finance at Louisiana State University, explains:

“Traditional models tend to lock anyone with a low credit score—including many young people, college-educated people, low-income people, Black and Hispanic people and anyone who lives in an area where there are more minorities, renters and foreign-born—out of the credit market.”

How Shortening Loan Origination With Automation Helps

Shortening the loan origination process benefits you in multiple ways:

  • Match customer expectations: You’ll deliver on the customers’ expectations by offering faster loan processing. 40% of mortgage customers are willing to complete the entire process using self-serve digital tools, but 67% still interact with a human representative via phone.
  • Deliver better experiences: Automation offers various opportunities to improve customer experience. For example, you can set up an AI chatbot that responds to customers’ questions in real time.
  • Increase efficiency: You can process more applications per month by automating loan origination.
  • Better use of your staff’s time: Automated workflows allow credit officers to focus on parts of the business that require a human touch, such as building stronger relationships with clients, than on repetitive tasks that automation can perform more accurately.

Loan Origination Automation with Blanc Labs

Selecting the right partner to set up loan origination automation is critical. Partnering with Blanc Labs ensures frictionless implementation of a personalized loan origination system.

Blanc Labs tailor-makes solutions best suited for your needs and workflow. Blanc Labs starts by assessing your needs and creating a strategy to streamline your loan origination processes. Then, Blanc Labs creates an automation system using technologies like RPA, AI, and ML.

Book a demo to learn how Blanc Labs can help you automate your loan origination workflow.

10 Tips to Successfully Implement RPA in Finance

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

10 Tips to Successfully Implement RPA in Finance

April 14, 2023
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 steps

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.

Banking Automation: The Complete Guide

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

Banking Automation: The Complete Guide

April 6, 2023
Banking Automation

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

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

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

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

What is Banking Automation?

Banking automation involves automating tasks that previously required manual effort.

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

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

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

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

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

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

Generative AI and Banking Automation

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

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

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

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

What is RPA?

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

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

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

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

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

You can use RPA in banking operations for various purposes.

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

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

The Need for Automation in Banking Operations

Banks need automation to:

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

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

Why Banks Need Automation

To Deliver Faster, Personalized Customer Experiences

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

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

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

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

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

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

To Improve Cybersecurity

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

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

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

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

For Better Decision Making

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

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

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

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

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

To Empower Employees

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

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

Challenges Faced by Banks Today

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

Inefficient Manual Processes

Manual processes are time and resource-intensive.

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

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

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

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

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

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

Automation Without Integration

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

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

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

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

Increase in Competition

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

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

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

Benefits of Banking Automatios

Benefits of Automation in Banking

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

Improves Operational Efficiency

An error-free automation system can supercharge operational efficiency.

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

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

Makes Processes Scalable

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

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

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

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

Cost Reduction

Automation helps reduce costs on multiple fronts:

a. Stationery

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

b. Human error

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

c. Increased employee satisfaction

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

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

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

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

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

Customer Satisfaction

Automation can help meet customer expectations in various ways.

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

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

How fast? Ideally, in real-time.

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

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

Better Risk Management

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

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

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

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

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

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

Blanc Labs’ Banking Automation Solutions

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

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

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