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WorkFusion Primary Use Case

JG
Senior Product Manager at a financial services firm with 51-200 employees

We use WorkFusion for SPA, Smart Process Automation. SPA combines robotic process automation and machine learning. The heart of it is machine learning. The RPA processes are a few steps that a robot does instead of outsourcing to a human in India. It makes the process more efficient to execute any exceptions on the WorkFusion cloud.

It's a SaaS solution, so everything goes over the cloud. Only the results are delivered locally on-premises. We're using it for machine learning purposes to extract data. However, the process is not entirely straightforward and sometimes we need manual intervention by our third-party ops provider in India and Poland.

We have between 20 to 40 bots that work in our production environment. They do the work in the background, so we don't see what they do, but they handle the workload. We also have approximately 20 employees in India that for whenever a bot has a question or has an issue. Then a human being needs to look after that. This gets done by our colleagues in India based on training. We define the gold data to be specified in each document we want to have extracted. We also have very detailed instructions on what has to be done if something happens that is not as expected.

We work directly with WorkFusion. We also work with a back-office services provider and they do the manual exception handling. Whenever something isn't automatically extracted, it appears in the cloud. An employee of our service provider in India or Poland handles the manual extraction based on the detailed instructions. We get the results and import them into our target systems.

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Shamus Cardon - PeerSpot reviewer
IT Engineer III at a healthcare company with 10,001+ employees

I started with invoice processing. That uses a lot of different parts of the WorkFusion solution. It uses their built-in OCR package, built-in S3 instance, and built-in databases. Invoice processing is the big use case. 

We use their AutoML tagging machine learning use cases. Then, at the end, we use their true robotic process automation, using the SeleniumLibrary, to enter things into our ERP system.

I have used it for a couple of other projects. I have done this mostly because WorkFusion makes it easy to code out a straightforward business process, put it on a schedule, and hook it up to a database without needing to requisition all new things and servers to launch it. I can host it in one central spot.

Our particular instance is on-prem. It has five or six different Linux servers that all talk to each other as well as a handful of Windows machines that end up talking to the central Linux boxes. In my time here, we have had two different major versions of WorkFusion: 8.5 and 9.2. We are currently on version 9.2.

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PS
Sr. Manager at a financial services firm with 5,001-10,000 employees

Within my company, I am responsible for a line of business where we roll out automations for various internal stakeholders, and WorkFusion is the platform of choice within my organization.

Approximately 90% of our use cases are RPA-governed use cases. We have one use case now that is a machine learning (ML) based use case. While we are not adverse to using ML within WorkFusion, we are still in the process of identifying or exploring the right use cases within the organization that are the best fit for ML.

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Buyer's Guide
WorkFusion
June 2022
Learn what your peers think about WorkFusion. Get advice and tips from experienced pros sharing their opinions. Updated: June 2022.
607,178 professionals have used our research since 2012.
Lada Chu - PeerSpot reviewer
Senior Vice President, KYC Director at a financial services firm with 1,001-5,000 employees

We have been in two proofs of concept with the solution. We're wrapping up two use cases with it right now.

The first one is for what we call "adverse media." We're required to do adverse media searches on potential new clients, as well during periodic reviews of existing clients.

For example, if we're onboarding a major retailer as a client, that retailer will have numerous negative news items, or adverse media. There might be employment abuse claims, civil lawsuits, and criminal investigations. For a large retailer, we would expect that kind of media. Currently, our adverse media process is performed by human beings, my analysts. They have to make a determination about the news items, based on rules set forth about negative news. If an analyst determines a match between an article and a rule, we would then escalate it to the business. The business would then make a determination as to whether the negative news is of enough concern that we would not onboard the client. Or, if the retailer was already a client, the business would determine how we should proceed.

With WorkFusion, their model will now use the criteria my human analysts follow, data elements to focus on first to validate whether the news is associated directly with our client. We first have to determine if an article is a true match. There are thresholds within the rules, severity levels. There's a difference between someone accusing the client of money laundering and whether they've been found guilty. Other severity levels are things like has someone been arrested, indicted, convicted, gone to jail, or served jail time. The Workfusion model is applying all those steps and thresholds that my analysts use, and should come to the same conclusion. The goal is that my analysts will be able to focus on the true matches and work on those. The point is to use our limited resources to focus on the high-value targets.

In our other use case, clients bring us documentation that we require to onboard them, such as articles of incorporation and ownership documents. Currently, what happens is that a banker would transcribe the key information from those documents into our onboarding system to start onboarding the client. After the customer has been onboarded, our review team will conduct a quality check against that profile to make sure the documentation is fully aligned with what was entered into the onboarding application.

We're using Workfusion's OCR model to read the documents that are collected and check the information in them against the profile that was created by the banker to determine if everything is correct. If it's not correct, it will then alert my analyst and tell them: "You now need to do a review and identify areas where there is a discrepancy to be corrected."

Once we close out our PoCs we will move the solution to Azure.

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RT
Vice President of Intelligent Automation at a tech services company with 5,001-10,000 employees

Most of our use cases are for internal operations. We have automated use cases related to 10-plus departments. Most of our use cases are using the robotic process automation capabilities of WorkFusion. Only one use case is through the machine learning capability. Then, there are a lot of use cases that have optical character recognition (OCR) in them.

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MB
Intelligent Automation Manager at a retailer with 10,001+ employees

We have done a number of different workflow automations and process automations, spanning a large number of different business units. We have created bots with RPA. 

We have done a little machine learning and AI work with the solution, but not a ton. I haven't found a lot of use cases for this. 

It has delivered pretty good value for RPA and workflow automation, but we haven't gotten as much out of the machine learning, data extraction, and classification stuff.

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MS
Director, Automation Engineering & Application Development at a consultancy with 51-200 employees

It is related to order entry and customs processing. At a high level, it is automatically reading from emails, processing attachments, OCR, and machine learning.

We use it for our important use cases. We are a transportation company. We take orders, then we fulfill those orders. So, if we do not take the orders, then we have nothing to work on.

We also do cross-border freight. We move freight from the US to Canada and Canada to the US. We need government clearance before we can move the freight. For that, WorkFusion is also important.

It is on the cloud utilizing AWS. We are working on changing it to the SaaS model from this year onwards.

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SB
Head of Intelligent Automation - Africa Regions at a financial services firm with 10,001+ employees

We are using WorkFusion as our enterprise RPA solution at this time to help us deploy some automation. It is a hybrid-based installation. Eventually, we are going to try to move everything to the cloud. Some of our customers are dealing with transactions, trader solutions, governance compliance needs, and other special cases so it is not totally possible to go totally on the cloud at this time. There are also clients who deal with things like a KYC (Know Your Customer) type solution, and then a few operational needs like ATM reconciliation and financial revenue reconciliation. The regulations sometimes preclude certain solutions in certain configurations.  

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Samuel Kamau - PeerSpot reviewer
Co-Founder at Beta Edge Technology Limited

I am a solution provider and I implement RPA products and automate processes for my clients.

In my recent deployment of this product, it is primarily used for financial processes, such as reconciliation in Excel. There are different Excel sheets that I reconcile using automation.

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JD
Analyst, Intelligent Automation at a financial services firm with 10,001+ employees

Our primary use case is for desktop automation for smaller solutions that stand outside the development on the core operating systems.

We also use it for building robotics capabilities and skills in all of our geographies across fourteen countries in Africa.

Automations have been done over several operating environments and include solutions in the following areas.

1. Operations

2. Compliance and Risk (Regulation driven requirements)

3. Credit solutions and integration with decision systems

The primary focus is delivering solutions that enable better customer experience.

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JS
Robotics Support at a financial services firm with 10,001+ employees

Banking, FX Trading, Collateral, Allocations (FI, EQ)
Process inbound emails (with & without attachments) from external clients for above lines of business.

Workfusion uses Machine Learning to process inbound data.

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PM
Director & Co-founder at a tech services company with 1-10 employees

We are a technology startup and we are developing a process discovery product. As part of this, we are integration several RPA products with our platform. We do not deploy RPA products or create bots for our own use.

WorkFusion is used for automating mundane activities.

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KP
IT Program Manager at a computer software company with 5,001-10,000 employees

The solution can be used for any sort of financial invoicing and billing.

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DC
Banking RPA Senior Engineer at a financial services firm

We use WF on banking use cases

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Buyer's Guide
WorkFusion
June 2022
Learn what your peers think about WorkFusion. Get advice and tips from experienced pros sharing their opinions. Updated: June 2022.
607,178 professionals have used our research since 2012.