Use Cases for UiPath

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UiPath Use cases

The process that are being automated most frequently include industry-specific activities, such as loan application processing in banking, claims processing in insurance, contact center process in the front-office, and finance and accounting in the back-office.

The uses cases of RPA technology vendors:

  a) Industry-specific.

      i. Claims processing.

     ii. Policy servicing and reporting.

     iii. Card activation.

     iv. Fraud claims discovery.

 b) Contact centers.

     i. Customer Data Management.

    ii. Contact processing.

 c) Finance and Accounting.

     i. GL and reporting.

    ii. AR and Cash Management.

    iii. AP and expense reporting.

d) Human Resource.

    i. New joiners and leavers.

    ii. Payroll variation checking.

e) Procurement.

    i. Invoice processing.

    ii. PO processing.

    iii. Inventory management.

 f) Web-based.

 g) Others.

They have been many good use cases of RPA and how it enabled enterprises to handle recurring process issues and streamlining them.

Which are mostly used use cases in UiPath?

In their quest for digital transformation, banking organizations and other financial institutions have established themselves as the early adopters of smart technologies.

Banking:

UiPath helps in banking companies differentiate. It executes process productivity and decreases costs while assuring regulative compliance and longer analytical insight. Implementation with UiPath is quicker and competitively minute expensive than IT automation schemes. The greatest part: it creates triple-digit ROI’s in the first year of performances.

Although, organizations yet require to beat a better stability between the front and the back office while growing faster and more reliable.

Credit Underwriting:

One of the clients served the UiPath solution for their Credit Underwriting activity, with two sub-processes profiting directly from RPA: Retail Credit Assessment and Retail Fraud Prevention. Robot accessed up to 15 applications, both internal and external. The initial restraint was that the bank had an insufficient number of resources allocated, which was weighing heavily on the staff, generating big inefficiencies.

Retail Credit Assessment:

The robots check the assets/vulnerability/taxes/other related knowledge of the client (credit applicant) in multiple databases and post it to the credit analyst in a report.

Retail Fraud Detection:

Robots can check various internal and external databases for possible clues of an unbelieving activity about the bank’s client.

Collecting and observing the information required for fraud detection is a difficult process for operators if performed manually. RPA software robots decrease the operator involvement required, by tracing bank account and credit card activity in real-time. By recognizing data models, RPA can assess client risk and anticipate fraudulent activity.

Insurance:

With demands to develop efficiencies and increase margins, insurance companies are identifying important competitive strength on various aspects. Deploying a robot for front-end tasks to perform a better client experience is pushing all insurance companies to track the path of new adapters in RPA just to hold the pace.

In insurance companies are presently very anxious to adopt automation because of the legacy systems, and of their yearly financial and compliance aims. And the main profits they obtain from RPA, besides reducing their costs, are compliance and scalability.

The UiPath result delivers “Scalability” for a greater performance. UiPath Orchestrator is influenced by a multi-tenancy characteristic that enables creating a bunch of tenants and isolating all their data utilizing an individual orchestrator instance.

A single user may run multiple robot runtimes in parallel, in the same virtual machine, allowing for real-time collaboration and complete reuse and redistribution of automation resources. Rollback is easy in cases of recovery scenarios.

Other significant trends influencing Insurance concern:

i)  Consolidating the new mergers and acquisitions between various insurers.

ii) Priority is given to international regulators over-regulation from national or regional organizations.

iii)  The rise of InsureTech partnerships, i.e. companies that deliver services and products only for specific fields of the industry; this lead to customers using different providers and getting informed via insurance aggregators.

At present everyone has started to upgrade their technical capabilities with automation tools, such as RPA.

Healthcare:

UiPath assists healthcare customers to survey its RPA result technology as “claim repair” robots, non-invasively integrating with back-end systems and databases. Moreover, it brings intelligent automation to “error and edit” claims that would otherwise drop into delayed and high-expensive manual remediation.

They help customers quickly incorporate process changes to support new products and stay ahead of the competition.

Our results to reduce claim processing turn-around-time and sharply lower operational prices.

Healthcare Challenges and solutions:

Bug release automation:

This healthcare insurer found that one to two thousand claims were being stopped each day for a simple error code associated with missing or incorrect data. These claims had to be worked manually to correct or supplied the claim data from other systems.

The RPA solution was robots with automation scripts based on the same business rules used by the claims group to manually correct the errors. Both the manual and the automation solutions were imperfect – the claim was still pending and still being touched for resolution.

Minor edits automation:

Another payer had a claims platform that held claims for minor front-end edits, such as non compliant national provider IDs, age, address, etc.

Now, the claims are dragged into work queues based on their hold codes and robots programmed to automate particular edit changes are assigned to the queues. The robots navigate to the claims system screens; gather the data required to edit the claim; make the edit corrections and resubmit the edited claim back into the claims systems.

Manually processing the edit changes took ten to fifteen minutes, whereas robots can do the tasks in one to two minutes or less.

It also implemented the capability to manage sudden developments in claims volume with more robots, instead of reassigning claims agents to low-value work.

Complex claim adjudication:

A health care insurer was seeing for a further effective way to process coordination of profits claims. The adjudication rules for these claims are complex.

This means the insured’s COB provisions must be understood and their benefits coordinated between plans—in such a way that everything is covered and payment does not exceed the total claim.

The RPA result placed these claims in a work queue for robots to assemble all the required reports and then stored everything in the claims agent’s folder. Using this assembly work away from the agents and permitting them to concentrate exclusively on adjudication decisions, shifted about two hours a day from low-level documentation tasks to high-value claims processing work—for each agent.

UiPath suggests an intuitive, cutting-edge platform that can be effortlessly implemented to boost the efficiency of banking, insurance and healthcare process. With peerless automation abilities and customer support, UiPath is able to change the world by creating opportunities for growth, while improving compliance measures and delivering superior customer service on a worldwide level.

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