RPA Handbook

Robotic Process Automation Handbook – All you need to know

  • Robotic process automation duplicates human execution of repetitive processes with
    existing applications by using software robots which are configured to capture and record
    these applications in order to process transactions, manipulate data, issue responses and
    communicate between different systems
  • As opposed to traditional automation solutions, robotic process automation uses existing UI
  • Robotic process automation is not just technology: there is a clear strategy and steps to be
    followed
  • Intelligent process automation, is the journey towards automation leveraging artificial
    intelligence in the fullest.

Robotic Process Automation and AI

  • While robotic process automation traditionally works more on the back-office level and
    artificial intelligence in making sense of scattered data for the front-office level, the horizon
    for the integration of AI and RPA before moving to intelligent process automation is good
  • Integration is the name of the game all around, and integrated automation is also the next
    logical step in which RPA would become a part of a broader approach and we enter the
    dimension of intelligent automation; with several forms of AI such as machine learning,
    visual recognition and heuristic neural networks adding on to RPA and its ability to combine
    scenarios, increase understanding, and make real-time predictive decisions.

Combining and leveraging RPA and AI: The Benefits

  • Low-risk Non-invasive technology:

    RPA can be deployed on existing systems, which allows for a creation of a platform
    compatible with complex AI algorithms and tools.

  • Accuracy:

    The right result, calculation or decision in the first attempt

  • Consistency:

    Identical tasks and processes, which eliminates variation of outputs.

  • Audit-Trail:

    Fully maintained logs imperative for compliance.

  • Reliability:

    Services provided all through the year.

  • Scalability:

    Spontaneous ramp-ups and downs to match demand highs and lows

  • Right Shoring:

    Geographical liberty without business case impact.

  • Productivity and retention:

    Freed up human resources for higher value-added and more priority tasks.

  • Cross-industry:

    RPA can be used across industries since it follows rules and procedures in use

  • Duration:

    RPA projects run for roughly 9-12 months with a ROI of < 1 year.

Market dynamics of RPA

  • RPA software spending is poised to total at $2.4 billion in 2022.
  • The market is projected to grow at a CAGR of 33.6% from 2020 to 2027.
  • UiPath (13.6%), Automation Anywhere (12.8%) and Blue Prism (8.4%) lead the market with
    their respective market shares. NICE, Pegasystems and Kofax follow the pack with a
    combined market share of about 16.5%.
  • Following is an illustration of industry segmentation of RPA market:

Industry-specific RPA Use Cases

1. Banking

  • Automated Report Generation:

    • Generation of compliance reports for fraudulent transactions in the form of
      suspicious activity reports or SARs is a fairly regular necessity at banks and financial
      institutions. RPA technology, coupled with NLP, can read through these mundane
      compliance documents before extracting the essential information and filing the
      SAR.
  • Customer Onboarding:

    • Customer onboarding in banks is a long and tedious process; usually due to several
      documents requiring manual verification. RPA can make the process much
      streamlined by picking off the data from the KYC documents using the character
      recognition technique (OCR). This obtained data can then be matched against the
      information filled in by the customer in the form.
  • Loan Application Process:

    • The loan application processing has always been considered as a slow and drawnout process. Although the
      banks have automated the process to some extent, RPA
      further accelerates it and brings it down to a record time of 10-15 minutes for
      processing.
  • Changing Loan repayment schedules

  • Know Your Customer – (reduced process backlogs and increased productivity)

    • Whether it is automation of the manual actions or spotting suspicious banking
      transactions, RPA implementation should prove instrumental in terms of saving both
      time and cost/value when compared to traditional solutions.
  • Card activation/restriction

    • One of the long, monotonous and time-consuming processes at banks is credit card
      applications, which typically take many days for validation of customer information
      before approval of the credit card
    • RPA, on the other hand, can help make quick decisions to approve/disapprove the
      application with a rule/process based approach.
  • Online sales

    • AI chatbots can function in a completely automated way, and depending on its
      development complexity, it can solve several kinds of customer issues. Chatbots in
      banking can be targeted to focus on personalization, which allows making to-thepoint recommendations and
      proposals for the clients.
  • Overdraft and collecting marketing consent

  • Trade Execution

  • Invoice Processing

  • Mortgage Processing

    • RPA allows for easy automation of various tasks crucial to the mortgage lending
      process, including initiation of loan, document processing and verification, financial
      analysis and quality assurance. As a result, the loans can be approved much
      quicker, which leads to improved customer satisfaction.
  • General ledger

    • It is mandatory for the banks to keep the general ledger up-to-date with information
      like financial statements, assets, liabilities, expenses and revenue which is used to
      prepare financial statements. With this massive amount of the data from multiple
      systems, it is probable to have errors. RPA could integrate data from multiple legacy
      systems even if the data in the systems is not in the same format. This reduces the
      sheer amount of data to be handled, and time.
  • Avoidance of Revenue Loss and Improvement of Dispute Resolution

    • The automation standardizes business rules and process, reduces client
      complaints, and ensures previously recorded client track-record are available in the
      bank’s system.

Results of RPA adoption in Banking

  • Cost effectiveness – Banks are estimated to save around 25-30% of processing cost.
  • Risk and compliance reporting – RPA in banking helps in generating full audit trails for each
    process, leading to reduced business risk as well as maintenance of high compliance.
  • Zero infrastructure cost – The best benefit of RPA in financial domain is that it does not
    require any significant changes in infrastructure, due to its UI automation capabilities. The
    cost of hardware and maintenance is further reduced in the cloud-based RPA
  • Business growth with legacy data – With RPA implementation, banks and financial services
    industry use legacy as well as new data to plug the gap that exists between processes. This
    kind of initiation and availability of essential data in single system allows banks to create
    faster and better reports for business growth.

2. Finance

  • Financial Review Preparation

    • Connection and automation of data movement from various core banking
      applications for easy consolidation for executive reporting.
    • Cleansing of data for easier formatting between applications—like Adobe or Excel—
      to create readable reports.
  • Account Reconciliation

    • Download sub-account balances into pre-approved formats.
    • Upload transaction data from various sub-systems and various formats
    • Perform data validation, exception research and handling.
    • Create and balance journal entries, noting and fixing discrepancies.
  • Standard Journal Entries

    • Creation of standard monthly journal entries.
    • Enter and manage data into the ERP.
    • Perform validation analytics to ensure precise entries
  • Bank Reconciliation

    • Automation of bank statement, download workflows for individual accounts
    • Create text files and store them in the right folders.
    • Reconcile balance and transactions to core financial sub-systems
    • Create balancing journal entries to resolve discrepancies.
  • Intercompany Reconciliation

    • Check and reconcile balances on inter-company accounts.
    • Conduct basic research and reporting for any exceptions between accounts
    • Create exception files and email reports for review/approval.
  • Accounts Payable Processing

    • Setup and maintenance of processes for payment to different vendors.
    • Creation of workflows for accounts payable approval.
    • Enter data for completion of payment preparation and processing
    • Process payments and mass payment files for sub-system journal entries.
  • Financial Planning and Analysis

    • Connection of pre-population of forecasts by means of historical and market data.
    • Load balances in planning systems to record.
    • Creation of variance reports that show pre-population and actuals.
  • Operational Finance and Accounting

    • Conduction of pricing review approval process to handle multiple variations for customer accounts.
    • Calculation and processing of rebates.
    • Download details of monthly sales data and commission calculations.
    • Creation of files and emails to gain approvals.
    • Post important information to general ledgers and sub-systems.
  • Regulatory Compliance and Reporting

    • Pre-population of annual complex reporting and routing.
    • Capturing and manipulation of data to support auto-generated regulatory reports
    • Creation of an audit trail or reports and get confirmation of receipt.
  • Accounts Receivable Processing

    • Credit approvals and maintenance of a customer master file
    • Routing and processing customer orders.
    • Processing accounts receivable cash receipts.
    • Send late payment notifications

Results of RPA adoption in Finance

  • Simply put, RPA is better, faster and cheaper than human labour at certain things
  • RPA reduces operational costs by replacing the human workforce in mundane, repeatable
    tasks, while also reducing the processing time of those tasks. Cost reduction estimates may
    vary across studies, but 50-70% reductions are not unrealistic and achievable
  • RPA technology is exceedingly precise. Errors from mis-typing or formatting are null and void.
    Unlike humans, an RPA robot performs tasks without a bias or any variation

3. Insurance

  • New Business and Underwriting

    • Underwriting is quite a prolonged process and takes about 3 to 4 weeks on an average
      in the life insurance niche. Since it is such a long process, about 18.5 million people
      do not complete it.
    • RPA can accumulate and process the accurate data automatically and at a much
      faster rate from both internal and external sites. It helps free up about 30% of the
      capacity and it can also ensure accuracy and delivery of work in a timely manner.
    • RPA can be used for to mitigate risks and allow new customers to come, with quicker
      response times.
  • Claims Processing

    • Claims processing is very data and document intensive. A claim process that is
      manual and tedious could lead to trouble for both customer service and operations.
    • RPA helps the insurers in easy gathering of data from various sources to be used at
      the centralized documents so that the claims could be processed at a much faster
      rate.
    • Studies show that the claims can be processed 75% faster with the use of RPA
  • Business and Process Analytics

    • All the processes or workflows which are taken care of by RPA can be tracked and
      recorded at each step.
    • It can be used to provide the insurance company with details like the transactions
      processed, the exceptions encountered etc.
    • This in turn leads to improvement of processes, reduction of workload for people
      and also customer satisfaction.
  • Manual Data Entry Process

    • There are many instances in the insurance industry where data is entered manually
      to the system, for e.g. quotations, insurance claim etc. This is as time-consuming as
      it is expensive.
    • Implementation of RPA can lead to elimination of all inconsistencies and errors in
      data, and can save about $30000 a year in wages alone.
  • Usage of Legacy applications

    • Many firms in the insurance industry heavily rely on legacy applications for handling
      much of their business functions
    • When the new ERP or BPM solutions are implemented, the insurance companies
      always encounter the tough task of integrating them with the legacy applications.
    • The RPA, when implemented can be used with the existing system as they can
      comply with any system that is available.
  • Regulatory compliance

    • The insurance companies rely on many compliance standards, including but not
      exclusive to HIPAA privacy rules, PCI standards, tax laws etc. These standards keep
      changing with time.
    • These compliance standards are followed for protection of business operations but
      the clients and company employees find it particularly hard to stick to them
    • RPA implementations make it really easy to stick to terms of compliance.
  • Policy Cancellation

    • Using RPA allows cancellation of processes to be done in a quarter of the time.
  • Form registration

    • RPA can significantly improve the time required for the form registration process by
      around 40% and with half the number of staff.
  • Policy Admin and Servicing

    • From quoting, rating, underwriting to the distribution of customer services – policy
      administration links all the functions of an insurer. Current policy administration
      systems that have been around for many years now, are expensive and highmaintenance. They can’t scale up
      quick
      enough to meet the growing demands of
      customers or support growth of business.
    • RPA in Insurance allows all the key players within each process to accomplish a
      variety of operations with ease without involving vast navigation across systems. It
      essentially automates transactional and administrative parts of process such as
      accounting, settlements, risk capture, credit control, tax and regulatory
      compliances.
    • A successful RPA implementation can free up around 20-30 percent of capacity at
      an enterprise level while improving customer experience and minimizing operational
      risks.

Results of RPA adoption in Insurance

  • Using RPA, a consultancy firm was able to save 54,000 hours of work annually while
    reaching 85% accuracy improvement.
  • According to Capgemini, there is an average of 50% productivity increase in business units
    where insurers apply RPA.
  • Insurers who have implemented RPA have reported a ROI as high as a whopping 650%.

4. Healthcare

  • Adaptive Staffing

    • The use of automation allows healthcare providers to have a real-time view of the
      care journey for each patient.
    • It can be used for adjustment of staff requirements to support the ever fluctuating
      volume of patients in the emergency department and lower waiting times in
      ambulatory services
    • A bot can also automatically update the patient’s Admission-Discharge-Transfer
      status and simultaneously send out triggers to the staff with minimal human
      intervention.
  • Appointment Scheduling

    • Based on the data provided by the patient, it is extremely difficult to align it with
      doctors’ schedules and availability in hospitals. And in cases of a last-moment
      cancellation, the hospital staff needs to inform patients without fail.
    • This complicated task could be simplified with RPA bots, which could quickly
      automate and process patient data collection methods.
    • These bots can scan abundant data to generate reports that can be sent to staff for
      fixing an appointment. It can also notify the patients about a doctor’s availability.
  • Streamline Claims Management

    • Claims management involves various activities like data input, processing,
      evaluation, and handling of appeals.
    • Ensuring regulatory compliance is another big challenge that could lead to claims
      being denied.
    • Handling of insurance claims can be error-prone and prove ineffective if done
      manually or with off-the-shelf software and could greatly impact cash flow.
    • RPA is required to smoothen out the insurance claims management process. Bots
      can easily monitor the entire process to avoid non-compliance and flag compliancerelated exceptions, thereby
      enhancing efficiency.
  • Enhance Accounts Settlements

    • Accounts settlement can take up a great amount of time of a healthcare
      administrator, who has to evaluate bills during the patient’s diagnosis and treatment
      as well as maintain records of various tests, doctor’s fees, prescriptions, wardroom
      cost, etc.
    • This work can be offloaded to an RPA bot, which can accurately calculate the bill
      amount and notify patients about it
  • Accurate Audit Procedures

    • Auditing is a norm in the healthcare industry as it is necessary for regulatory
      compliance. It involves various tasks for risk assessment and is done for varied
      objectives, including quality of services or patient safety.
    • Generating audit reports manually can be tedious and error-prone since evaluating
      a bunch of reports can lead to oversight, which can ultimately culminate in noncompliance of regulations.
    • Using RPA bots to optimize the audit process can help healthcare facilities generate
      accurate audit reports and ensure full compliance. These bots can collect data and
      generate reports, which can automatically be shared with the respective
      departments for approval.
  • Enhance Healthcare Services

    • Using RPA in healthcare gives an opportunity to easily collect, store and optimize a
      huge volume of data for future analysis.
    • Healthcare providers collect different types of patient data including but not limited
      to- personal information, treatment, medical condition, and diagnosis. To extract all
      this information and add new data manually requires a lot of man hours.
    • When a bot is used instead, such data can be easily recorded and monitored to
      generate reports and identify trends/seasonality. It also enables healthcare
      providers to deliver a precise diagnosis in a short time.
  • Deploy Discharge Instructions

    • Healthcare institutions can use RPA bots to comply with the post-discharge
      guidelines to help out patients exhibiting specific symptoms.
    • These bots not only ensure that the guidelines are followed to the full, but also send
      reminders to patients to pick up their prescriptions.
    • It can also remind them about their upcoming appointments and medical tests, thus
      enhancing the patient’s overall experience, provide better care and lower readmissions.
  • Patient data processing

  • Claims Underwriting and Processing

  • Medical Coding

  • Medical billing and Processing

  • Patient Payment Consolidation

  • Automated Healthcare Workflows

Benefits of RPA in Healthcare

  • Estimates show that health plans spend a collective of $2.1 billion each year on inefficiently
    performed manual tasks – and that figure is only for provider data management (PDM)!
  • Similarly, insurers spend $6 million – $24 million per year to make up for poor data quality
  • These numbers do not account for fines attribute to failed regulatory requirements.
  • RPA in healthcare complements the existing systems, workflows, processes, and
    procedures. Through automation, it restructures lousy workflows and inferior methods of
    execution. Once that is achieved, user services also improve, which leads to an increase in
    customer satisfaction levels.

5. Manufacturing

  • Bill of Materials

    • Bill of Materials (BOM) is a wide list of raw materials, components, sub-components
      and other products for the new product creation.
    • Employees in the manufacturing industry should ideally refer to the document to get
      detailed information to get an idea of where to purchase, what to purchase, when to
      purchase and how to purchase.
    • By using the RPA in this section, the companies can create the product much faster
      with better data accuracy, and the product creation could be completed on time.
  • Logistics Data Automation

    • While integrating RPA Transport management system, we can monitor the
      transportation of products in an efficient manner. It will reduce the human errors.
    • When a company has multiple carriers and multiple insurances, the RPA will give
      the report of which choice is giving the best value in terms of cost, insurance and
      transit time.
    • Real time freight tracking option could be included with RPA in the Transport
      Management System, which would give an enhanced report to the customer about
      product arrival.
  • ERP Automation

    • The integration of RPA in ERP could be the next stage in planning resources. The
      reports, like inventory, Accounts Payable and Receivable, Pricing and other reports
      are automatically generated and can be automated.
    • A manufacturing industry can monitor the current/existing inventory and notify when
      the stock is low. Then it could be automated to reorder again. They can also mass
      update the SKU automatically.
  • Web integrated RPA

    • A long-standing company might have multiple branches of factories and offices. It
      might be harder to manipulate the data in the particular system.
    • While deploying RPA in this area, a manufacturing industry can monitor, access and
      update any changes in the web-connected systems with ease. This reduces the
      communication time between one area of the branch to another.
  • Purchase Order Creation

    • The manual process for purchase order creation can be daunting for midsize to large
      organizations dealing with several categories of products.
    • With the help of RPA solutions, the entire process of PO creation can be automated
      enabling completely accurate and speedy results.
    • The process is automated based on a rule-based workflow that takes care of
      extraction of data from independent systems, seeking email approval from
      concerned departmental heads and processing the request of PO generation.
  • Inventory management

    • The process of inventory control is of vital importance and lies at the core of the
      supply chain management. Real-time monitoring of inventory levels is required to
      ensure that demand can be met.
    • RPA helps in automating various functions such as monitoring inventory, generating
      notifications about the levels of stock, and reordering products when the levels go
      below a pre-set threshold. This can be done with minimal human intervention.
    • As an added bonus, implementation of RPA automatically results in the creation of
      a detailed audit trail. Live dashboards and reports also provide information about
      business patterns and internal workings that could highlight potential bottlenecks.
  • Vendor communication

    • In the manufacturing industry, the daily communication between vendors,
      customers, and internal workforce requires a huge amount of manual effort.
    • RPA, however, can take over the entire process, starting by opening the email,
      reading the text, downloading the attachments if required, logging into the ERP
      portal, determining the status of the shipment, replying to the customer, and moving
      on to the next customer email.
    • Such automation can eliminate up to 65% of the manual effort, enabling employees
      to resolve more customer queries in lesser time.

6. Telecom

  • Order Entry

    • Recording the service parameters that are sold to the customers precisely
  • Order Management

    • Each order is broken into sub-components (fiber/CPE; voice/internet/security) and
      processed/tracked simultaneously.
  • Contract Management

    • Contracts are digitized/stored in the system.
  • Supply Chain/Procurement

    • Creation of eCatalogue and enabling eAuction.
  • Service Delivery

    • Beginning with activation to test and acceptance, inventory and capacity
      management.
  • Operations/Service Assurance

    • From service desk, auto-ticketing to self-healing.
  • Billing/Revenue reconciliation

    • Ensuring alignment of service commitment to bills generated.
  • Ability to scale operations

    • Without incurring additional costs, RPA can be deployed to several similar tasks
      and get benefit. By handing over manual work to software robots, telecom service
      providers can scale better to different market scenarios.
  • Cost reduction

    • Implementation of new technology for business demands would increase investment. But the implementation
      cost of RPA is less when compared to ERP or BPM software. The software license of RPA can be re-used for
      multiple processes within the organization. Finding similar tasks and implementing automation can reduce
      cost and increase ROI.
  • Accelerate efficient data flow

    • RPA can process information from various sources and process it with efficiency.
    • RPA is non-invasive which can easily go along with the existing setup. When
      combined with data analytics, the best business benefits can be obtained.
      Extracting required data and sharing is done with precision and efficiency.
  • Periodic report preparation and dissemination

    • Upon generation, the bot can also analyze the content of the report. Based on the
      provided criterion, it can decide who the report is relevant to, and email it to them.
      Thus, the information flows more efficiently.
  • Responding to partner queries

    • Software robots are smart enough to interpret emails, issue responses to simple
      questions, and forward complex ones to humans. This is particularly useful for
      telecom companies, which generally rely on partners like independent brokers to
      sell their services.
  • Reducing manual sales order processing effort

    • RPA technology can analyze the business process tasks performed by the
      employees of a telecom company. Based on employees’ actions, a structured
      workflow can be generated, which serves as the infrastructure for automated
      processes.
    • By mapping each process step with its respective cost for manual execution, it is
      fairly easy to pinpoint the automation of which steps would lead to highest ROI.
    • This application area is a good example of RPA helping in managing large,
      unstructured datasets.
  • Competitor price tracking

    • The transparency of online pricing is a strong motivator for tracking competitors’
      prices, especially in the case of e-Commerce. And since e-Commerce is becoming
      the norm in telecom, careful price monitoring is an extremly valuable asset.
    • Automation, with its zero errors and 24/7 capacity to work, can provide a telecom
      company with the most detailed kind of comparative price analysis. Moreover,
      software robots can do the tracking at individual, category and brand level, which
      can offer better and deeper understanding of the market.
  • Backing up information from clients’ IP systems

    • Software robots can chain up several technical tasks, creating coherent backup
      systems. Their scope of use is as broad as the scope of telephonic systems, since
      backups can be done independent of the client’s specific system.
    • The bots can obtain data from the databases of all IPT devices on a client system,
      and upload them onto an FTP server. Refreshes can be scheduled according to the
      client’s needs.

7. Retail

  • Sales analytics

    • Comprehensive analysis of large amounts of sales data is fundamental for analysis
      of marketing and consumer behaviour. It is a necessary condition for a wide range
      of retail decisions.
    • Automated analytics provides easy access to in-depth reports providing real-time
      insights of customers’ behaviour and corresponding customer preferences.
    • Hence, it is a very useful tool for discerning the parameters that affect clients’
      dropping out of services, which allows timely deployment of required actions for
      retention.
    • Moreover, future-oriented analysis allows precise sales forecasting, which is a
      supporting rock of stock optimisation.
  • Demand and supply planning

    • The integrative nature of RPA allows to streamline data gathering, formatting, and
      standardisation, plan simulations, exception finding, etc.
    • This leads to improved capacity and assets management, and subsequently,
      boosts productivity.
  • Store planning

    • RPA in retail brings in the ability to make use of fine-grained data to create storespecific merchandise
      disposal, optimally fit with what customers’ desire most.
    • The upshot is a personalised shopping experience, which promises to boost
      expenditures, which ultimately results in increasing profit.
  • Marketing planning

    • Data collection and analysis are mandatory prerequisites of positive and fruitbearing trade promotions.
      Software robots can do this much faster and more precisely than human employees entering data in
      spreadsheets ever could.
    • Automation of rebate processes is basically a tool to increase price effectiveness by eliminating all
      variable costs.
  • Launching new products

    • The more streamlined the communication between R&D, manufacturing, and
      marketing departments, the more efficient and impactful the introduction of new
      products.
    • As an epitome of integrative capacity, robotic process automation allows retailers
      to change pricing, production and stocks in close sync with customers’
      preferences.
  • Product categorisation

    • A crucial task when it comes to product categorisation in MNC’s is to achieve a
      certain degree of correspondence between local and global stock keeping units
      (SKUs).
    • Given significant variation of culture, it is likely that products across different
      markets have different definitions and constituents, and require different
      marketing campaigns/strategies.
    • Software robots can easily (i.e., quickly and error-free) process data from retailers
      and vendors in various data formats such as texts, images, etc., in order to match
      the local datasets to global standards.
    • According to a report, automation can lead to 98.5% accuracy in product
      categorisation.
  • Customer support management

    • In order to stay consistent with the boost of customer-centric retailing, the
      provision of 24×7 customer support is an integral part of competitive retailing.
    • RPA is the ideal technological development to rely on, because customer records
      can be easily managed across multiple systems by synchronising CRM information.
      This also allows convenient customer on-boarding from websites, preparing data
      for subscription renewals, as well as timely complaint/query management.
  • Delivery tracking

    • With the use of software robots, orders can be tracked easily, and real time
      shipment updates can be delivered to clients.
    • This way, clients just don’t have to take any time out of the customer portal,
      because bots can gather order-related information from external sources and
      deliver it right there.
    • Once this is done, they can also collect customers’ feedback, which is a
      tremendous resource for subsequent retailing decisions, to be dealt with by onpoint analytics.
  • Order and invoicing

    • Use of optical character recognition (OCR), and the capacity to deal with various
      data formats, e.g., Word, Excel, email, allows automated import of orders and
      invoices into the retail company’s ERP. Both suppliers and customers can benefit
      from prompt delivery.
  • Automated checkout

    • With the help of RPA, retail companies might help its customers escape hassle by
      automating the checkout, improving the customer satisfaction levels in the
      process.