About the Customer
The customer is one of the leading international freight forwarding companies, offering a multitude of services to meet customer’s business needs. They have a customer base over 30 countries around the world, who rely on their expertise to manage the day-to-day logistic needs. They believe in delivering logistics services on time and cost effectively. That’s why customers in over 30 countries around the world rely on their expertise to manage their day to day logistic needs.
About the process
Dubaitrade is a government website. Each freight forwarder has to update the details of each shipment whether they be import or export and make the payment accordingly. Even a slight mistake will cause heavy financial penalties to the freight forwarder. Hence accurate detailing is very essential.
Challenge:
Increased Employee Expense: More than 2000 invoices and supporting documents are received per month for freight forwarding. Skilled resources time are wasted on manually extracting data from each document and updating Dubaitrade website (govt owned) and making the payments. Each document follows a different format. Company incurs increased recruiting and training expense every month since employees are constantly moving out after 3-4 months after they learn the operation.
Solution:
Using RPA, Alzone designed a solution where the bot extracts the data from the documents. The bot has been trained for each invoice format and it functions 24×7 without any hiccups. The employees’ role comes only if the bot encounters any discrepancy in the current invoice or for any new invoice.
Impact:
The number of employees to be maintained reduced to 3 from 15 which resulted in an annual savings of $65K
Automobile dealerships has shown great signs of improvements and technology upgrade recent times by adopting newest technologies in the market. The OEM provided DMS had severe complexities like delivering real time business critical data, frequent price changes, applicable tax differences, new part additions, part number changes etc and was not provisioned for dealerships to generate the data on a single sheet. Dealerships had an internal ERP application separately to track this data and deployed huge manpower in all multiple locations to update the same manually in ERP which has the below mentioned business challenges.
Alzone digitalized the entire operations by deploying MIS BoT and allowed for real-time monitoring of Stock Maintenance, generation of MIS reports featuring Parts Sales, DSR with revenue details, accurate tax calculations as per prevailing rules. This helped the business to enhance smooth running of business operations, effective utilization of resources increasing operational efficiency and maintaining business critical necessities which resulted in :
Our client is one of the largest energy company who are into production and exploration of oil and energy and suppliers around the world.
Business Challenge
Being a whole time energy company they are into production and distribution of energy supplies around the globe. Most of their clients are spread across the world the payment realization is done through transfers and in destination currencies as well. For realization they deal with almost 20 bank accounts and most of the back activities are done manually as well. They receive 20 emails per day with cash realization and expense reports. Manual labourers are deployed to read the mail and download the statement and are assigned to do matching and reconciliation tasks manually. Theses tasks includes :
These activities take 6 hours day and has manual entry errors and missing entries as well. As a part of Digital Transformation Journey, Our client has decided to automate the Bank Account – Counter Transfer process.
Solution
Alzone’s RPA team has done a detail discovery of the process and developed a BoT to do the Bank Account Transfer Process. The developed BoT read the emails and downloads the statements send by the finance team. The BoT will then log into the ERP system using necessary credentials. The BoT will extract the data from excel sheet using counter transfer as the key word and validates using account number, date, amount and transaction id. Then the Bot will search for the similar transaction details in received accountusing the same credentials and matches the records. Thus matched records will be updated in the ERP – Bank transfer successfully by the BoT without errors and in less than 10 minutes per day.
The client is an upstream Oil and Gas company who is an active explorer, driller, Producer, Refiner and Distributor for petroleum products in India market.
Business Challenge
Being a pioneer among in Oil and Gas industries, they have large machineries used in the plants, explorations fields and refineries as well. These machines are sold and serviced by multiple vendors at different refineries. These machines requires repairs, parts replacements and annual maintenance frequently. Also for each parts of the machinery they have different service vendors. So the refinery receives almost 500 multiple formats of drawings from those service vendors with their details. These records has to be maintained at the refinery for any service purposes. Currently almost 20 people has been deployed to scan and update these documents within their internal COMOS application. They have to process almost 500 documents on a daily basis. As a result the current process cycle they had backlogs and the associated manual activities resulted in data entry errors, excess time consumption for data reading and manual entries as well.
Solution
We Alzone Software, got engaged and we automated the entire Data creation and SAP upload of engineering drawing using Intelligent RPA Automation and advanced OCR Technology. We designed and created Attended RPA BoTs for Real Time automations. Once the document is scanned and saved into the system, our advanced OCR technology will read and extracts the relevant data from scanned sheet and saves it into a folder. The our validation BoT will read the data and validates for errors if any and process the sheet for final upload. Then our System BoT will read the validated data and uploads the same within COMOS application.
An US based company that provides network-enabled services for healthcare and point-of-care mobile, has a network of more than 160,000 providers and 110 million patients and offers a suite of services to manage medical records, revenue cycle, patient engagement, care coordination, and population health. Currently operations are handled by human and is going to be fully automated and to be handled by automation.
To tackle this challenge an AA RPA digital bot was designed with an WLM (Workload Management) which will divide your automations into small, yet logical work items and process them simultaneously to ensure that time-based Service Level Agreements (SLAs) are met with optimum resource utilization. They are having lakhs of patient details in excel format which are processed manually. Workload Management (WLM) allows the manual prioritization of high-value transactions inside the automated queue management model.
A hospital network wants to improve their customer relationship management process as a key strategy to increase their business volume. As part of the strategic plan, in order to meet the increased volume of customers with desired customer satisfaction, they decided to decouple the customer engagement activities with various departments such as appointments, front office, billing and payments, pharmacy etc. They realized that their present Hospital Information Management System (HIMS) is a bottle neck to meet the organization goal due to its limitations. Upgrading the legacy HIMS system, to cater the present need is an impossible task as there is no sufficient technical documents present to scale the HIMS system and also no OEM support is available.
Implementing an RPA solution which provides seamless data integration between CRM and HIMS systems without impacting the current operations activities was the best way of overcoming the challenge. The solution consists, a group of attended and unattended bots which handle the data need of both CRM and HIMS in a synchronize and asynchronies mode based on the business nature.
The external transactions happening in an automobile dealer management system is as tedious challenge as the sale of a vehicle. The process mainly includes the following:
Once a vehicle is chosen by the customer, then the process of other external transactions starts. But when is done manually, it becomes a very complex process.
An RPA bot was deployed to solve the situation. The bot will make data entry for the insurance and extracts the policy from the insurance company. Then if the customer has requested for some extended warranty the bot will process it and move on to registration (title) and tagging process. Once all these external transactions are done bot notifies the dealer along with required documents to be downloaded.
The dealer management system in the process of automobile sales includes the following steps:
In this whole process two ERP systems are involved, the dealer level and the manufacturer level ERP systems. The data extraction from the dealer ERP system to the manufacturer ERP system and vice versa happens in many occasions like on vehicle registration, accessories requirement request raising etc.
The main challenges faced in this process are:
An RPA bot was designed and trained to overcome these tedious tasks with less human intervention and without much of a time delay. The bot does the data extraction from the one ERP system to the other whenever it is required.
What makes E-way bill generation a difficult process is the possibility of data entry errors, delay in issuance and providing the state specific credentials each time. The process involves logging in and fetching invoices from the company in-house portal, then extracting the required data and finally uploading it into the government E-way bill portal to generate the corresponding E-way bill. On a daily basis when the task is done manually the process could take hours to generate E-way bills for a batch of files causing unproductive use of resources, when they could be allocated for productive work rather than for such mundane tasks.
To solve this challenge an attended bot was deployed with the assigned tasks of:
Our client is a global technology company which operates in the information technology product distribution business, supply chain solutions and after sales services of information technology products.
Business Challenge
Being a whole time partner for IT product companies, our client is enabled to distribute and provision the IT Product assigned to their region. Our client receives almost 100 Webex customer orders per day from multiple e-commerce applications and need to provision these Webex licenses at the earliest for successful activation. Usually these licenses are valid for a period of one year from the date of activation and provisioning. They do have some credentials which is of alpha numeric code which has to be read and updated manually. Our client has a team of people together to do this function which often results in human errors, not meet with demand and supply requirements which resulted in cancellation and revenue loss as well.
Solution
As a part of Automation Journey, We Alzone Software are assigned to continue with this process for automation as well. Alzone’s Engineers done a detailed process discovery and arrived at a better solution for Webex license Provisioning. We have designed and developed a License provisioning BoT for license validation & provisioning purpose. The BoT will download the data from our client portal in an excel sheet. The BoT will read the data and using the credentials will log into the CISCO WebEx portal. Then the BoT will update the data against the end user details by updating their necessary credentials and will update all the information for successful activation
A leading FMCG company implemented RPA solutions in automating the business and sales related reports. There are different types of reports are generated by business people, that are weekly /monthly /quarterly/yearly reports for business analysis. The process involved in extracting input data from different resources (SAP, database, website(oracle cloud ERP system), Excels) and doing different data operations like data validation, reconciliation, and data manipulation as per the requirement of different level business perspective. After that sharing a proper report to the corresponding business persons of different region or sharing the report to the corresponding resources for the backup. There are many employees working to generate these repetitive reports.
A RPA bot was deployed to solve this repetitive report generation problems. The bot will read and understand various inputs from various sources in different formats like spreadsheets SAP Data, applications and/or websites. After collecting the relevant data based on some conditions and formulas, bot performs data massaging to come up with the required data. Finally the required output files will be generated from the collected data and will be shared to the business. This solution perfectly generates the report on a timely manner and without any manual influences.
The tedious challenges faced during the punching of orders on to the system are its massive volume and the complexities involved. Once the purchase orders of different PDF formats are received, it has to be read and entered to the ERP system for order generation, which usually takes about two weeks to complete. It takes place by converting the PDFs to a standard CXML format to upload it to the business system. Following that a series of validation steps are conducted and finally the orders are punched on to the system. But when a RPA bot is introduced to automate the process of reading PDF purchase orders of different formats using OCR system, the task is completed in a single day. It make use of the Python based AI crafted algorithm to read various formats of OCR outputs. When the bot manages the overall order punching, the processing time is reduced to 20 minutes.
Bot also handle third party business-to-business systems like Ariba and Coupa, sometimes it results in punching of order failure. The failure could happen due to the complex and strict validations and authentications involved. As a result the task to re-punch it manually by identifying and rectifying the error increases the complexity of the process. But the automation solution ensures the successful re-punching of erroneous orders by self identification and rectification of the cause.
The challenge was the delay in invoice generation against the purchase enquiries submitted by the customers. This happens because the customers can send these purchase enquiries in any file format such as PDFs, Excel, Word, HTML etc. The file send also shouldn’t have any standardized formats for making the extraction of purchase enquiries details because each customer has different formats. The Oracle ERP system with the punching team enters the extracted data in to the ERP enquiry registration and a corresponding Excel sheet is being downloaded. Some macros are being run at this time and it is passed on to the ODOO ERP system to generate the invoice and finally these invoices have to be send to the corresponding customers. To manually perform these tasks it takes a substantial amount of time.
To solve this challenge, a cognitive RPA solution was designed, by which the bot will fetch data from the purchase enquiries that comes in multiple formats by making use of machine learning and NLP techniques. The punching of data into the Excel file and running some macros are also done by the bot. Once the data is extracted the bot passes it on to the ODOO ERP system for generation of performa invoices for each purchase order. On generation of these performa invoices the bot itself will be sending it to the corresponding customers. Thus invoices for purchase orders can be sent on a timely manner, without much of human interventions.
Our client is one of the leading revenue cycle management and medical credentialing verification processes company in India having their headquarters in US. They improved the internal billing efficiencies for about 80 customers by deploying robots to manage the Charge Entry process. This created staff efficiencies and reduces the error rate due to human data entry which led to 100% claim settlement.
Business Challenge
They need to process thousands of scanned records/ excel sheets per day from multiple clients to post charge entries into several Billing Application systems. For which they have to identify, verify data using CPT Codes and subsequent DX codes before posting charge entries in respective applications. While performing charge entry posting process using Current Procedural Terminology codes and medical codes, they have to consider a set of Customer specific rules to consider priorities on hierarchy. Currently all these data validation processes like identifying, verifying and posting charge entries are done manually and almost 40+ people are deployed to do this activities. The major business challenges include:
Alzone deployed 10 Human collaboration CPT BoT’s instead of Coders/billers to address the above said major business challenges. The CPT BoT’s understanding the CPT codes and subsequent medical codes will review the superbill and entered procedures. The BoT’s then considering customer specific rules verifies the data and post charge entries in subsequent Billing Applications.
Business Highlights:
Financial institutions perform reconciliation of their GST transactions to ensure that the data filed by the suppliers match with those of the recipients and there are no missing or wrongly reported sales or purchases in the GST returns. The reconciliation process is complex, as it must keep track of every discrepancy or mismatches between the book of business and the GST system. It takes a lot of human effort but still results with calculation errors, data entry mistakes and unidentified of transactions. This ultimately ends up with auditing and accounting issues as well as financial loss.
Some of the common reasons for mismatches of tax entries are:
An unattended bot is designed to trigger automatically at defined intervals to do the entire reconciliation process without any human intervention. The bot will first identify the transactions based on the GSTIN numbers provided by the supplier and match them based on invoice number, invoice date and CGST/SGST/IGST tax amounts corresponding to each tax brackets. Bot identifies the fully matching transactions as well as partially matching and unmatched transactions with reasons or pointers for corrections. Issues in the book of business and the errors from the supplier end are clearly classified for the accountant to make necessary corrective steps.
A letter of credit (LC) or letter of undertaking (LoU) is the payment mechanism used in international trade to provide an economic guarantee from a creditworthy bank to an exporter of goods. It is extensively used in the financing of international trade, where the reliability of contracting parties cannot be determined easily. So a bank will be introduced as a guarantor, where it assumes the counterparty risk of the buyer paying the seller for goods. Document scrutiny is the most important step in the process where all the supporting documents undergo verifications which results in the following challenges when performed manually:
The solution was to automate the process using a cognitive RPA bot with advanced OCR technology in place. Bot will extract necessary information from LC and cross check with the supporting documents based on the master rule book. The bot is trained to read the additional rules mentioned in the LC in natural language and run corresponding algorithms by applying the necessary conversions to complete the validations.
Trade finance issuance is a tedious banking process with sequence of steps involved. This process includes:
Unattended RPA robot can simplify the complexity of this process. The bot will be scheduled to start every day at a predefined frequency. The bot does data entry to the Finacle core banking system and updating of the daily excel register with LC and BG details.
Once the TFCPC user verification is successful, the bot changes the status authorization and the message about successful authorization of LC is transmitted to SFMS or SWIFT. Then the bot will login to SFMS and shares the soft copy of LC or BG to branches through email. Bot is capable to cater both inland and foreign LC and BG issuances.
Our client is a global technology company which operates in the information technology product distribution business, supply chain solutions and after sales services of information technology products.
Business Challenge
Being a whole time partner for IT product companies, our client is enabled to distribute and provision the IT Product assigned to their region. Our client receives almost 100 customer orders for CISO Webex per day from multiple e-commerce applications. As per the current scenario, to process these orders many a people has been allocated to read this mail and download the reports initially. Then they have to log into the product company portal to update the order one by one for these 100 Webex orders. Also pricing and product packaging will be different as per the customer requests. The concerned team has to manually update the data which as data entry errors, value errors and also this action will create backlogs for product delivery and license provision as well.
Solution
Alzone’s Engineers done a detailed process discovery and Business Process Standardization for Online Order Processing. Our team first decided to automate the Online order processing by way of RPA Un attended automation. Here Alzone developed an Order processing BoT will log into our client application and downloads the customer orders in an excel sheet. This BoT will read the data and then logs into the IT Product portal using credentials and updates the same for Order creation for those which are on payment completed status. Once the order is created the BoT will update the product type and price using the captured data from excel sheet. The Bot then confirm the order by updating the end customer details and reseller details as well. Thus the BoT will process the online order and this way for almost 1500 orders per day.
A leading airlines shared customer service company was looking out for an attended RPA solution, which can assist customer service representatives to pull PNR information and related policies of their customer’s ticket when dealing with cancellation, rescheduling etc. operations from different system such as ODEGOE, Amadeus and tax systems.
To submit a solution for assisting customer care agents when dealing with fare calculation policies. An automation especially with AI driven attended robot was deployed which will understand policies written on the ticket and translates to respective mathematical formula to calculate applicable fare.
Main challenges faced are:
An integrated banking group based out of Saudi Arabia, also having branches across different regions has been looking for digital transformation. As part of their digital transformation journey, they collaborated with Alzone for automating some of their time consuming and repetitive financial tasks. Alzone had automated the ATM Setup Process, by implementing RPA technologies for processing setup request of 700 to 800 ATM outlets for the client. The setup of an ATM involves several steps to ensure its proper installation, configuration, and integration into the banking or financial system.
Integrating an ATM (Automated Teller Machine) with a banking system can present various challenges due to the complexity of the financial ecosystem, security considerations, and the need for seamless communication.
Here are some common challenges associated with ATM integration:
Automating the integration of 1000 ATMs with the banking system can offer numerous benefits, improving efficiency, security, and overall operational effectiveness. Here are some key advantages:
Some of the substantial impact in automating the ATM setup processes are
Business intelligence and analytics are extremely connected and interlaced in their approach towards resolving business issues and providing insights on past and present data, and defining future decisions. While some experts try to underline that business analytics focuses, also, on predictive modelling and advanced statistics to evaluate what will happen in the future, BI is more focused on the present moment of data, making the decision (and future of a company) based on current insights.
Alzone business analytics solutions provide insights for all departments of a company, providing immediate access to strategic information from organizations of any size or segment.
Data analytics helps businesses convert their historical and real-time, traditional and big data into actionable insights. Alzone has been offering companies a comprehensive kit of data analytics services to improve their decision-making process and win the competition.
Customized analytical solutions we design and implement allow our customers to achieve up to:
An integrated banking group based out of Saudi Arabia, also having branches across different regions has been looking for digital transformation. As part of their digital transformation journey, they collaborated with Alzone for automating some of their time consuming and repetitive financial tasks. Alzone had automated their Financial Position Validation process
Financial position validation is a crucial aspect in banking for several reasons:
Some of the challenges are
Automating the financial validation process in banking and financial institutions can offer numerous benefits, including:
Some of the significant impacts of automating the financial validation are,
An internationally acknowledged biotechnology company, which is India’s largest stem cell bank with accreditations from WHO, FDA NABL and many more. There are 6 sub-brands owned by them for the preservation of stem cells, Placental Tissues, DNA etc., They have a pan-India presence with 200+ centers with footprints in GCC nations.
Business Challenge
The primary challenge faced by the financial department of the company was updating their internal finance system MS Dynamics with bank transactions and the controlled accounts details hence to perform the reconciliation on time. The large number of transactions having various rules made the system more complicated and error prone. There are 14 banks and 9 controlled accounts involved in the day-to-day financial transactions.
The reconciliation process are mainly divided into such as Bank Statement Mirroring and Bank Statement Reconciliation.
In Bank Statement Mirroring, the statement received from 14 Banks are mirrored after applying a set of validation rules. Thus created Mirror Statement is uploaded to the ERP system.
In Bank Statement Reconciliation, the collection and realization reports received from the 9 bank control accounts are reconciled against the Mirror Statement created for the main bank accounts in the ERP system. To complete this reconciliation, the following activities are being performed;
(a) Deposit slip creation & upload
(b) Banking statement creation & upload
(c) Validation & Posting to ERP
(d) Unique ID & transaction ID identification from Mirror Statement
(e) Realization statement creation & upload
(f) Validation & Posting to ERP
(g) Reconciliation using ERP
Solution
Using Robotic Process Automation (RPA) , Alzone has derived an end to end Bank statement Mirroring & Reconciliation, with zero human intervention. Individual RPA BOTs were deployed to perform the statement mirroring and reconciliation activities on a daily basis as per the schedule.
In Mirroring process the BOT performs the following activities;
(1) Identification of the valid emails and downloading the bank statements attached
(2) Mirror statement creation using a pre-defined ERP accepted template
(3) Validating the mirror statement created for data correctness
(4) Uploading to the ERP
Activities performed by the BOT in Bank statement Reconciliation process are;
1. The collection/Realization reports are downloaded from email/TPA websites
2. Deposit slip creation & upload
3. Banking statement creation & upload
4. Validation against Mirror Statement
5. Realization statement creation & upload
6. Validation & Posting to ERP
An aviation and aerospace component manufacturing company, which is a new industry champion focuses on the long-term growth in the global aerospace and industrial sectors. They are a leading provider of aircraft engine Maintenance, Repair and Overhaul (MRO) solutions and have been leading the way in engineering excellence and innovation for more than three decades. Invoice processing for an aircraft maintenance company involves the handling and management of invoices related to the services, parts, and maintenance activities performed on aircraft. This process is crucial for the financial and operational efficiency of the company. The key aspects of invoice processing are receipt of invoices, verification and approval, matching with purchase orders and contracts, coding and data entry, discrepancy resolution, payment processing, record keeping and compliance and reporting.
Challenge:
Increased operational expense: Each supplier will be having their own invoice format. To extract details from those invoices, a separate team was maintained who manually reads and enters the details from the invoices. When business volume surges, the number of invoices increases which was creating stress on this team. So, team size has to be increased. Unintentional data entry errors starting coming up and the invoice has to be processed again. This whole process was becoming a big expense for the firm who was looking for a way to reduce it.
Solution: Using Robotic Process Automation (RPA), Alzone has derived an end-to-end solution for invoice processing of flight engine repairs and maintenance. In the first phase, the set of invoices for training was selected based on the volume of transactions and a consolidated invoice data sheet with the track of all the financial workings is shared with the business for their review and feedback. In the second phase, the bot picks up the confirmed invoice data sheet and converts it into the invoices. These invoices are shared with the respective customer via email/designated websites in the last phase of the bot process. This way, only the invoices which was not trained was handled by the team. This helped the firm reduce the team size and save the cost.
Impact: The impact of automating invoice processing is,
Bank reconciliation is a process of reviewing all the AP and AR transactions between the core financial systems and banking accounts for a specific period, it is a useful financial internal auditing tool to ensure accuracy and to avoid fraudulent or missing transactions.
A leading NBFC from India who is associated with 40 different banks for its massive daily transactions was facing the challenge of periodical bank reconciliation. The account statements were taken periodically for the review, but these statement formats varies from bank to bank. Using the statements, respective closing balance sheet and the statement sheet were prepared and uploaded to an ORACLE fusion built ERP system called ORION. Followed by the four different types of reconciliations were performed:
Only when all these comparison gets successful, the process gets completed. Any mismatches were manually reconciled, which increased the process complexity.
To tackle the situation an unattended bot was deployed. Now the bot will do statement extractions and its conversions irrespective of their formats to the closing balance sheet and the statement sheet. It does the required validations without any human interventions. Then the bot will log on to the ORION financial systems, and upload the sheets under the specified menus. Then the tedious work of four type matching process and reconciliation is done by the bot in minutes.
We have a strong pool of talented and experienced engineers of various roles eager to take up challenging assignments. Our professional services include discovering, developing, implementing and training robotic solutions to our clients and partners. Together with our extensive multi-domain expertise, standards and methodologies that we follow, we ensure our deliverables with highest quality, robustness, scalability and maintainability. We accelerate the automation journey of our clients by reducing the TCO and achieving higher ROI and faster time-to-market.
Some of our delivery advantages are:
Alzone’s RPA maintenance and support services follows an industry standard framework with phased stages for transition, stabilization, and services delivery.
These phases are powered and supported by our exhaustive program management and service enablers to ensure risk free, continuous delivery of high-quality services that consistently meet all service levels (SLAs) and at the same time provides business value contributions with structured innovation and continuous optimizations and improvements.
Alzone has designed an Intelligent RPA the way you think. A revolutionary feat of software technology set to become a core component of all modern software over the coming years and decades. RPA enabled Artificial intelligence (AI) emphasizes the creation of intelligent machines that work and react like human workforce.
An Integrated Robotic Process Automation platform which comes bundled with key essential technologies like Artificial Intelligence, Machine Learning, and Natural Language Processing for front office, middle office, back office and IT operations automation. It helps in reducing cost, improve response time, grow business and achieve compliance. Ready bots and development environment are available to build new bots.
Alzone has derived a matured cognitive automation model that makes RPA even better. Firstly, cognitive RPA can be used to improve data. Natural language processing and text analytics, transforms unstructured data into structured data. Then, an RPA system use this data in automated processes. Secondly, cognitive automation can be used to make automated decisions. Predictive analytics can enable a robot to make judgment calls based on the situations that present themselves.
Finally, a cognitive ability called machine learning can enable the system to learn, expand capabilities, and continually improve certain aspects of its functionality on its own. So, to sum up, the power of cognitive RPA comes from its ability to process unstructured data, such as documents and emails, and then use that data to drive higher levels of automation
A leading ISP was encountering issues in inward Internet service order processing request. The ordering process involves complex approval processes and processes in various environments such as web, desktop, ERPs and citrix environments. The process is susceptible to fallouts, hence each individual request may not get completed on time. Not only the fallouts but the enormous number of requests flooding in, that are yet to be handled on time, makes this process complex, stressful and large resource crunching task. This created lower customer satisfaction .
To tackle these issues a state of the art RPA solution was deployed whereby the bots monitor email inboxes for requests and reads every incoming request in various formats(PDF, Email, HTML, Word, etc) containing purchase enquiries.
The bots then login to the an ODOO ERP system to create a lead and later convert it to opportunity. The bot then login an Oracle ERP system and register an enquiry in registry record. It updates customer information and services and generates pricing details, which are the downloaded. Bot performs excel operations to validate this downloaded sheet and obtain the final sheet to upload to the ODOO ERP and finally a performa invoice is generated and an email is sent to the customer. Ensuring quick and efficient request handling and processing.
RPA (Robotic Process Automation) is a software virtual workforce to perform repetitive tasks that are currently being done by humans. The bots emulate the activities using the existing platforms and applications that a company is currently using.
To sum things up, here’s what a RPA software can do for you:
Perform repetitive, structured transactions processes
Scale up operations and processes rapidly in your company
Interact with and update multiple applications in a transactional manner to keep everything in sync
Validate data in places that are complex for people to understand
Perform calculations faster than humans
Robotic Process Automation (RPA) for Profit & Loss (PnL) calculations are quickly evolving as the most efficient process automation systems with extremely small value realisation time for finance companies.
The cost of implementing RPA are significantly lesser than building a custom solution to eliminate human tasks that can be error prone.
An internet service provider was facing the cumbersome issue of poor FCR( First- call Resolution) rates. The main culprits for such poor FCR rates were data inaccuracy in data entered by customer relationship agent, the cumbersome ordeal of interacting with multiple systems real time while on the call. Processing each and every request from customer requires a series of steps involving data entry and validation across ERP, CRM and internal/external systems leading to inaccuracies, validation errors, poor FCR rates and an unhappy customer.
Solution to this challenging problem was to deploy an attended bot, equipped with all the validation and processing rules, at every agents’ system. During every call the bot retrieves every information about the customer and all the possible information to assist the customer. The bot waits for the agent to click or type-in the request, upon which the rest of the processing, transactions, validations and the final conformation on the requests are solely done by the bot. Thereby ensuring timely completion of requests with accuracy, efficiency and above all a happy customer.
The RPA strategies have been successfully implemented on one of the global companies, engaged in oil and natural gas production and excavation, in automating their Maintenance Communication Process. The maintenance works on their production site were conducted as per request from the workers. These requests were then conveyed to an Analyst who fetches the related diagram from the database to identify the rectification points. The proposal and diagrams were then sent to an IT team along with the proposed changes requiring approval for implementation from the concerning stakeholders.
For an industry such as the oil and gas industry, where time is of the essence our Cognitive RPA solution was deployed for this delicate task. The bot deployment automated the entire process from proposal generation , to problem identification by using the corresponding diagram from database and finally identifying specific points requiring fixes. Bot learns the processes of identifying such point to fix through a continuous learning process. Finally the proposal is sent for approval, all within seconds of request for approval.
Health care MGUs would need to perform ratings across multiple reinsurers platforms. Robo-Rater steps in as an intelligent digital underwriter and predicts indication premiums and its benefits. Keying in the client details and requested coverage information across all the rating systems is one of the business challenge as it is repetitive task and requires accuracy. Also the underwriters need to perform a number of combinations of coverage, limits, deductibles etc to obtain a premium closer to the clients target premium. These two are areas are automated by the Robo-Rater.
By leveraging the AI abilities of RPA the Robo-Rater provides a solution by fetching the employee data, clients coverage history, providing indication of premiums to requested coverage and alternative options. Underwriter chooses one from this, then the bot will enter details to all rating systems. The final ratings will be much closer to the initial prediction.
A leading US based digital media company was facing great difficulty in calculating the AP & AR of their programmatic advertisement business on a monthly basis. The company has tie-up with a large number of ad-Networks and each ad-Network has their own analytical websites from where the advertisement related revenue data to be collected for invoicing. On top of that, post downloading the revenue data, the finance team has to perform several calculation rules to arrive at the final invoice amount.
The major steps involved in this process are:
An un-attended bot is deployed to automate the entire financial activities related to ad-Networks revenue. The RPA solution helped to complete the whole activity within 2 days which used to take 10 days earlier. It also helped in avoiding calculation errors and multilevel of verification needs.
A leading telecom service provider implemented the RPA solutions in automating their payment reconciliations. The process involved extraction of invoice data from PDFs sent via email and reconciling it with supplier payments data .The approved data are then entered into the SAP ERP system on a daily basis. There is also a second level of reconciliation made between the entries in the ERP system and the corresponding banking statements. These levels of reconciliations are time consuming, mundane, stressful and most human error prone when done manually.
Deployment of our cognitive RPA solution was the perfect solution for this challenge whereby an intelligent bot was deployed to read and arrange the PDF invoice by means of OCR engine and fuzzy logic algorithm. The extracted data is reconciled with payment data stored in an excel file. The reconciled payment details are entered by the bot into the ERP system. The bot is also equipped to perform banking reconciliation as per need. When triggered to perform banking reconciliation, the bot will extract banking statements from corresponding portals and transforms statement to the ERP format for uploading into the ERP system. The uploaded banking records are then reconciled with the book record in the ERP system by the bot. Thus the entire process of reconciliation was automated saving our client money and time.
The task of contract renewal process when done manually include analyzing various parameters for different customers and businesses who grouped under categories such as gold, silver, platinum etc. The manual process took mostly 80 days annually to complete it, which would results in delay of the renewal processes to new service contract. Changing a contract in SAP manually take nearly 8 minutes per renewal transaction, which will amount to a substantial time for more than a million requests.
Our solution for the entire process was to deploy an unattended bot which monitors renewal requests coming via email other document formats. The data extracted from these are used as parameters by bot to prepare a data comparison sheet .The bot compares the data with master contract information from an internal portal. The bot will inform the corresponding authorities regarding the discrepancies on the data received via an email. The ones with matching parameters are entered into an SAP system and contract is updated.
When a request for credit limit increase is arrived to the customer service representative(CSR), he/she need to navigate between the screens in CRM and other data sources to collect information regarding the customer financial history to determine if the customer indeed is eligible for an increase. After gathering the information, the CSR has to perform validation steps to calculate the eligible amount and communicate the same to the client.
Once approved by the client, the CSR has to process a transaction on mainframe as well as the CRM and send the confirmation email to the customer. It is a time consuming process, and causes customer concerns especially when he/she is on the call with the CSR.
This business challenge was very delicate and involved handling of highly sensitive databases, systems and rules by the CSR. A secure, attended bot serving as an assistant to the CSR, will simplify the overall services provided by him/her. As soon as the CSR receives the call, bot will pull out all the details of the customer from CRM along with necessary information for the CSR to validate with customer’s financial history.
Bot will then perform all the validation steps to assess the eligibly of credit increase and provide options to the CSR which he/she can immediately communicate to the client. Upon customer’s approval, bot takes care of processing the necessary transactions in the mainframe and CRM systems and sends the summary email to the customer.
