Conversational automation can be experienced in broadly 3 forms. These are chatbots, voicebots, and voice assistants.  Let us study them in detail.

• Chatbot: These are software programs that interact with human users over chat platforms using natural language processing(NLP) and artificial intelligence(AI) in order to understand questions put forth by the user and provide relevant answers. The initial chatbot was text-based and was programmed to reply to a limited set of simple queries. Answers had to be hardcoded by the chatbot developers, and the bot would only be able to answer questions for which it was trained.  However, today, chatbots are able to learn through repeated interaction with human users and can dynamically provide responses by integrating with knowledge bases.

There are multiple approaches to building chatbots that are used in the market today:

1. Menu based: These are the most basic type of chatbots. The user may have to choose one among multiple options to finally reach an answer. These type of chatbots are best when the intent is to strictly navigate the user through pre-decided offerings and limited and fixed FAQs
2. Keyword recognition based: These chatbots listen to what users type and respond appropriately. They are trained to capture relevant keywords associated with the service being offered. However, they tend to fail when questions asked are similar in nature but not an exact match to the keywords.
3. Rule/Linguistic based: These are intent-driven chatbots that are trained on recognizing the purpose of a user’s enquiry. This type of chatbot is best implemented when there is a clear demarcation of customer query type. It can catch any intent put forth by the customer that it has been trained for.

At IGT, we have created multiple chatbots for various clients across the globe. For example, we have developed a keyword based chatbot for a leading retail company specializing in health self-test kits. The chatbot answers basic queries related to the product sold, such as product usage eligibility, cancellation, refund policy etc.

• Voice Assistant: Voice Assistant is a type of Virtual Assistant. Voice Assistants make use of voice recognition, speech synthesis and natural language processing and help people by doing some basic tasks. There are multiple voice assistants like Apple Siri, Microsoft Cortana, Amazon Alexa, Google Assistant. Voice assistants make use of certain wake words like “Ok Google” or “Hey Siri” in order to start performing the task assigned. Voice assistants don’t really understand what a human says, they only recognize wake words and communicate with a server to complete the task.  Voice assistants can be deployed on the phone and even at home. Voice assistants for phones perform tasks like setting alarms, scheduling a meeting, taking photos, or accessing other apps on the phone. Voice assistants in homes can be used in the form of smart speakers to get information on weather or news, finding a recipe, or controlling smart home devices.

IGT has built integrations into some of its chatbots so they can be triggered by the use of voice assistants such as Google assistant.

• Voice Bots: Voice Bots are also a type of conversational Assistant. The voice bots make use of artificial intelligence and natural language understanding for communication. It converts speech to text and passes on the query to the NLU engine, and once the relevant response is generated, converts it back from text to speech and parses it back to the user. In effect, they are used either as a complement or as an alternative to traditional IVR in the Contact Centre space. Voice bots respond to how human agents would respond to queries, and not only determine what a customer wants but also guides them to an effective resolution.

IGT is involved in the deployment of voicebot at the contact centre of a leading global online travel agency and a large hospitality group. With the help of voicebot deployment IGT has helped its clients to improve its efficiency by achieving up to 35% containment of volumes within the BOT and improvement in CSAT by 15% and NPS by 25%.

In conclusion, while there are multiple approaches to implementing conversational automation within an enterprise, the decision of which type of conversational automation should be made depends on factors like the business problem statement, customer engagement channel, breadth and depth of offering, and service level agreements in place.

Author:

Ayushi Jain is a Module Lead in RPA at IGT Solutions. She has 8.5 years of experience in the IT industry and has rich work experience in the Travel and HealthCare domains. Ayushi has obtained various certifications in UiPath and Automation Anywhere. She loves to travel and explore the untouched beauty of nature and enjoys reading fiction in her free time.

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Hotel contact centres are the backbone of hospitality operations and play a vital role in providing round-the clock support to ensure customer needs are being met promptly and accurately. The good quality of service encourages repeat business, increased referrals, opportunity to cross sell and up-sell, customer satisfaction and a boost in profitability. In the hotel industry, contact centres are crucial because of the demanding nature of the business and the need for consistently increasing operational efficiency.

Given that the primary driver of the hospitality industry is guest experience, contact centre agents should spend most of their time providing accurate and quick resolutions to customer queries. However, the majority of the agent time goes into the mundane task of pulling information from different systems and carrying out manual repetitive back office tasks when responding to customer queries. While handling complex customer queries, contact centre agents have to put customers on hold when searching for answers across different systems and documents, which is tedious and time consuming. This increases the AHT and irritates the customer, and leads to customer dissatisfaction and potential revenue loss for the hotel. Robotic Process Automation (RPA) as a technology can be of great help to contact centre agents in this scenario where retrieval of details is required from multiple systems. Attended RPA bots can be deployed on systems of contact centre agents to help them gather information required to resolve customer queries from different systems with the simple click of a button.

RPA bots can be used in hotel contact centres in the following areas to assist agents and enhance overall productivity:

• Bookings: RPA can be used to automate the booking process from start to finish. The vendors or partners send details to the contact centre for bookings or cancellations and bots can be used to create or cancel bookings on reservation systems.
• Analysis of customer feedback and reviews: Customer reviews play an important part in improving service and standards. The RPA bot can extract reviews, analyse them and send a prompt response to the customer depending on the review.
• Notification to customers: Providing regular updates to the customers is a key aspect of the hospitality industry. This can be easily managed using RPA, the bots can be used to send timely updates to the customers for a better experience.
• Back office operations: Repetitive and high volume back end processes like invoice processing, claims processing and bill generation can easily be automated using RPA to save agent time and reduce human errors.
• Reporting: The bots can swiftly extract and organize data from multiple sources and systems to generate reports to provide better insights of performance and identification of areas for improvement.

The role of Robotic Process Automation (RPA) as a technology in hotel contact centres has increased significantly in the last few years. Many contact centres are implementing RPA solutions to improve the customer experience, enhance efficiency and increase productivity.

The following are the key benefits of using RPA in hotel contact centres:

• Time Saving: The RPA bots can gather information from multiple systems in no time leading to reduced wait time on calls.
• Improved Accuracy and Compliance: The manual errors will reduce as BOTs are more consistent and process with 100 percent accuracy.
• Reduce Operational Expenses: RPA bots can work 24/7 and process transactions faster compared to a human agent leading to reduced operational costs.

IGT Solutions Intelligent Automation practice has worked with many hospitality companies by providing automation solutions to improve efficiency and reduce operational cost in contact centres. Over the last couple of years, IGT solutions has worked with two leading hotel groups in Europe and USA respectively and automated processes in the contact centre such as guest booking confirmation, contract loading, updating metasearch commissions and auto-response to customer reviews which has helped these clients to save over $2M in the last 2 years.

Author:

Nischal Guleria is a Senior Business Consultant at IGT Solutions’ Intelligent Automation Practice. He has an extensive experience in process automation using RPA for Travel, Hospitality and Finance domains. Outside of work, he loves travelling and walking. He can be reached at Nischal.Guleria@igtsolutions.azurewebsites.net

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Before Robotic Process Automation (RPA)
Depending on the procedures, protocols, and infrastructures of each institution, steps to process debit or credit card fraud significantly varied. Still, certain steps used to be followed, namely, collection of disputed transaction data from the web-based core banking system; gathering and investigating of information associated with the claim; and processing of the debit/credit card fraud disputes via CMS – card management system.

Without the help of technology or automated solutions, every single step would be conducted manually, from data gathering and data processing to decision making. For some banking institutions, transactions could be handled by batch, while for others, they needed to be resolved separately. This traditional method was not only time-consuming, discouraging, repetitive and overwhelming for workers but was also prone to more errors. Given the fact that there were thousands of card fraud claims per day, it was a challenging task for financial institutions to ensure accuracy and speed through conventional techniques, most of which were based on human intervention.

After Robotic Process Automation

Data Gathering: Collecting information on disputed transactions is the first and foremost step bank employees have to follow. Robotic Process Automation (RPA) solutions can help navigate and log into the web-based system of the bank, select a date range, and export the transaction data. To gather additional information from numerous internal databases or public domains to give a holistic view of customer data for fraud analysts robots can be utilized.

Data Processing: After relevant data is captured, Robotic Process Automation (RPA) can assist bank employees in removing duplicates, and formatting and refining data to make it fit for use. When this automation solution is combined with Artificial Intelligence (AI) technologies such as Intelligent Document Processing (IDP), Text Analytics, and Machine Learning (ML); the robot can track activities, collate payments, determine anomalies, and identify fraud patterns. Apart from freeing up humans from repetitive and monotonous tasks, RPA also ensures higher accuracy and enhanced productivity, as it can self-learn from previous cases, thereby reducing time spent on subsequent disputes at most.

Decision Making: RPA has revolutionized the back-end operations of banking organizations, and debit/credit card fraud processing is not an exception. The automation solution has been able to significantly reduce costs while easing financial employee workloads, as well as increasing the quality of fraud processing and minimizing the number of human error-related issues. While the issues faced by financial institutions in detecting and processing fraudulent card transactions may continue in the future, Robotic Process Automation, more or less, can empower efficiency in resolving these challenges.

About IGT in RPA
IGT Solutions has an extensive experience in back/front office automation leveraging Robotic Process Automation (RPA) as the means to automate business processes which are high volume, repetitive, prone to human error and come with stringent regulatory compliances. The tasks can include queries, calculations, reports and maintenance of records and transactions.
IGT has a team of RPA specialists who have successfully automated processes for some of the major players across industries.

Author:

Himanshu Gandhi is a Project Manager at IGT Solution’s Robotic Process Automation (RPA). He has 14 years of diverse work experience as a Senior Consultant and Project Manager for Digital Transformation across Airlines, Food and Beverage, and Banking industry. He can be reached at Himanshu.gandhi@igtsolutions.azurewebsites.net.

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Continuous refinement of technology has redefined and enabled the user to harness various benefits of digital transformation, on the other hand, it has also provided the same advancement to a hacker who has been sharpening hacking attempts and malware attacks.

In the year 2022, it has become prudent for individuals and companies to be well prepared for tackling ever increasing cyber threats and continue to fine-tune and upgrade security strategies and benchmarks.

One of the solutions is to timely invest in security testing but it would be important to know about the trends to expect this year.

Artificial Intelligence: The key use cases of artificial intelligence are seen in the fraud detection on financial portals and intrusion detection systems. It is very useful in analyzing the data and finding unusual patterns of cyber-attacks on the systems. Artificial intelligence by its core is capable of analyzing humongous amount of data from network traffic to assess possibility of cyber threat on the system.

Given the fact that hackers are trying to utilize machine learning methodologies to automate and implement malicious events in organizations, it is prudent for the organizations to enhance their cyber defense systems by harnessing the power of artificial intelligence.

Ransomware Threat: The year 2021 had seen a spike in ransomware attacks. The UK National Cyber Security Centre reported the number of ransomware attacks increased by three folds in the first quarter of 2021 compared to the whole of 2019. The various reasons attributed to these spikes are due to the increase in financial activities on digital platforms due to the pandemic, enhanced usage of e-commerce and enough controls not in place for employees working from home.

Many companies and governments are still using outdated technologies, processes, protocols, and procedures, which ultimately increases the vulnerability of getting attacked by ransomware. We have to fix these issues with proper budgeting and management alignment, in addition to other measures such as improved security, better monitoring and reporting.

Cloud Security: With the popularity of cloud implementation and moving organizational sensitive data to the cloud, it becomes very important to secure cloud infrastructure. Cloud though is very secure and has several layers of security from user management, network management, to secure key management. It has its own challenges in terms of security, as any security issues on cloud hosted applications will impact the authenticity, integrity and availability of the data.

One trend of year 2022 would be a possible growth in terms of cloud adaptation, it will also mark for newer ways of cyber-attacks on the cloud infrastructure.

Cybersecurity Talent Shortage: Cybersecurity talent is scarce in the market and there is no doubt about it.  The increased number of cyber-attacks in the year 2021 has further fueled the demand for trained cybersecurity professionals across the globe. It is unlikely that this gap will be filled in a timely manner, respite may come from artificial intelligence, where it will be used to detect malware in the network by analyzing a vast amount of data more quickly than humans, detecting issues such as phishing attacks, privilege escalations, and insider threats.

Internet of Things: Statista, a market research company, projects global spending of 1.1 Trillion USD by 2023 and consumer spending on smart home systems worldwide in the tune of 123 bn USD by 2021. The risk of cyberthreat is going to increase in the year 2022 with more proliferation of IoT devices. As we all are aware of the high vulnerability of IoT devices owing to different communication protocols, operating systems, integrations and lack of any standardization in space.

Conclusion

IGT with its Security Testing COE is well positioned to achieve shift-left of security testing and thereby finding security vulnerabilities earlier in the lifecycle, and working with all stakeholders to ensure these vulnerabilities are taken care of before releasing the software on production. IGT cyber assurance covers OWASP, PCI-DSS, HIPPA, ISO 27001 and other standards of cyber security.

Author:

Yatender has 20+ years of experience in software test engineering. As the head of Testing Practice at IGT Solutions, Yatender is actively involved in innovations related to test engineering covering new tools, technologies, and solutions, and enabling IGT’s clients to achieve faster time to market quality improvement, and optimization of developer efforts in overall SDLC. A result-oriented leader, proficient in delivering high customer value and achieving excellence in service delivery management with proven skills in consulting and managing large and complex test programs. When away from work, he enjoys reading on a variety of topics and spending time with kids.

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With growing demand, organizations realize it is important for them to enable their business users to build micro automation for their day-to-day work. Any such business user who builds automation with minimal or no coding experience to support their own business work is called a citizen developer.

According to a recent Gartner report, 61% of corporates already have or are planning to have initiatives for citizen development. By 2024, it is expected that low-code application development will be responsible for 65% of all application development activity.

Gartner defined a citizen developer as “employees who create application capabilities for consumption by themselves or others, using tools that are not actively forbidden by IT or business units.” A citizen developer hence is not a dedicated role in and of itself. They report to a business unit or function other than IT, and the development activity is not their primary work role.

Citizen development initiatives can bring multiple benefits for a company, such as:

• IT-business collaboration: As business users can build basic productivity automation solutions, it will reduce the IT backlog, allowing IT to focus on complex legacy migration activities to modernize infrastructure or build native mobile apps to create an engaging customer experience. This collaboration also allows business users to get involved early on in the application development process, to help IT by providing valuable domain expertise and business requirements.
• Improve customer experience: Business teams automating their own back-office processes will improve their ability to deal with customer requests and improve customer experience in the end.
• Reduce risk: With an IT-approved LCNC tool, any business team can build multiple automation solutions, under the IT team’s supervision, allowing IT to maintain visibility and control into the entire application landscape of the company and the data it produces.
• Productivity Gain: Empowering employees with the right tools can allow them to streamline their internal processes and make their operations smoother since employees are the most motivated to solve their operational problems and understand their business processes better than anyone else.

Scaling Automation with Citizen Developers​

While IT-enabled technical teams are needed for enterprise automation, empowering business users to develop their own automation could help sustainably scale the automation within a company. Citizen developers are a creative force that generally comes under two categories.

• Basic users, who can build automation for their selves on their desktop related to their day-to-day tasks.
• Advance users, who can build automation for themselves or for the team or company, which can later get validated and standardized by a professional developer.

Since employing a full contingent of developers can be a cost-intensive approach, broadening the scope of automation to citizen developers carefully chosen for their interest and skill with low code development, with an added layer of technical validation by fully trained developers can help reduce costs.

Before rolling out the citizen development initiative, decision-makers need to consider two factors: Value and Risk. To make such an initiative a success, the team should enable staff with in-depth knowledge of business processes by providing them training and mentorship. They should establish clear governance and boundaries, set goals, make best practices, and track and manage outcomes. Finally, they should review processes for ongoing support, maintain and avail reusable assets, and leverage and document automation ideas.

Author:

Brij Mohan Sharma is a Senior Technical Architect at IGT Solutions’ Intelligent Automation and Analytics Practice. With a specialized experience of 15 years in Digital Transformation Consulting across Travel, Hospitality, and Retail domains, Brij has worked extensively on the front edge of process and conversational automation technologies, designing and delivering innovative back and front office automation solutions.

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Introduction

In an increasingly digitized world, corporates have realized that the fastest way to ensure efficiencies within internal operations is to automate – and the biggest roadblock to automation is structured and digitized inputs. Consequently, there has been a big focus on digitization and document processing. The target of these drives is to boost accuracy and effectiveness to structure unstructured and semi-structured data, and to digitize any non-electronic data into machine-readable formats. Towards this end, multiple technologies have been explored – optical character recognition through digital character libraries, redaction solutions to un-redact or redact digital documentation, AI/ML to classify and categorize multiple formats and data structures and provide automated learning.

It is a base understanding that the automation scope in the back office today is limited to the volumes that come from electronic and structured data, with a manual intervention needed for the rest. Through IDP, the scope of automation can be expanded to all the volumes that can be digitized and brought to a structured format, thereby maximizing the value delivered. The following sections look into how Intelligent Document Processing takes process automation to the next level, by adding digitization, structuring, and intelligence to the picture.

Components of the IDP Solution

The document reading and extraction market today is highly fragmented. Different vendors provide different process flow and differentiated capabilities. Any comprehensive Intelligent Document Processing or IDP solution will comprise of five critical flows – Data Ingestion, Pre-Processing, Document Classification, Data Extraction, and Validation or Feedback Loop.

Data Ingestion: Any IDP solution needs to be able to read different documents using OCR or other powerful ML algorithms. Normally, any data captured by an organization can be categorized as Structured (fixed structure and hierarchy), Unstructured (unorganized and multi-format, free form), and Semi-structured (blend of structured and unstructured data). Market research shows that more than 75% of data in the world is either in an unstructured or semi-structured format. While it is easy to read and categorize data in structured formats, like Excel tables, reading data in unstructured and semi-structured formats requires the use of AI based solutions – such as Optical Character Recognition (OCR), Computer Vision (CV), and Natural Language Processing (NLP). OCR detects language-related characters, letters, numbers, etc. by depending on structured data tables. However, with CV and NLP, the capabilities of OCR to handle unstructured and semi-structured data have undergone a paradigm shift, resulting in a set of solutions called Intelligent Character Recognition (ICR).

IDP solutions capture the data extracted by ICR and enable the system to structure it based on the data types, regardless of whether the documents are structured, unstructured, or semi-structured. Adding ML algorithms on top allows the solution to learn from training with the manual corrections made every document-reading iteration.

Pre-processing: IDP may need to run on handwritten documents, or scanned images or computer generated PDG files. Each of these have a different standard of quality. Before any data can be extracted then, a document needs to be evaluated from a quality assessment standpoint – including cleaning, organizing, and transforming the raw data to meet the quality parameters mandated by the IDP or machine learning models.

Some popular preprocessing methods used by IDP tools include:

• Data annotation and labeling: A configuration process where specific document types, including document fields, get tagged and annotated to help with classification.
• Merge/split documents: Capability to analyze multi-page documents to recognize the layout to detect when documents need to split or analyze multiple documents to recognize when they need to be merged into one.
• Skew correction: Ability to recognize when a scanned document is not upright and is skewed, where the text appears rotated or tilted in different angles. Capability to carry out a skew correction or de-skewing.
• Noise Removal: The process of detecting and removing unclear sections, such as black dots, shadows, or blurs, and cleaning them up to ensure better quality. Noise removal methods include median filtering, edge detection, linear regression and auto-encoding.
• Data validation and correction: Compatibility check of the document, format validation, resolution specification.
• Taxonomies and ontologies: Collection of data in categories, and the identification of a pattern of various entities and relationships among the data

Any IDP solution should be able to take up pre-processing to ensure data quality for extraction.

Document Classification: When a back-office process requires multiple types of documents or multiple types of information to be captured – these need to be classified correctly by the IDP solution to be able to extract the relevant information. This could be the classification of multiple documents or even the classification of pages or sections within a single document basis the data type being captured.

The classification module of an IDP solution is based on a combination of NLP, ML algorithms, deep learning, and other AI technologies. In today’s IDP market, a classification does not just identify the content type within a document and categorize it but aims to achieve intelligent classification by looking at additional contributing parameters of classification, such as date ranges.

Data Extraction: The actual data extraction element of an IDP solution goes beyond traditional OCR. Since OCR focuses on character recognition, it is limited in terms of intelligence of what a data point indicates. With the evolution of technology, businesses are looking to neural networks and algorithms for natural language processing or computer vision to go from OCR to intelligent data extraction.

An efficient IDP solution addresses many extraction challenges:

• Textual data extraction: Use of entity extraction models to identify and segregate sets of information based on similar or common semantic parameters. For example:
  1. Key value pairs
  2. Entity recognition
  3. Questions and answers
• Visual data extraction: Understanding of visual elements such as tables, graphs, checkboxes, logos, and signatures. IDP solutions focus on the following during extraction:
  1. De-noising irrelevant content, and detecting the region of the visual element presence accurately;
  2. Detecting elements with multiple layouts and mostly different variations;
  3. Detecting the exact boundaries, and segmentation based on semantics;
  4. Detecting sub-elements in the region of interest and extracting information from them, such as rows and columns for tables; and
  5. Decoding the structural relationship of the information

Validation and Feedback Loop: The key evaluation parameter of any IDP solution is the accuracy of extraction. Unlike OCR, IDP looks beyond quality of extraction to data validation against external sources to improve accuracy. An efficient data validation system can improve IDP accuracy by almost 5-10%. Data validation can be dictionary-based, context-based, or pattern-based. Most IDP solutions validate data against defined business rules.

Another method used by IDP solutions to improve accuracy is the incorporation of feedback loops. Any corrections performed by a user carrying out quality checks can act as an input to the system so that the accuracy can be improved for future extractions. Modern ML-based IDP solutions automatically learn from manual corrections to ensure the accuracy of future extractions is improved.

Author:

Nandhagopal Muralithar is a Senior Business Consultant at IGT Solutions’ Intelligent Automation and Analytics Practice. With specialized experience of 7 years in Digital Transformation Consulting across Travel, Hospitality and Retail domains, Nandh has worked extensively on the front edge of process and conversational automation technologies, designing and delivering innovative back and front office automation solutions.

The post Intelligent Document Processing (IDP) in a New Age Automated Workplace appeared first on IGT Solutions.

However, as automation matures, it is clear that its potential is limited by its rule-based nature. Blending RPA however, with Artificial Intelligence technologies, and other advanced techniques, can expand the scope of automation, not just bringing down its limitations but compounding the benefits delivered. This combination of AI and RPA is called Intelligent Automation.

The most important feature of Intelligent Automation is its non-invasive nature where no major changes are required to the existing landscape and can be integrated across multiple applications, helping in faster deployment, and continuous improvement as opposed to legacy system automation that would require invasive integrations and has long turnover rates.

Driving value across Finance with Intelligent Automation

Let’s understand how intelligent automation can be implemented in the back-office processes of Finance, such as: Account Receivables (AR), Account Payables (AP), and Financial Planning & Analysis (FP&A) that are critical elements in the functioning of any corporation.

Challenges

Account Receivables: Accounts receivable (AR) is the payment/balance due to an organization for the use or purchase of its goods, products, or services. Companies that are still using humans for their account receivables process face the challenge of errors in invoicing leading to delayed payments, credited invoices, and other disruptive and troublesome issues. Thus to overcome these problems automation of account receivables is important.

Account Payables: Accounts Payable (AP) is a liability and a short-term debt on a balance sheet where a business owes a payment/money to its vendors/merchants/providers that have furnished the business with goods or services on credit. Perhaps the most high-risk errand in the financial services industry is managing payments. AP serves the ideal conditions for automation and guarantees a more prominent ROI i.e. return on investment. In order to streamline the account payables process, AP automation is a necessity.

Financial Planning and Analysis: Financial planning and analysis (FP&A) involve activities that support an organization’s financial health: these are activities such as planning and budgeting, forecasting and modeling, management and performance reporting, integrated financial planning. When processes such as these are not automated and handled through emails, attachments, and spreadsheets, it leads to inefficiency and there is a high risk of delays, lack of visibility, and improper approvals. Organizations running FP&A on manual mode would not have enough resources to make forecasts at a faster cycle time as they require regular updates on the latest financial statements, capital expenditures, and investments making for weak financial planning.

Clearly, the finance industry requires processes that ensure tedious, repetitive, and time-critical patterns are not an issue. In addition, these cycles are data-sensitive and a slight mistake or error could bring about considerable losses, so robotization of errands requires an unflagging precision.

How can Intelligent Automation (IA) help?

Account Receivables: IA helps streamline the AR process and helps distribute all your customer invoices electronically regardless of your customers’ digital capabilities. Rules can be modified basis each customer’s needs and requirements generating a fully digital workflow. Also, it benefits in lower distribution cost, faster payments, and invoice handling, improves cash flow, increased accuracy and security, and most importantly customer relations.

Account Payables: The timeline for sending and receiving payables can be automated. RPA bots can build approval workflows and process payments and receipts; ensuring that all the transactions take place on time and all financial audit policies and regulations are adhered to.

Financial Planning and Analysis: Performing analysis of the latest financial trends is instrumental for visibility over the workforce. Automation of processes helps in the reduction of process inefficiencies, increasing process visibility which leads to better decision making, and maintaining a stronger, more transparent relationship with business units and departments.

Some other benefits:

• Reduction in operational costs
• Improved accuracy-by almost ~99.99% and increase in compliance as the human error rate is reduced
• Productivity, faster processing time, and reduced average handling time by 35-50%.
• Improved decision-making capabilities
• 24*7 Availability: BOT will execute tasks even during odd working hours.

F&A processes where Intelligent Automation can be applied

Listed below is a list of processes that were automated (% wise) and the benefits of IGT’s IA implementation in Finance and Accounting.

What would the automation of the above processes look like?

Account Receivables: Once applied, AI rules allow the BOT to access and process the billing data, prepare daily AR dashboards and reports, provide visibility on invoice statuses and all customer accounts & share the generated invoices with the revenue department. The system’s ability to deliver more granular results makes it highly accurate, precise, allows for fine detail analysis, and quickly resolves issues related to invoices.

Account Payables: Let’s look at an example to understand how the automation process takes place in AP: Essential cycles of Account Payable include Telecom and Travel invoice processing, Daily Exchange rates upload, and Trial Balance. The BOT reads the invoices using an OCR and creates their entries in SAP based on defined business rules. In case of a failure, notifications are sent to the respective users. The BOT is scheduled to pick up the currency exchange rates for multiple countries daily and update them in SAP. It also extracts data from SAP, consolidates and filters to deliver all the reports under the automation scope, and emails them to the Finance team.

Financial Planning and Analysis: Let’s look at an example to understand how automation works in the headcount of FP&A: Essential cycles of Finance Planning & Analysis include undertakings such as headcount, profitability in SAP, SG&A analysis, reports- DNB credit analysis, entity wise, travel, MIS, etc. The BOT extracts the required details from the SAP headcount dump which is then processed to create a headcount report.

Conclusion

RPA is an innovation that can change the realm of the finance industry.  RPA solutions are expected to grow in several main areas. It offers the clearest path towards a true digital transformation for businesses. IGT Solutions Pvt. Ltd supports businesses driving transformative efforts with investments in automation.

Author:

Ramani Giri is the Senior Business Analyst at IGT Solutions’ Intelligent Automation Team. She has an overall 3 years of experience in the Travel and Hospitality domain. With expertise in Data Analytics, Process Automation, and Conversational AI for delivering back-office automation solutions. Outside of work, Ramani likes to swim, travel and read.

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For the benefit of the uninitiated, RPA in layman terms can be understood as a solution that allows the automation of business processes end-to-end, irrespective of the type and number of applications involved and the environments in which they are used. Automation itself is not a new concept though and has been around for a long time. However, it has been limited to certain applications or areas of use. RPA is different from “conventional” automation as it is non-invasive and can be used to automate larger business processes instead of creating multiple point solutions. RPA “Bots” can be quickly deployed to automate repetitive tasks, and they save a considerable amount of time and money for the organization. They improve accuracy, efficiency, and even compliance.

RPA bots are responsible for carrying out crucial processes across multiple business functions. They operate as a human and replicate steps to execute repetitive tasks that a user would do on a day-to-day basis. They can access databases and use supporting services. This creates a possible risk and a potential challenge. Since the bots handle sensitive data and the solution may involve moving it across systems from one process to another, it can be exposed if it is not secured. Thus, it must be made sure that things work out as planned.

What are the challenges?

RPA bots are not built like enterprise applications. Enterprise applications are built over a long period, and huge inputs and overheads in development and testing are involved. RPA, on the other hand, is a quick implementation. Development and deployment of RPA bots only take 1-2 months on average. As a result, it is more susceptible to threats if proper security frameworks are not applied and best practices are not followed.

RPA bots help organizations process a huge quantity of data 24/7. As the RPA tools have matured, the scope of data that can be handled by bots has also increased. The emergence of process intelligence features has helped significantly in increasing the variety and volume of data. This varied and massive volume of data helps in uncovering more insights than before. At the same time, however, the risks of data being compromised have increased as well.

One of the main risks associated with RPA, and the concern of many, is data security. It may either be from the point of view of the bot transactions or data leakage. Transaction safety is always a concern for enterprises when they opt for RPA. It is difficult for them to trust the bot to function with minimal supervision. Data has become and will remain for some time, the most important asset of an organization. Any untoward incident can lead to huge problems. Two of the primary reasons that can lead to this problem are improper governance and lack of adherence to best practices.

Data leakage can be broadly understood as exposure of bot/user credentials or the customer data that the RPA bot handles. The bots use the organization’s credentials to log in, and they need access to passwords. Therefore, it is really important to keep track of who has access to the bot for execution and maintenance. Unauthorized access to an RPA system could result in intellectual property damage. As world bodies are taking note of the importance of data and bringing in regulations to protect it from unauthorized access and use, it is of prime importance that problems like access abuse and data disclosure are weeded out of RPA solutions completely.

What can be done?

The good news is, the problems described above can be remedied and avoided altogether. To address security failures in RPA projects and manage associated risks, the following things need to be kept in mind.

• There should be a distinct difference between an RPA user; the person who will operate and run the bot and the RPA bot itself. A unique identity should be assigned to each RPA bot along with dedicated credentials. This will help in demarcating bot and human actions and will attach accountability to bot actions. It will provide the complete audit trail of what the bot does. The trick is to not create a bot but a virtual employee.
• Manage access on two fronts. First, who has access to the bot? Limit the number of people who can access the bot for both execution and maintenance. This will eliminate the chances of rogue changes being made in the bot and the bot will act on tested lines. Second, access to systems. Creating a separate bot entity as discussed earlier will help in this. Using user credentials can provide more privileges to the bot than actually required. Dedicated credentials will limit the scope of system and application access the bot has. Reduction in the possibilities of unwanted actions and transactions will help in avoiding breaks in security
• The development and deployment of RPA bots is a continuous process. It is not a one-time activity that ends when the bot goes live. Thus, it is imperative that the threats and vulnerabilities are also tackled continuously. The people handling the bot may leave the organization, the applications involved in the automation solution may change/update, the process itself may change based on business requirements. This makes it necessary that the security team is as much of a stakeholder in the RPA initiative as the RPA CoE (Centre of excellence) or the line-of-business team. Creating a risk framework that evaluates RPA implementation as a whole, as well as the individual scripts, periodically reviewing and testing RPA scripts with a special focus on business logic vulnerabilities, will go a long way.
• Focus on the security features of third-party plug-ins. The RPA tools available in the market come with the possibility of adding plug-ins to enhance their scope, use, and performance. The passing of data from one application to another requires special supervision. It is important to ascertain the security and trustworthiness of the plug-in that is used. Perform a product architecture risk assessment before buying into it.
• The last is to follow all the best development practices. Create separate environments for development, quality assurance, and production. Avoid hard coding of credentials and use credential vault protect passwords. Use configuration files to provide flexibility to the bot. Test the bot rigorously over all the possible business cases and variety of data that it may encounter. Maintain detailed log reports so that they can be reviewed when the RPA security fails. Complete, system-generated logs without any gaps help in investigating the root cause and taking mitigating steps.

The benefits an RPA implementation provides to the organization are immense. Proper selection of the RPA tool that suits the type of process and applications in consideration, vetting of any plug-ins that may be used, creating a security framework, and following best practices for development will help eliminate any security or data leak threat that may be posed. Undoubtedly, the rewards can be reaped for a long time.

Author :

Pratik Sharma is a Sr. Business Consultant in the automation practice at IGT Solutions. He has 4 years of experience in RPA in multiple capacities. Outside of work, Pratik is passionate about football and reading. He can be reached at Pratik.sharma@igtsolutions.azurewebsites.net.

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Customer Experience (CX) remained an ignored arena as companies were paying little to no attention to their customer experience strategy. However, the increased competition in the market has changed the scenario. The consumer’s experience management market is growing at around 17% every year, a trend that will continue in the future as well. Companies are used to toning products to match customer’s preferences. And they have now realized that CX is as much part of the product/service itself, leading to a changed CX strategy.

How CX affects revenue growth

Over time, businesses have understood that improving customer experience is not a marketing gimmick. It also has the potential to bring monetary benefits with increased revenue growth for the business. According to a study by Forrester, companies paying attention to customer experience outperform their peers by as much as 80%. It is an expected result as a better customer experience creates loyal customers. Higher brand loyalty eventually leads to increased engagement and willingness to spend more.

“If you’re customer-first and do it in a smart way, then it can help the company.”

– Augie Ray (VP Analyst, Gartner Research & Advisory)

People trust word-of-mouth more than any other form of marketing. Loyal customers can be the most reliable brand ambassadors for any business. However, it is only with a strong orientation towards CX that organizations can provide them with experiences they would like to share with others. And there is no reason to put it off the table when even one point improvement can lead to more than a billion dollars in additional revenue.

How to Improve CX

Customer experience is not about selling great products but is about building great relationships. And to build a healthy relationship, businesses need to establish trust with their customers. Here are a few strategies that have helped companies to connect better their customers:

a) Data collection: One reason for the inability of the businesses to provide exceptional CX in the past is that they lacked quality customer data. However, with increased digitalization, enough customer data is available, giving insights into customer behavior and preferences. Holistic data enables businesses to make informed decisions. As per Gartner, 80% of companies showing positive growth collect survey data than 58% of the no revenue growth organizations.

b) Leveraging Technology: Innovations like real-time analytics and Artificial Intelligence enable businesses to gather data and create a deeper understanding of customer behavior. It leads to a more personalized experience for the customer, increasing revenue through up-selling and cross-selling.

c) Customer care availability: Customers prefer businesses that are available 24*7, not only to sell but also to handle customer queries. Another aspect of availability is switching to multichannel reality, with presence across email, voice, web, chat, and social media. 24*7 availability of help through various channels helps resolve customer queries faster, accelerating the sales cycle.

d) Automation: Automation has proved helpful in streamlining many processes behind the scene. It has even addressed the 24*7 service availability expectation of the customer through bots. Businesses are increasingly using bots in customer-facing tasks where they have proved successful due to enhanced NLP technologies. It has resulted in increased lead generation and conversion, driving revenue growth through increased sales.

e) Consistency across communication channels: Switching from one communication channel, like the web, to another, such as mobile, shouldn’t affect customer’s experience. All of their data, along with services provided, should be equally accessible across all the channels. People use multiple devices these days. It becomes frustrating to enter the same information repeatedly as they switch channels. They would instead switch to your competition.

f) Agent Experience: Businesses need to take proper care of their employees first. Discontent employees become rude customer care executives that lead to unsavory customer experiences. Organizations should train them to be empathetic to respond efficiently in all situations.

Conclusion

The competition out there is unrelenting. It has already outgrown the quality space and is entering the field of customer experience. Net Promoter Score shows a difference of 10-70% in revenue growth with changed CX experiences; CEOs around the world agree. It demonstrates that the only way for a business to survive in today’s time is to shift from a product-centric to a customer-centric approach.

  Sources: Grand View Research, Qualtrics, Gartner, Forrester, Bain & Company

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A few common examples of how ecommerce businesses leverage automation.

• Fraud filters
• Suspicious login alerts
• Email newsletters based on customer groups
• Similar item suggestions
• Order status updates

And much more.

Imagine if you had to do all this manually or divide it amongst your team members, it would require constant monitoring and collection of information, parameters check, followed by taking action on these by following a certain process (e.g. sending an email, flagging orders, adding customers to specific segments), etc. Automation provides a means for the software to handle all this and proceed accordingly, without the need to intervene. The above can also be termed as workflow automation; automating tasks that keep the flow of work systematic.

Workflow automation aids any ecommerce business to run smoothly. If implemented properly, it can reduce redundancy, improve communications and customer experience and allows organizations to review how well the business is operating. While we’ve looked at a few examples where automation is generally applied, here are some key ecommerce business areas that cannot function without automation.

• Inventory and order management
• Accounting
• Cart abandonment
• Rating and review reminder
• Follow-ups

Automation and inventory management

There are hundreds of products in the inventory of an ecommerce business, and keeping track of each of them is simply a waste of time. Automation here lends a helping hand by keeping track of whether the products are in stock or out of stock. The scalability of your business also depends on the automation systems that have been implemented. With automation, businesses can get more visibility into their inventory which helps in checking backorders and missed sales opportunities. Not just this, from order placement to shipping labels and dispatch to post-sales, all of these processes can be automated and viewed in real-time.

Accounting with automation

An ecommerce business deals with several transactions in a day. Handling the receipts, invoices and other relevant documents manually will take an eternity. When these tasks are automated, you are not only increasing the productivity of your business but also saving time. Having an automation system that seamlessly integrates with your payment systems and automatically pulls in data on revenues and expenses while providing a detailed report is a basic feature ecommerce businesses need today. This can take care of expenses, purchases, refunds, returns, coupon code applications etc. effortlessly and eliminate delays and inaccuracies in the transactions.

Address cart abandonment with automation

According to Statista, the shopping cart abandonment rate in 2020 was 88.05%. Many people who add products to their cart, don’t necessarily purchase them, however, waiting too long to address the abandonment can affect your cart recovery and there is a chance your customer might lose interest. There are plenty of ways to recover the abandoned carts. By giving your automation tool the necessary commands, you can filter the users who did not complete their purchase and link it with an email reminder that shoots out an email to the user with a single click. Sending these automated emails keeps the products fresh in the customer’s mind making it easy to jump back into the buying process and pick up where they left off.

Review reminders with automation

According to research by Spiegel, about 95% of customers read reviews before making a purchase. This clearly indicates that if your customers ignore the ratings and review pop-up, does not mean that you should give up on it. Email still remains a flexible and universal messaging medium. It allows us to send longer, targeted messages to customers irrespective of where they are in the buying lifecycle. One way to remind customers to leave a rating or review is by sending them an email reminding them to express their thoughts about the product they just purchased. Automated emails can drive conversions that would have otherwise been left behind.

Automate follow-ups

As per a study by Bain, revenues for businesses that prioritize customer service rise 4-8% above their market. A satisfied customer will purchase more and even serve as a promoter who recommends to their friends, making them extremely valuable. Targeting customers who bought something and suggesting something suitable can be a difficult process only if it is done manually. Automation can simplify this to a large extent and keep the conversation going with the customers. By offering them new products and giving discounts, you cannot just bring back existing customers and increase your chance at further sales, but build sustainable paths that lead people back to your online store again and again.

Productive businesses rule the market and automation can help unlock the full value of your ecommerce business. The customer of today expects a smooth, streamlined experience that is augmented by intuitive and easy-to-use technology. Automation workflow makes operations less intricate and more well-organized. As automation simplifies task management and diminishes human errors, your team can focus on detecting customer pain points and analyzing the big picture. IGT’s Automation Centre of Excellence plays a vital role in providing a range of automation services that suit every business’ requirements. With strong expertise in the design and delivery of tailor-made solutions, we aim to cater to the demands of today’s customer.

Author

Gurmeet Oberoi is a researcher and writer of change tactics and technologies in travel and other verticals, she frequently posts across the digital ecosystem. With 9-yrs of experience in communications and marketing, Gurmeet has a passion for travel and reading among other things. She can be reached at gurmeet.oberoi@igtsolutions.azurewebsites.net

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