An active directory is crucial for managing user accounts, permissions, and network resources in IT operations. Manually managing active directory becomes a challenge as the network grows in complexity and scale. To keep the organization running, the IT operational team spends more hours on repetitive but mandatory tasks such as user account management, password reset, and access control.

But it doesn’t have to be this way. Active directory Automation is a necessity for organizations to streamline IT operations. In this article, let us explore the multiple aspects of active directory automation and its benefits for IT operations.

Why Does Active Directory Matter?

The Active Directory is the backbone of IT infrastructure. It provides a central repository for user group management, computers, and other network devices. Along with offering a central repository system, an Active Directory enables IT administrators to enforce security policies, user authentication, and access control to network resources. By providing a hierarchical structure of resources, an Active Directory makes it easy for the IT operational team to manage their administrative tasks and promotes better collaboration across IT organizations.

Manual Active Directory Management Challenges

Managing an active directory manually is a challenge for the IT operational team. Some of its challenges include-

1. Increased Legal Risk with Data Collection

   In the digital age, organizations use nontraditional employee onboarding to track employee activities. With high employee data comes legal risk. Organizations must have elaborate data records for their day-to-day activities to ensure compliance with regulatory standards. However, most organizations lack reporting system activity in the active directory, which increases the legal risk.

2. Human Error in Data Processing

   Manual active directory management increases the risk of typos, inaccuracies, and data inconsistencies in activity directory configuration. Suppose an IT service desk agent misplaced a username or group membership character. These human errors will lead to unintended permission or access to the system. Further, this data inconsistency can risk data security in active directory management.

3. Inefficient Employee Experience

   Across IT organizations, most employees require access to several systems and applications. With high-volume user provisioning de-provisioning, IT service desk agents struggle to process each request on time. Also, manual provisioning takes days to complete, which deters the employee experience and leads to inefficiency.

Active Directory Automation Examples

1. User Provisioning and Deprovisioning

   This IT process involves creating, modifying, and managing user accounts within the active directory. Active directory user account automation can create a pre-defined workflow and policy for user account management when an employee joins or leaves.

2. Group Management

   In IT infrastructure, group management means creating, modifying and deleting security groups and distribution lists in the active directory. Active directory automation tools can easily set up automated workflows to assign group membership based on user roles and attributes, create project-specific security groups, and enforce access control policies across the organization. Active directory automation can take care of the tasks like-

   1. Group Member Extraction
   2. Create & Delete Group
   3. Get Group Properties
   4. Check Group Existence

3. Password Management

   Password reset is one of the most common requests IT service desk agents receive. Manual password reset, including policy enforcement, is a time-consuming task. Active directory automation can reduce the burden of service desk agents by creating a self-service portal for easy password management. An automated password reset system can enforce password complexity requirements, expiration policies, and multifactor authentication to enhance password security.

4. Auditing & Reporting

   Audit management is another aspect of IT infrastructure that requires the constant attention of IT service desk agents. However, managing audit log collection, data analysis, and reporting requires much time and resources. Instead of performing audit monitoring manually, active directory automation tools can capture and centralize all the audit logs from various active directory components, including group memberships, user logins, and other administrative activities.

   Enabling real-time auditing reports and activity directory automation can detect anomalous behavior, unauthorized access attempts, and compliance violations. IT automation streamlines Active Directory management, empowering IT organizations to proactively address security risks and ensure compliance effortlessly.

5. Access Control

   Active directory access control involves assigning, modifying, and revoking access rights and permissions. Automating access control enables administrators to define granular access control policies based on user role, departments, and organizational hierarchies.

   Consider a scenario where a large organization implements Active Directory automation to manage employee access control. This organization has defined role-based policies that grant different employee access levels based on their roles and responsibilities. Hence, the finance department will have access to finance data, and the sales department will only get access to CRM data.

Conclusion

AutomationEdge IT Process Automation solution offers active directory automation to manage the complexity of user account management, access control, and security in a network environment. Embracing AutomationEdge’s active directory automation tools benefits organizations by helping them build strong IT infrastructure and overcome challenges in the ever-evolving digital era.

In today’s interconnected world, customers have myriad channels to reach out to businesses – from social media and in-app surveys to review sites, emails, and chats – accessible at any time and from any location.

But what happens to all these conversations?

Typically, companies rely on IT service desks to centralize customer feedback and aid agents in automatically categorizing support tickets. However, while this system reduces some manual workload by tagging tickets, the ticket classification systems within help desk software often prove to be rudimentary. Consequently, many tickets end up labeled as ‘other’ or with overly broad tags that fail to accurately describe the underlying issue.

This is where ticket classification utilizing machine learning technology becomes invaluable.

Let’s discover more in this blog about how ticket classification is powered by AI and can kickstart advanced ticket classification efforts immediately.

The Importance of Ticket Classification

Ticket classification serves as the backbone of effective customer support and IT service management systems. By accurately categorizing tickets, organizations can:

Challenges with Ticket Classification

When a support ticket emerges at the service desk, it requires processing and assignment of a tag or category to ensure it reaches the appropriate team member. This assignment can be either manual, where agents read the ticket and assign a tag, or automatic, where rule-based systems are set up following the ‘IF X happens THEN do Y’ principle.

Manual classification systems can be convoluted and overwhelming, leading support agents to struggle with categorization. Some of the other challenges the IT service desk team struggles with are-

• High Volume of Tickets: As organizations grow and expand their customer base, the volume of incoming tickets can become overwhelming, making manual classification processes time-consuming and error-prone.
• Subjectivity and Inconsistency: Human agents may interpret and classify tickets differently, leading to inconsistencies in categorization and prioritization.
• Resource Constraints: Limited human resources may hinder the scalability and efficiency of manual ticket classification processes, especially during peak periods.

How AI-Based Ticket Classification Help?

AI-driven bots have revolutionized the way organizations handle incident tickets with accurate ticket classification. Let’s explore how this process unfolds seamlessly:

1. Ticket Classification with AI Logic

   When a user raises an incident ticket an AI-powered bot swiftly classifies the incident based on its characteristics, leveraging advanced logic to determine the nature and urgency of the issue.

2. Automated Allocation to Support Group

   Once classified, the ticket is automatically routed to the correct support group, ensuring that it lands in the hands of specialists equipped to address the specific issue at hand.

3. VOIP Integration for Support Executive Communication

   The bot initiates VOIP calls to support executives within the designated support group. Leveraging availability data sourced from rosters and attendance records, the bot strategically contacts support engineers individually, maximizing the chances of prompt response and resolution.

4. Escalation Protocol

   If no support engineer picks up the call within a reasonable timeframe, the ticket is promptly escalated to the Escalation Manager of that particular shift for the respective support group. This ensures that critical issues are swiftly brought to the attention of higher management for immediate action.

By seamlessly integrating AI logic with VOIP communication capabilities, organizations can streamline ticket classification and achieve an 80% TAT reduction in ticket classification.

Network device management in IT refers to the process of overseeing and controlling the configuration, monitoring, and maintenance of network devices within an organization’s infrastructure. It encompasses a broad range of hardware components and appliances that facilitate communication and data exchange across computer networks. Examples of network devices include routers, switches, firewalls, access points, and various networking peripherals.

With multiple network device management, it’s challenging to ensure reliability, security, and optimal performance of network infrastructure. In this article, we will explore in detail network device management, the challenges associated with it, and how automation can enable IT teams to better manage their network devices.

Why Automate Network Management?

Network device management, while essential for maintaining the stability and security of a network infrastructure, presents several challenges that network administrators and IT teams must address. These challenges arise from the complexity, scale, and dynamic nature of modern network environments.

1. One of the biggest issues for network managers is the growth of IT costs for network operations. The growth of data and devices is starting to outpace IT capabilities, making manual approaches nearly impossible. According to a report, 95 percent of network changes are performed manually, resulting in operational costs 2 to 3 times higher than the cost of the network.
2. Manual configuration of network devices is time-consuming and error-prone. Ensuring uniformity across device configurations, maintaining configuration baselines, and enforcing compliance with organizational policies and standards require robust configuration management practices and tools. According to an industry report, around 40-80% of network failures are the result of human error.
3. Network devices are prime targets for cyberattacks, exploitation, and unauthorized access. Vulnerabilities in device firmware, misconfigurations, weak authentication mechanisms, and inadequate access controls pose significant security risks to network infrastructure.

Addressing these challenges requires a holistic approach to network device management that combines proactive monitoring, automation, security controls, and ongoing optimization efforts. Let’s move ahead and explore how network automation can enable IT teams to better manage their network operations.

How Does Network Automation Enhance Network Device Management?

Instead of relying on the traditional mode of network device management, an automation solution enables the IT operation team to better manage their network across the organization. According to a report, the network automation market is expected to hit around USD 28.63 billion by 2032. Some of the automation opportunities in network device automation are-

1. Device Block/Unblock

   Instead of manually performing this process, network automation can swiftly block or unblock devices from accessing the network. Also once this process is done, the user is notified through email whether access is granted or revoked. Additionally, the bot can also perform checks/troubleshoots when a network device is not reachable.

2. Device Configuration

   Automated configuration management simplifies the deployment and maintenance of network devices, ensuring uniformity and compliance with organizational standards. Instead of manually performing configuration, bots accept the Input- Inventory file with network devices, log into each network device, and execute the write config command. Once the output is released, the bot shares the updated Excel file over mail.

3. Device Configuration Backup

   Within any organization, it’s imperative to backup network configurations to minimize downtime during device outages. Automation and AI here facilitate backup operations, enabling swift configuration restoration in the event of a network disaster. Additionally, it offers configuration comparison capabilities, aiding in the identification and resolution of faults, ultimately optimizing network performance.

4. IP Allocation

   The allocation and management of IP addresses across devices can be simplified through network automation. The automated system allows the IT operation team to allocate server IP with the server name to use for application owners. This way it ensures efficient utilization of IP resources and minimizes conflicts.

5. Network Compliance Management

   Staying compliant with industry standards is important in network device management. Automation tools keep the network devices compliant, and on alert generation, it automatically logs into the device, checks loopholes in a configuration fixes the vulnerabilities, and avoids legal compliance.

6. Network Monitoring

   Imagine that there are many network administrators, operators, and users. As a result, it can be extremely tiresome and time-consuming to manually check configuration changes This can be resolved with automation in network device management. The automated system here helps to track changes immediately with change management and generates a change report for every device. Using AI bots, the IT operation team can get notifications on who made the configuration change and also take configuration backups once the changes are saved.

7. Traffic Management

   Automation in network traffic management operates through a combination of intelligent algorithms, predefined policies, and centralized control mechanisms to optimize the flow of data across network infrastructures. Network automation facilitates granular control over network traffic by enabling administrators to define and enforce access control lists (ACLs), route policies, and quality of Service (QoS) parameters, thereby optimizing network performance and ensuring regulatory compliance.

Security has become a paramount concern for organizations worldwide. The rising frequency and sophistication of cyber threats underscore the critical importance of robust security measures. Security is the backbone of IT operations, safeguarding sensitive data, critical systems, and the overall integrity of an organization. A security breach can result in severe consequences, including data breaches, financial losses, reputational damage, and legal ramifications. A recent report by IDC stated that companies of all sizes are ignoring one-third of security alerts and spending time investigating false positives.

As businesses increasingly rely on digital platforms and interconnected networks, the need for a proactive and comprehensive security strategy becomes even more crucial. So what’s the solution to make organizations secure? Let’s dig out the answer in this blog.

Why do Organizations Need Security Automation?

There are a number of reasons that can compel organizations to adopt, expand, and improve security measures.

• Unfortunately, for many organizations, the first indication of insufficient security measures often comes in the form of a security breach. According to research conducted by Splunk, within the past two years, 49% of respondents had faced a data breach, marking a notable increase from the previous year’s 39%. While some breaches may be minor and easily resolved, others can lead to substantial financial repercussions and even catastrophic outcomes. According to the IBM Cost of a Data Breach Report, the average total cost of a data breach reached $4.35 million in 2022.
• Security systems generate a lot of alerts daily, overwhelming IT teams. Distinguishing genuine threats from false positives is time-consuming and resource-intensive.
• Monitoring incident response times serves as an effective method to gauge the efficacy of your cybersecurity measures. When the mean-time-to-detect and mean-time-to-remediate incidents start to prolong, it signals a need for enhancements in your existing security infrastructure.
• Many organizations struggle with limited resources for security operations. This constraint can impede the ability to implement and maintain robust security measures effectively.

How Does a Security Automation Solution Help?

Automation emerges as a powerful solution to address the challenges faced by IT operational teams in maintaining robust security. By leveraging automation, organizations can enhance their security posture in several key areas:

1. Malware Detection

   Security automation utilizes advanced algorithms and machine learning techniques to analyze patterns and behaviors indicative of malicious software. These systems continuously monitor network traffic, file systems, and application behavior to identify potential threats. They can detect suspicious patterns such as unexpected file modifications, unauthorized access attempts, or anomalous network activity. Once malware is detected on a network it isolates the host and network traffic access. Additionally, if it receives any alert from file systems, it instantly identifies the system, finds malware, checks the reputation, and detonates the file.

2. Incident and Event Management

   Incident and event management streamline the entire lifecycle of security incidents, from detection and analysis to response and resolution. With automated security systems, the IT service desk can collect and correlate data from various sources, including security logs, intrusion detection systems, and network traffic analysis tools.

   They can employ predefined rules and policies to identify suspicious activities and security breaches in real time. Once an incident is detected, automated workflows are triggered to initiate incident response procedures, including containment, investigation, and remediation. By reducing the time it takes to identify and respond to security incidents, automation minimizes the potential impact of cyber threats and helps organizations maintain operational continuity.

3. Data Exfiltration

   Data exfiltration in IT refers to the unauthorized extraction or removal of data from a computer system, network, or organization’s environment. It occurs when sensitive or confidential information is intentionally or unintentionally accessed and transferred outside the intended boundaries of the system or network by an unauthorized entity.

   Security automation here can monitor the data flows and communication channels and apply encryption and access control policies to prevent data exfiltration attempts. If an alert is raised, then the automated system can instantly block data transfer, disable the compromised user, and reset the password for the system. This way security automation reduces the risk of data breaches.

4. Alert Monitoring

   With a lot of alert generation, IT service desk agents struggle to offer prompt service. Leveraging security automation, the IT service desk team can classify alerts based on their severity, relevance, and potential impact on the organization. Having security automation and AI in this process, service desk agents can resolve alerts for USB block/unblock, clean up requests for applications, and email alerts for account activation/deletion. Additionally, automation bots can perform on-demand checks for users who logged into certain workstations using their email or SMS.

5. Site Whitelisting and Blocking

   Automation in site whitelisting and blocking enables organizations to control access to websites and online resources based on predefined policies and criteria. Automated web filtering solutions inspect URL requests, web traffic, and DNS resolutions to enforce site whitelists and blacklists. They categorize websites based on content, reputation, and security risk factors, such as malicious content, phishing attempts, or inappropriate material.

As businesses increasingly rely on software systems for their day-to-day operations, IT organizations find themselves grappling with a multitude of challenges stemming from the substantial workload. The primary objective of IT organizations is to contribute to overall business growth, emphasizing system quality, rapid response times, and minimal system downtime. However, achieving these goals necessitates the continuous upgrading of processes.

Traditional server management systems are inherently intricate, comprising numerous infrastructure components. Managing these systems proves to be a complex task, demanding a high skill set. Additionally, these systems’ operational efficiency often requires different teams’ involvement to ensure seamless service delivery. This is where the significance of server automation becomes evident. In this blog, we will delve into the concept of the challenges faced by IT service desk agents in server management, and the benefits of using server automation.

Manual Server Management & Challenges

Server management is the process of overseeing and maintaining computer servers to ensure they run smoothly and efficiently. This includes a wide range of tasks, such as provisioning, patching, configuration management, monitoring, and performing backup and recovery.

With large and complex IT organizations, server management becomes more challenging for the IT operational team. According to a report, the server is the largest part of the cost of the data center, accounting for about 60%-70% of the hardware cost. Some of the other challenges include compatibility issues with network devices, security threats, performance optimization, server maintenance costs, and lack of skilled resources.

Combating these challenges gives rise to the need to adopt in server management. Let’s explore how server management automation can help in the IT service desk.

Benefits of Server Automation

Server automation offers a unified solution for a variety of tasks and processes, encompassing activities like application deployment, code building, and the management of both virtual and physical systems.

By orchestrating workflows with precision through orchestration automation, various tasks and processes in server management are automated, enhancing efficiency while minimizing the risk of human error. This is achieved by streamlining complex steps that are typically part of these processes. Some of the ways server automation benefits IT organizations are-

1. Task Automation for Configuration & Patch Management

   As per a report, around 53% of software developers face operating system compatibility issues during their projects. Automation tools facilitate the standardization of server configurations across the entire IT infrastructure. This involves defining and enforcing desired configurations, and ensuring that all servers align with organizational standards. Also using automation and AI in server automation, the IT operational team can deploy updates, patches, and security fixes across servers in a systematic and controlled manner. This way automation ensures that patches are applied promptly, reducing the window of vulnerability to potential exploits. It also allows for scheduling updates during non-critical hours to minimize disruption to services.

2. Create a Reliable & Secure Environment

   The creation of a reliable and secure server environment by enforcing standardized configurations is another challenge that IT organizations struggle with. Here automation enables the creation and enforcement of standardized server configurations. This consistency reduces the likelihood of misconfigurations that could introduce vulnerabilities or impact system stability. Also, these automation tools can be configured to check and enforce security policies automatically. This includes settings such as firewall rules, access controls, and encryption standards. By ensuring continuous compliance with security best practices, organizations can proactively mitigate risks and maintain a robust security posture.

3. Instant Feedback for Server Maintenance

   Receiving a request for server maintenance requests is a common instance for IT service desk agents. Automation here can improve responsiveness and customer satisfaction. Using automation, IT service desk agents can handle common server maintenance requests, such as system updates, software installations, configuration changes, user access, and others. Also, automated notifications and communication channels to keep users informed about the status of their maintenance requests. This transparency enhances the user experience and builds trust in IT service delivery.

4. Perform Server Health Check

   Monitoring and health checks are crucial for identifying and addressing potential issues before they impact server performance. Automation tools continuously monitor server performance metrics, including memory utilization, disk space, and network activity. Any deviation from predefined thresholds triggers alerts, allowing IT teams to proactively address issues before they escalate.

   Additionally, if there are instances of server downtime, then the automated monitoring system can autonomously generate alerts in advance so that the IT team can perform their tasks without any hassle.

5. Conduct Compliance Checks

   Streamlining compliance checks to ensure servers adhere to regulatory requirements and internal policies is another process where automation can be a great help. The integration of the automation in this process can check server configurations against predefined compliance policies. This includes verifying settings related to security, access controls, and software versions. Any deviations trigger alerts, allowing IT teams to remediate non-compliance promptly. This way automated compliance checks enable compliance reporting and internal auditing purposes, providing a transparent record of server configurations and their compliance status over time.

Conclusion

Server automation is a key enabler for IT service desk agents, addressing the challenges associated with manual server management. Using server automation IT organizations can automate routine tasks, can enhance efficiency, improve security, and create a reliable IT infrastructure. By leveraging its power, you can unlock a world of efficiency, security, and proactive service, ultimately transforming your service desk into a true champion of IT excellence. So, step into the future, embrace automation, and let your service desk rise above the chaos!

Robotic Process Automation in Banking

Did you know that human mistake in the banking industry results in over $878,000 in wasted time and labor each year? It is evident that the desire for change on the part of banking and financial services is not surprising.

Implementing robotic process automation makes sense since the human error can have a high financial cost in the BFSI industry. A Mckinsey report claims that RPA can automate more than 30% of tasks in about 60% of occupations.

The banking sector is anticipated to grow as business procedures across organizations change. The urge to automate superfluous procedures and provide end users control is expected to drive the sector over the next few years.

Automation adopters will concentrate on four areas: Quick Automation, Auto Decision, Data Security, and Instant Scalability.

BFSI is a tremendously competitive industry; banks and other financial institutions must continuously innovate, stay competitive, and deliver excellent user experiences. This is especially true given the significant counter-competition from FinTech and other virtual banking alternatives.

Banks and other financial institutions are under a lot of pressure to reduce costs and boost output. The lack of qualified workers, the need to increase process effectiveness, and the sharp rise in labor costs all contribute to the adoption of RPA in banking business.

Top 10 Benefits of RPA in Banking and Finance

You must consider which tasks in your banking and financial organization to automate.

1. Enhanced Productivity and Efficiency

   Another advantage of RPA systems is how easily and quickly they complete tasks since they listen to and carry out instructions without any space for ambiguity. Robotic accounting procedures don’t have any drawbacks, in contrast to manual ones. Gartner estimates that banking automation can prevent up to 25,000 hours of unnecessary work caused by human mistakes.

2. Scalability

   By addressing the need for bots to respond to events at record speed, robots’ high scalability enables you to manage big volumes during peak business hours. In addition, by relieving bank personnel of tedious activities, RPA deployment enables the bank to concentrate more on creative business growth ideas.

3. Accurate Information Extraction

   Because there is a vast amount of consumer data saved in systems, RPA, a combination of AI and machine learning, can readily store the necessary data for any desired query. Additionally, automated processing leverages third-party databases to gather information when there are errors or blank fields on bills in order to streamline Accounts Receivable and Accounts Payable procedures. However, similar operations can be completed quickly with RPA and particularly Intelligent Automation.

4. Cut Down Expenses

   The requirement for manual intervention will diminish as a result of the elimination of redundancy, which will allow banking and financial companies to drastically cut their additional expenses for resources, systems, and staff.
   Repeated tasks like manually processing data and adding fresh data could be avoided by employees. The financial sector can employ this technology to boost efficiency, consume less energy, and cut back on time, which can lower expenses by around 25–50%.

5. Increased Accuracy and Dependability

   It is natural for people to make mistakes. However, occasionally even the smallest errors could result in serious mistakes that would cost the company a significant amount of money. Unfortunate circumstances may even result in the customers’ excellent reputation being lost.
   But the introduction of RPA systems can quickly allay these concerns. The systems will conduct the procedure precisely and effectively with RPA. With the most recent technical marvels like AI and ML, massive amounts of data and processes may be managed effectively. Additionally, RPA solutions are accessible 24/7 and are not hindered by data failures. The data is effectively, automatically, and frequently backed up. Therefore, even if an unexpected event or downtime occurs, it will only stay a short while, and the process will resume as usual very quickly.
   According to Grand View Research, the banking and financial services sector, which accounted for over 29% of global revenue, was at the forefront of RPA adoption in 2019.

6. Better Compliance and Risk Management

   In order to comply with regulatory requirements and ensure meticulous record-keeping for potential audits, banking organizations must align their operational practices with applicable regulations. The banking industry, in particular, faces rigorous regulatory standards that necessitate strict adherence.
   Managing a lot of data coming from multiple resources and monitoring them on time takes a lot of effort from banking employees. Here RPA bot can be programmed to automatically perform real-time monitoring, and analyze the data to make sure business processes adhere to regulations.

7. Fraud Detection

   Having a lot of transactions happening across the banking operations, banking employees must keep all the data in check to prevent any fraudulent activities. Instead of banking employees handling the transaction and analyzing it in real-time, RPA can take over this repetitive process and analyze the transaction in real-time. Also, these RPA bots can also generate alerts whenever any fraudulent activities occur. That’s how RPA enables faster defect detection and maintains transparency.

8. Faster Loan Processing

   According to a poll conducted by Moody’s Analytics, manual data entry is the biggest challenge in loan origination. As banks receive these loan applications in high amounts, banking employees need to extract, analyze, and verify the data before processing loans. Here RPA can reduce the time involved in loan application processing using intelligent document processing to extract, analyze, and process the data, and the RPA bot can facilitate seamless communication with customers for information about approval and other information

9. 24/7 Assitance

   With a lot of processes encircling the banking operations, banking employees receive queries 24/7. Checking these queries extracting the information and routing the ticket to the right banking agents for instant resolution can be done by using an RPA bot. Also, this RPA bot can be available 24/7 and with pre-defined rules, it can offer self-service to customers as well.

10. Improved Data Analytics

    RPA can automate data extraction and transformation tasks, making it easier for banks to collect and analyze customer data. This facilitates data insights in one glance and enables banking organizations for data-driven decision-making, allowing banks to offer targeted products and services.

[Also Read – Top RPA Use Cases in Banking Industry in 2024]

Final Reflections

As opportunistic, system-based solutions that are quicker and simpler to adopt than extensive transformations, several banks, and financial institutions have started the journey of implementing RPA in their operations.

Robotic process automation, or RPA, services, which automate manual, repetitive, and time-consuming operations, can aid in the banking industry’s digital transformation if properly applied. Increased output, a considerable drop in error rates, and rapid turnaround times would result from automating such repetitive activities.
Throughout the RPA deployment process, having a partner with a track record of proficiency in RPA tools, technologies, and staffing is essential.

This will benefit banks and other financial organizations, but it will also show them when and how to transition from RPA to AI and other advanced technologies. And, who better than the RPA innovators – AutomationEdge!

For IT agents, doing repetitive tasks can be boring and take up a lot of time, regardless of whether they are entry-level or experienced. These tasks often follow a routine, and that’s where IT support automation comes into play. It makes the service desk processes more organized and saves your company time and effort.

However, it’s not a good idea to automate everything without thinking. You have to be selective about what to automate. That’s why we’ve got some service desk automation ideas to help you enhance your service and reduce mistakes.

In this article, we’re going to give you a big list of these ideas and show you how to use InvGate Service Desk to make them even better.

So, without any more delay, let’s get started!

What is Service Desk Automation?

Service desk systems were created to make life easier and help businesses provide excellent customer service.

Unfortunately, you will hear many customer service agents say, “We’re still stuck dealing with a huge pile of support requests, and simply getting around the system takes up a lot of our time.”

Here, service desk automation can fine-tune the ticketing process and reduce the manual effort. In a nutshell, service desk automation means using technology and methods to make IT support services work better. This usually includes using smart ticket systems, self-service websites, and tools that do tasks automatically. With these IT automation technologies, you can sort and organize support requests, answer common questions automatically, offer self-help options, and manage different tasks and approvals more efficiently.

Top 7 Service Desk Automation Ideas

Now, let’s have a look at some of the service desk automation use cases that we can automate using RPA.

1. Ticket Routing

   Is your business struggling with the manual distribution of support tickets among agents? Do you often find that support agents end up with tickets that should have gone to someone else?

   If these scenarios sound all too familiar, it’s time to consider an automated service desk. With automated ticket routing, support tickets are directed to the agents best equipped to handle them.

   Automated ticket assignment ensures that each support ticket is in capable hands. For example, technical support issues are assigned to agents with the technical expertise to address them. On the other hand, billing or returns-related tickets are routed to agents who are knowledgeable about return policies and procedures.

2. Email Management

   Email management can be challenging for IT service desk agents when it comes to filtering, routing, and offering responses to each customer. Here, automation can play a role in filtering and sorting mail into categories. Once these emails are categorized, using RPA bot service desk agents can offer immediate responses to customers. Also, the RPA bot can prioritize mail and schedule its delivery for a specific time.

3. Alerts and Notifications

   In the quest to automate support services and deliver seamless customer experiences, effective communication is paramount. This is where notifications come into play. Notifications are predefined automated alerts, messages, or responses that are triggered when specific conditions are met. These notifications serve a dual purpose, keeping both support agents and customers well-informed. They are typically dispatched via email or text messages, offering a means to track the progress of a support ticket.

   IT service desk agents can use automation to provide multiple conditions under which they can send and receive email notifications. RPA bots can easily create auto responses on ticket creation, assignment, and response to users.

In the ever-evolving landscape of IT operations, businesses are constantly searching for innovative solutions to streamline their processes, improve efficiency, and enhance overall productivity. Two critical technologies that have gained significant attention are Workload Automation and Service Orchestration Automation platforms. While both offer substantial benefits, understanding the differences and similarities between the two is vital in making the right choice for your organization.

In this blog post, we will explore Workload Automation and Service Orchestration Automation, highlighting their respective features, use cases, and the scenarios where each solution excels.

What is Workload Automation?

Workload Automation (WLA) is a technology that simplifies and automates complex job scheduling, execution, and monitoring tasks within an IT environment. It primarily focuses on the automation of batch jobs and the management of workloads, helping organizations optimize resource utilization, reduce errors, and meet service level agreements. The key features of workload automation include:

1. Job Scheduling:

   Workload automation platforms excel at scheduling and managing routine tasks, such as data backups, report generation, and system maintenance.

2. Dependency Management:

   They allow users to define job dependencies, ensuring tasks are executed in the correct order.

3. Monitoring and Alerting:

   WLA platforms provide comprehensive monitoring and alerting capabilities to detect issues and take corrective actions.

4. Resource Optimization:

   WLA helps in optimizing resource usage by allocating tasks efficiently based on available resources.

Some common use cases for Workload Automation are-

• Data backups and archiving
• Routine batch processing tasks
• Report generation
• Database maintenance
• Job and process automation

What is Service Orchestration Automation?

Service Orchestration Automation (SOA) is a broader concept that involves coordinating and automating multiple services and processes across an organization. It focuses on connecting disparate systems, applications, and data sources to ensure seamless workflows, rapid decision-making, and enhanced collaboration.

Key Features of Service Orchestration Automation:

1. Integration Capabilities:

   Service orchestration automation platforms have robust integration capabilities, enabling them to connect various systems and services seamlessly.

2. Process Automation:

   They can automate complex business processes that involve multiple steps, often across different departments

3. Workflow Management:

   SOAP offers advanced workflow management, enabling businesses to streamline and optimize their operations.

4. User-Centric:

   Service Orchestration Automation platforms prioritize user experience and often involve self-service capabilities for employees or customers.

Common Use Cases for Service Orchestration Automation:

• Onboarding and offboarding employees
• Order processing and fulfillment
• Incident management
• Customer service and support workflows
• Complex, multi-step business processes

There is always a significant amount of confusion when it comes to automation software. The terminology used to describe these technologies keeps expanding, and this includes terms like Robotics Process Automation (RPA), Intelligence Automation (IA), and Hyperautomation.

These various terms are coined and disseminated by analysts, software vendors, and solution integrators, each trying to put their unique spin on the market.

To gain clarity in this rapidly evolving landscape, let’s provide a concise overview of some of these terms to get a real sense of what they actually mean.

Understanding Automation & Hyperautomation

Automation involves the utilization of technology to carry out tasks autonomously without human intervention. It stands as a potent tool that has revolutionized diverse industries, consistently enhancing efficiency, productivity, and cost-effectiveness. Typically, automation concentrates on uncomplicated, task-driven procedures, allowing robots or other technological systems to execute repetitive tasks swiftly and accurately.

In its initial stages, automation primarily concentrated on automating straightforward, standalone tasks, often referred to as task-oriented automation. This approach was aimed at automating routine processes but still required human oversight for handling intricate scenarios or orchestrating activities across multiple systems. These responsibilities are frequently fulfilled by bots, which are programmed to adhere to specific rules and procedures.

Hyperautomation is indeed a significant advancement in the field of automation, leveraging a combination of technologies to improve business processes. Let’s break down the key components you mentioned:

1. Robotic Process Automation (RPA)

   RPA is the foundation of hyperautomation and focuses on automating repetitive, rule-based tasks. RPA bots can interact with applications, enter data, and perform tasks just as a human worker would. This is crucial for streamlining routine processes and reducing human error. RPA is often used for tasks like data entry, file organization, and report generation.

2. Artificial Intelligence (AI)

   AI is a critical component of hyperautomation because it enables systems to understand, interpret, and learn from data. This cognitive capability allows AI to handle more complex tasks, such as natural language processing (NLP) and image recognition. NLP, for instance, can be used for chatbots, sentiment analysis, and understanding unstructured text data, while image recognition can be applied in areas like quality control and content classification.

3. Machine Learning (ML)

   ML is another integral part of hyperautomation, as it empowers systems to learn from the data they process without explicit programming. ML algorithms can analyze large datasets to detect patterns and trends, which is particularly valuable for decision-making, analytics, and forecasting. Additionally, ML models can adapt and improve over time, making them suitable for tasks that involve evolving regulations, business models, or customer behaviors.

Together, these technologies create a powerful synergy that allows organizations to automate not only routine, repetitive tasks but also complex processes that require cognitive abilities.

Hyperautomation vs. Automation- The Difference

Hyperautomation and automation are related concepts, but they differ in scope and capabilities. Here are the key differences between the two:

1. Scope and Complexity:

   • Automation

     Automation refers to the use of technology to perform specific tasks or processes without human intervention. It is typically applied to repetitive, rule-based, and well-defined tasks. Examples include automating data entry, email filtering, or report generation.

   • Hyperautomation

     Hyperautomation is a more advanced and comprehensive approach that involves the use of a combination of technologies, such as robotic process automation (RPA), artificial intelligence (AI), machine learning, and process orchestration, to automate not only repetitive tasks but also complex business processes. Hyperautomation aims to automate end-to-end processes that may involve multiple systems, data sources, and decision-making steps.

2. Integration and Orchestration:

   • Automation

     Traditional automation may be limited to a single task or a single software application. It often operates in isolation
     

   • Hyperautomation

     Hyperautomation involves the integration and orchestration of various automation technologies and systems to create seamless end-to-end processes. It can connect with multiple software systems, databases, and APIs to streamline business workflows.

3. Decision-Making Capabilities:

   • Automation

     Basic automation typically follows predefined rules and instructions and lacks the ability to make complex decisions or adapt to changing conditions.

   • Hyperautomation

     Hyperautomation leverages AI and machine learning to enable decision-making capabilities. It can analyze data, learn from historical patterns, and make intelligent choices, allowing it to handle more complex and dynamic processes.

4. Scalability and Flexibility:

   • Automation

     Traditional automation solutions may require significant effort to adapt to new tasks or processes.

   • Hyperautomation

     Hyperautomation is designed to be highly scalable and flexible. It can quickly adapt to changing business needs and accommodate a wide range of processes.

5. Continuous Improvement:

   • Automation

     Basic automation solutions may require manual adjustments when processes change, and they may not actively seek opportunities for improvement.

   • Hyperautomation

     Hyperautomation systems are designed for continuous improvement. They can identify inefficiencies, bottlenecks, and opportunities for optimization and suggest or implement improvements automatically.

6. Holistic Approach

   • Automation

     Automation is often used on a case-by-case basis to address specific tasks or challenges.

   • Hyperautomation

     Hyperautomation takes a holistic approach to improving business processes. It focuses on optimizing entire workflows and can provide a more comprehensive solution to business challenges.

In summary, while automation focuses on simplifying individual tasks, hyperautomation aims to revolutionize entire business processes through the integration of multiple technologies and advanced decision-making capabilities. Hyperautomation is a broader, more intelligent, and forward-looking approach to process optimization and efficiency.

When to Choose Hyperautomation or Automation?

The choice between traditional automation and hyperautomation depends on your business’s specific needs:

• Traditional Automation: Ideal for routine, rule-based tasks and situations where minimal adaptability is required. It can be a cost-effective solution for simple, repetitive processes.
• Hyperautomation: Best suited for complex, dynamic processes that require integration, adaptability, and scalability. It’s a valuable asset for organizations seeking to remain competitive in an ever-changing landscape.

Conclusion

In conclusion, while both automation and hyperautomation offer substantial benefits, they differ in their approach and scope. The decision to adopt one or the other depends on your organization’s objectives and the nature of the tasks you wish to streamline. As technology continues to advance, the line between these two concepts may blur, but for now, understanding their differences is crucial for making informed decisions in an increasingly automated world.

In the contemporary world of business, expedited loan approvals and streamlined lending procedures stand as pivotal objectives for both lending institutions and loan applicants. Consequently, lenders are persistently in search of methods to enhance their operations and boost productivity. Automation, specifically within the loan underwriting phase, holds substantial potential to revolutionize this process. In this blog, we will discuss loan underwriting, challenges that financial institutions face and how automation can accelerate loan decision-making.

What is Underwriting and How it Works?

Underwriting is the procedure by which a person or a company accepts financial risk in exchange for a fee. Most of the time, this risk is associated with loans, insurance, or investments. The word “underwriter” comes from the practice of having each risk-taker sign their name under the entire amount of risk they were ready to assume for a given premium.

Even though this mechanism has evolved, Underwriting plays a critical role in the financial industry. The entire Underwriting process is based on the risk related to the borrower returning the loan on time or default.

Underwriters assess loans, particularly mortgages, to gauge the possibility of a borrower paying as agreed and the availability of sufficient collateral in the case of default.

In addition, underwriters look at a policyholder’s health and other criteria to distribute the risk as widely as feasible in insurance. Underwriting securities, which are most commonly done through initial public offerings (IPOs), aid in determining a company’s underlying value compared to the risk of funding its IPO.

Challenges with Manual Loan Underwriting

Underwriting is a critical process in the financial institution where companies assess and evaluate risks associated with loan applicants. While underwriting plays a crucial role in ensuring the financial stability of BFSI companies, there are several challenges and complexities associated with this process. Some of these challenges are-

1. Data quality and availability
2. Regulatory Compliance
3. Data Privacy
4. Risk Assessment

Although manual underwriting may seem appealing for clients with unconventional financial circumstances, like those who are new to establishing credit or have a history of financial difficulties, it can be a significant burden on providers in terms of time and resources.

How Automated Loan Underwriting Works?

Automated underwriting systems are computerized tools used by financial institutions, such as banks and insurance companies, to evaluate and make decisions on loan or insurance applications. These systems streamline the underwriting automation process by using algorithms and data analysis to assess the creditworthiness, risk, and eligibility of applicants. Here’s how they work:

1. Data Collection

   The underwriting process starts by collecting data from applicants. This data typically includes personal information, financial records, credit reports, employment history, and other relevant information. This data can be provided by applicants directly or obtained from various databases and credit bureaus.

2. Data Verification

   Using intelligent document processing solutions, financial institutions can verify the accuracy of the data provided by applicants. It can check for inconsistencies, errors, or missing information that could affect the underwriting decision.
   

3. Risk Assessment

   With automation and AI in underwriting, underwriters use sophisticated algorithms to assess the risk associated with each application. It considers factors such as credit scores, income, debt-to-income ratios, and employment stability to determine the applicant’s risk profile. These algorithms are often based on statistical models and historical data.

4. Rules and Guidelines

   Financial institutions can use AI to program their bot with specific rules, guidelines, and lending or insurance policies. These rules can be adjusted to reflect the institution’s risk tolerance and business objectives. For example, a bank may set a minimum credit score requirement for mortgage applicants.

5. Decision Making

   Based on the data, risk assessment, and predefined rules, the AUS generates an automated underwriting decision. This decision can fall into several categories, including approval, denial, or referral for manual underwriting.

   • Approval: If the applicant meets all the criteria and the risk assessment falls within acceptable parameters, the system can automatically approve the application.
   • Denial: If the applicant’s risk profile is too high or doesn’t meet the institution’s criteria, the system can automatically deny the application.
   • Referral: In some cases, when the application is borderline or has certain complexities, the system may refer it for manual underwriting. This involves human underwriters who will review the application in more detail.

6. Documentation

   The automated underwriting system may also identify required documentation or additional information needed to finalize the underwriting process. For instance, it may request pay stubs or bank statements for income verification.

7. Communication

   The system communicates the underwriting decision to the applicant. If the decision is automated, it is usually provided instantly. If the application is referred for manual underwriting, the applicant will be informed about the additional steps required.

8. Monitoring and Compliance

   Automated underwriting systems can be often programmed to monitor loans or insurance policies for ongoing compliance with the institution’s policies and regulations. This may include periodic reviews of borrower creditworthiness or policyholder risk.

Overall, automated underwriting systems are designed to increase efficiency, reduce the time required for decision-making, minimize human errors, and ensure consistent application of lending or insurance policies. However, they are not completely devoid of human involvement, as some cases may still require manual review by underwriters, especially when dealing with complex or exceptional situations.

Automated Loan Underwriting’s Advantages

Using automation technologies like RPA and AI, financial institutions can leverage a lot of benefits while performing the underwriter process

1. Increasing Productivity

   It’s a win-win situation for both lenders and borrowers. The automated credit underwriting approach saves time for both parties, allowing for faster decision-making and fewer steps than traditional Underwriting.
   The automated Underwriting process also ensures that the borrower’s desire for more rapid processing is addressed while maintaining accuracy that does not jeopardize the lender’s balance sheet.

2. More Effective Decision-Making

   Algorithms are incapable of making clerical errors. As a result, a human, no matter how efficient, might have a bad day, costing a lender millions of dollars in non-performing loans. However, automated algorithms are becoming better at forecasting which loans will do better because of machine learning capabilities and increased data on such loans.

3. Fraud Detection that is More Intelligent

   Loan fraud is on the rise. In and of itself, credit card fraud is a multibillion-dollar business. However, fraud risk is significantly and systematically reduced by automation. How? The robotic operations use powerful predictive analytics to quickly identify hazards associated with disbursing a loan to a customer. Wherever a mismatch is placed, these systems raise red lights, allowing for more accurate fraud detection.

4. A customer-centric experience

   Loan paperwork may be merely a back-office procedure. However, it’s vital to make sure that all of the rules are followed. With the Government imposing strict measures for banking institutions and charging hefty fines on erring institutions, there are zero scopes of error.
   Hence, underwriting and loan disbursement documentation are automated, ensuring a seamless solution for the bank.

5. Underwriting Consistency

   The bank’s capacity to underwrite, approve, and document credit in a more personalized manner while remaining compliant with the bank’s standards is enhanced by automation. It compensates for the bank staff’s inability to interpret bank policies, which may differ from one employee to the next.
   Furthermore, automation considers all loan-risk elements related to loan policies, which may overlook traditional Underwriting yet critical to a loan decision.

6. Compliance with Regulatory Standards is Easier and More Effective

   The best aspect about automation is that you may update a rule, and it will be applied across the board based on the filters you specify. As a result, regulatory requirements that may be neglected in a traditional system are always checked in automated methods, resulting in improved compliance.

7. Improved Auditing

   Automation of documenting processes simplifies the documenting and lending operations, allowing for quicker and less time-consuming audits. This is beneficial to traditional banks and credit unions since it improves accuracy and reduces fraud.

8. Workflows That are More Consistent and Well-Defined

   To put it another way, automation operates through a specified process that makes Underwriting well-defined, resulting in a more consistent and efficient operation. As a result, it overcomes and slashes out all weaknesses of legacy banking systems.
   

Conclusion

In summary, the automation of loan underwriting procedures offers substantial advantages to lending institutions. It enhances the efficiency and precision of loan approvals, reduces the likelihood of errors, and ultimately enhances overall business performance and customer satisfaction. Leveraging AI and machine learning algorithms, electronic document management systems, automated decision-making processes, digital signatures, and e-signatures, as well as automated validation, empowers lenders to streamline the loan underwriting process effectively.

AutomationEdge is one of the leading automation platforms in automating banking, insurance and financial services processes. To know more, request a demo.