Did you know that Taylor Swift was the most streamed artist on Spotify last year? Her fans played her song on the music app over 26.1 billion times!
But how does Spotify know all this information?
Since 2017, Spotify has been leveraging RPA, categorizing it into enterprise and citizen programs. By unleashing over 100 bots, the music titan saves over 45,000 hours of labor, unlocking 24,000 hours of additional staff capacity.
The 2022 McKinsey Global Industrial Robotics Survey highlighted that many industrial companies are planning to allocate about 25 percent of their capital spending to automated systems over the next five years.
Yet, as industries globally embrace RPA, understanding and mitigating the inherent RPA risks becomes paramount. The risks of RPA, particularly in security, pose significant challenges. Unauthorized data access, weak authentication, and data leakage are just a few of the many RPA security risks.
This article will delve into RPA implementation risks, providing insights into effective RPA risks and controls.
Table Of Content
- What is RPA and What Can It Do for Enterprises?
- RPA Use Cases for Enterprises
- Why is there a Risk to Using RPA?
- Top 5 RPA Risks Faced by Enterprises
- How to Mitigate RPA Risks?
- Kanerika Case Studies for RPA Implementation
- Kanerika: The Leading RPA Implementation Partner in the USA
- FAQs
What is RPA and What Can It Do for Enterprises?
Is RPA really reshaping business landscapes? Reports conclude that 85% of large companies will focus on RPA in 2022. But why?
RPA enables businesses to focus on strategic goals by reducing staffing costs, minimizing human errors, and increasing work volume handling capacity.
Fabrizio Biscotti, research vice president at Gartner, has duly noted the following on this: “Enterprises can quickly make headway on their digital optimization initiatives by investing in RPA software, and the trend isn’t going away anytime soon.”
Notably, RPA has been instrumental in sectors like banking, insurance, and retail, demonstrating its versatility.
In 2024, popular RPA tools like UiPath, Blue Prism, and Automation Anywhere stand to offer user-friendly interfaces and adaptability across various industries. These tools are designed for tasks ranging from customer service to payroll processing, offering increased productivity and a higher return on investment.
RPA Use Cases for Enterprises
Robotic Process Automation (RPA) offers transformative potential across various sectors. Here are five detailed use cases, illustrating how RPA reshapes enterprise operations:
1. Finance and Accounting Automation
In finance, RPA streamlines processes like accounts payable, receivable, and general ledger entries.
For example, a multinational bank employs RPA to automate its daily reconciliation tasks. The bots reconcile accounts, process transactions, and update ledgers in real-time, leading to error reduction, faster processing times, and significant cost savings.
2. Customer Service Enhancement
Enterprises use RPA for automating customer service tasks, such as ticketing, query handling, and updating customer records.
A telecommunications company implements RPA bots to handle routine customer inquiries and complaints, allowing human agents to focus on complex issues. This results in improved response times and customer satisfaction rates.
3. Supply Chain Management
In the logistics and supply chain sector, RPA is employed for inventory management, order processing, and tracking shipments.
A leading e-commerce company uses RPA bots to update stock levels, process orders, and provide real-time tracking information to customers, ensuring efficient and timely delivery.
4. Human Resources Processes
RPA streamlines HR processes such as onboarding, payroll processing, and benefits administration.
An international IT firm utilizes RPA for automating its employee onboarding process. The bots handle document verification, account creation, and initial training schedules, making the onboarding process faster and more efficient.
5. Healthcare Patient Scheduling and Records Management
Healthcare institutions leverage RPA for patient scheduling, record-keeping, and billing.
A large hospital chain uses RPA bots to schedule appointments, update patient records, and process insurance claims, leading to enhanced patient care and reduced administrative burden.
Why is there a Risk to Using RPA?
The digital revolution inevitably brings increased risks to IT infrastructures, as seen in the 2022 Twitter breach, where 5.4 million users’ data was compromised.
This incident highlights the vulnerabilities in digitized systems, underscoring the RPA risks and challenges in security and data protection.
However, RPA also aids in mitigating these risks by reducing human error and improving compliance, demonstrating its dual role as both a contributor to and a protector against digital vulnerabilities.
Let’s further discuss the proper implementation of RPA and stringent RPA risk assessment in detail:
Top 5 RPA Risks Faced by Enterprises
As per Ernst & Young, up to 50% of RPA projects fail. Enterprises employing RPA face risks like security vulnerabilities, compliance issues, and operational disruptions, often leading to financial, operational, and reputational damages if not managed effectively.
RPA Risk No. 1 – Cybersecurity Risks and Data Exposure in RPA
RPA significantly enhances business efficiency, but it also introduces substantial cybersecurity challenges. As Deloitte highlights, the interconnection inherent in RPA systems escalates cyber threats, a key aspect of RPA risks.
The unprotected source code of RPA bots is a critical vulnerability, presenting opportunities for malicious actors to alter scripts and perform unauthorized actions.
An alarming RPA risk is the potential for credential theft, which can lead to significant security, privacy, and fraud risks. This underscores the importance of robust RPA risk and controls. Alarmingly, about 74% of data breaches start with privileged access abuse, according to cybersecurity research.
The core issue lies in the privileged access that RPA bots have to company systems and databases. Similar to human roles with elevated access rights, such as IT administrators or financial managers, RPA bots can be misused to gain unauthorized entry into internal systems.
Cybercriminals exploiting these vulnerabilities can cause unauthorized disclosure of confidential information. This not only threatens data privacy but also contravenes regulations like GDPR and HIPAA.
RPA Risk No. 2 – Compliance and Regulatory Risks
Organizations using RPA need to ensure their bots comply with all relevant regulations, such as data privacy laws and industry standards. Failure to do so can result in hefty fines and reputational damage.
This is especially important for industries such as healthcare, where laws like HIPAA can land healthcare organizations in trouble for not managing patient data effectively.
Another item on the list of RPA risks is auditing. Traditional auditing methods may not be effective for automated processes handled by bots.
This can make it difficult to track and verify the activities of RPA bots. This, in turn, can make it challenging for organizations to discover certain activities of RPA bots.
RPA Risk No. 3 – Incorrect or Inadequate Tool Selection during RPA Implementation
Choosing the right RPA tool is a critical step in RPA implementation, yet it’s often where many organizations falter.
This is a challenge amplified by “RPA washing” and crowded vendor offerings, both of which lead to the presence of inadequate RPA tools in the market that advertise many features but perform poorly.
Tools offering limited capabilities, like basic screen-scraping can lead to high maintenance and RPA implementation risks. The integration complexity with multiple vendors, each requiring specific training, increases the RPA risk management burden.
This lack of standardization in processes and practices adds to the challenges.
Additionally, the ‘stickiness’ of vendors makes switching RPA tools costly and time-consuming, involving re-training and process re-engineering.
RPA Risk No. 4 – Operational Risks in RPA Deployment
RPA needs to run every hour of every day of every year. That’s quite a heavy responsibility, and so is its maintenance.
RPA solutions can be costly, ranging from $5,000 to $15,000 per unit, with licensing fees comprising only 25-30% of the total cost. The remaining cost is attributed to yearly license renewals, training, consulting for implementation, infrastructure setup, and third-party integrations.
RPA bots are only as good as the rules they are programmed with. If the underlying processes change or unexpected errors occur, the bots can malfunction and create problems.
These costly and time-consuming break-fix cycles can limit the true potential of RPA.
Operational risks in RPA also arise when bots are deployed without a robust operating model.
This lack of preparation can lead to blurred roles and responsibilities, especially when humans and bots collaborate in production environments. Such confusion directly impacts RPA risk management effectiveness, leading to job displacement for human employees, and growing workforce resentment.
RPA Risk No. 5 – RPA Sourcing and Implementation Risks
RPA sourcing risks often arise in organizations attempting to internally manage RPA without the requisite expertise. The Heavy Reading survey underscores a deficiency in DIY automation skills as a major item in RPA risks and challenges.
Inexperienced internal teams or selecting external agencies with unverified success in RPA projects can lead to inadequate RPA risk management.
Additionally, choosing the wrong consulting partner or delaying the involvement of external advisors exacerbates these RPA implementation risks.
Cloud data management, while centralizing automation and ensuring continuous security, poses compliance challenges under regulations like the UK Data Protection Act, Swiss Federal Act on Data Protection, and Canadian PIPEDA. It is important to work with a trusted and experienced RPA consulting firm to monitor and address these risks with RPA implementation and maintenance.
How to Mitigate RPA Risks?
Mitigate RPA Risks with Regular Updates and Patches
A crucial aspect of RPA risk management involves regularly updating and patching RPA software.
Updates typically include vital security patches and error eliminations, essential for maintaining system integrity. Neglecting these updates makes the RPA system a more accessible target for cyberattacks.
Reinforce Security Policies
Deloitte reports significant improvements in compliance (92%). To sustain this gain, updating existing security policies in line with the new IT infrastructure is crucial.
An effective RPA risk management approach involves creating a security governanceframework, including regular risk assessments, audits of RPA processing activities, and a security requirement checklist tailored for RPA.
Configure Minimum Access Rights for Bots
Mitigating RPA risks effectively involves applying the principle of least privilege. This means configuring RPA bots with only essential access rights for their tasks, which is crucial in preventing excessive data exposure.
Regular audits of RPA bots’ activities are recommended to monitor their access levels, further reducing potential damages from cyber attacks.
Additionally, creating unique credentials for each bot, stored in a secure, encrypted location and not in the source code, is vital. Limit access to these credentials and employ robust authentication methods like two-factor authentication to enhance security.
Work with the Right RPA Implementation Partner
Selecting a proficient RPA implementation partner is vital for managing RPA risks.
Kanerika, a leading RPA implementation partner in the USA, excels in this realm. We offer comprehensive RPA services, ensuring 25-70% cost efficiency, 70-90% process agility improvement, and 40% growth in employee productivity.
Kanerika’s expertise spans across major RPA platforms like Automation Anywhere, UiPath, and Blue Prism.
With over 150 processes automated and 1000+ bots in production, backed by a team of certified experts, Kanerika stands as a premier choice for businesses seeking secure solutions free from RPA risks.
Kanerika Case Studies for RPA Implementation
Leading IT Solutions Company – Streamlined Recruitment with RPA
The IT solutions company faced HR challenges due to manual recruitment processes, leading to delays and inefficiencies. Candidate sourcing from diverse portals posed a risk to hiring quality, while the absence of centralized data hindered decision-making.
To address this, Kanerika implemented UiPath-powered automation, streamlining candidate screening.
An HR bot was deployed to receive and manage resumes from various sources, enhancing candidate management. Accurate candidate evaluation and efficient handling were ensured, resulting in higher quality hires.
The outcomes included a 30% increase in conversion rates, a 46% reduction in time-to-hire, and a remarkable 70% decrease in HR workload.
Leading Global Insurance Company – AI/ML-Powered RPA for Fraud Detection
The global insurance company faced financial losses and inefficiencies due to manual claims processes. The absence of a fraud detection system exposed the company to fraudulent claims, while rigid processes and human intervention hindered data analysis.
To combat these challenges, Kanerika implemented an AI/ML-driven RPA for fraud detection, reducing financial losses. Predictive analytics, AI, NLP, and image recognition were harnessed to monitor customer behavior, enhancing satisfaction and resulting in significant cost savings.
The outcomes included a 20% reduction in claim processing time, a 25% improvement in operational efficiency, and a noteworthy 36% increase in cost savings.
Kanerika: The Leading RPA Implementation Partner in the USA
Kanerika stands out as a leader in the RPA implementation domain in the USA, renowned for its deep expertise in deploying RPA solutions across a spectrum of industries.
We ensure that all RPA solutions are rigorously compliant with the latest data protection regulations. This meticulous attention to compliance and privacy safeguards client data and ensures enterprise success without any RPA risks.
By choosing Kanerika as your RPA partner, you benefit from:
Tailored RPA Strategies: Customized solutions that align with your unique business needs and goals.
Compliance Assurance: Robust frameworks ensuring all RPA deployments meet regulatory standards.
Privacy Protection: State-of-the-art security measures to protect sensitive data and maintain confidentiality.
Take the first step towards unlocking new efficiencies and capabilities – sign up for a free consultation with Kanerika today!
FAQs
What are the privacy concerns of using AI?
AI systems often process large amounts of personal data. Concerns include unauthorized data access, lack of consent in data usage, profiling and decision-making without human oversight, and potential biases in AI algorithms that might infringe on individuals' privacy rights.
What are the risks of generative AI and privacy?
Generative AI can create realistic images or texts, potentially leading to the creation of deepfakes or synthetic media, which can be used to invade privacy, spread misinformation, or impersonate individuals without consent.
How do you fix privacy issues in AI?
Addressing privacy issues in AI involves implementing robust data governance policies, ensuring data anonymization, obtaining explicit consent for data usage, conducting regular privacy impact assessments, and incorporating privacy by design principles in AI development.
What are the legal issues surrounding AI?
Legal issues include liability for AI decisions, intellectual property rights, compliance with privacy regulations (like GDPR), data protection, and the ethical use of AI, especially in terms of bias and discrimination.
Is AI good for privacy?
While AI poses privacy challenges, it can also enhance privacy protection through advanced data monitoring, fraud detection, and enforcing privacy policies. AI can automate data anonymization and assist in regulatory compliance.
What is an example of AI and privacy?
An example is AI-driven facial recognition technology used for security purposes. While it can enhance security, it raises privacy concerns regarding the tracking and profiling of individuals without their consent.
What is privacy preserving AI?
Privacy-preserving AI refers to techniques that allow AI systems to learn from data without compromising the privacy of the data subjects. This includes methods like differential privacy, federated learning, and homomorphic encryption.
What is private artificial intelligence?
Private artificial intelligence refers to AI systems designed to operate with a strong emphasis on data privacy and security. This involves using encrypted data, ensuring minimal data exposure, and adhering to strict privacy regulations.
How does AI affect our everyday lives?
AI impacts daily life through applications like personalized recommendations on streaming services, voice assistants, smart home devices, navigation apps, and in sectors like healthcare, finance, and transportation.
What is an example of privacy?
An example of privacy is an individual’s right to keep their personal information, such as health records or financial data, confidential and protected from unauthorized access.
