5 Ways Intelligent Automation Can Transform Your Financial Services Business

Intelligent automation technologies like Robotic Process Automation, artificial intelligence, and machine learning are transforming how financial services businesses operate. When implemented strategically, these technologies have the power to streamline processes, improve efficiency, enhance customer experiences, and minimize risks. At its core, intelligent automation enables financial services firms to do more with less - achieving higher productivity and agility while reducing costs and reliance on manual labor.

What is Intelligent Automation?

Intelligent automation utilizes artificial intelligence, robotic process automation, and other technologies to identify and automate routine business tasks, resulting in more effective and efficient operations. It employs technologies like machine learning and natural language processing to enable systems and software robots ('bots') to think, act and adapt like humans. 

Unlike traditional IT automation which performs predefined tasks, intelligent automation relies on cognitive capabilities that allow systems to learn from data, spot patterns, make autonomous decisions, and self-correct errors. This convergence of artificial intelligence, robotic process automation, and other emerging technologies empowers automated systems to handle flexible, changing, and exception-based tasks with minimal human intervention. 

Together, these capabilities allow intelligent automation to replicate human decision-making and improve over time based on outcomes. The overall aim of intelligent automation is to augment human capabilities and reduce manual work and costs while improving consistency, speed, and quality of output.

Automation technologies

Here are some of the key automation technologies used in intelligent automation:

• Robotic Process Automation (RPA): RPAs are software robots that operate through rules-based algorithms to mimic human actions and automate repetitive manual tasks. They integrate with existing applications to complete tasks at much higher volumes and speeds with rule-based precision.
• Artificial Intelligence (AI): AI technologies like machine learning and deep learning algorithms enable systems to think, act and improve over time with exposure to data. They empower automated processes with abilities like pattern recognition, natural language processing, and decision-making.
• Machine Learning: A type of AI that allows software applications to become more accurate over time without being explicitly programmed. Machine learning algorithms enable automated systems to mimic human cognitive functions like learning from data and experience.
   

Five Ways Intelligent Automation Can Transform Your Financial Services Business

Here are five ways intelligent automation can transform financial services businesses:

Transform Customer Journeys

By automating repetitive manual tasks through technologies like robotic process automation, artificial intelligence, and machine learning, intelligent automation can dramatically improve the speed, convenience, and personalization of customer engagement for financial services businesses. Customers benefit from faster responses, 24/7 availability, and a more seamless experience. Customer service chatbots and AI-powered robo-advisors provide on-demand assistance and support. 

Automated fraud detection and anomaly identification based on AI and behavioral analytics enhance security while minimizing customer friction. Overall, intelligent automation has the potential to elevate interactions across digital channels and enable financial services firms to gain an edge through superior customer experiences.

Enhance Employee Experiences

One of the major advantages of intelligent automation for financial services businesses is its potential to improve employee experiences and productivity. By automating repetitive manual tasks through technologies like robotic process automation and artificial intelligence, workers are freed from rules-based data entry and administrative work that offer little satisfaction. They can instead devote time to value-added activities that leverage human skills like critical thinking, problem-solving, and empathy. This shift to more engaging work can boost worker satisfaction, retention, and engagement. 

Additionally, automation offers opportunities to upskill employees for roles interfacing with AI systems. Overall, when implemented appropriately, intelligent technologies have immense potential to transform employee work lives within financial services through redeployment, skill development, and better work design.

Unify Operations

Intelligent automation technologies like robotic process automation, artificial intelligence, and machine learning have the potential to integrate and automate processes across siloed systems within financial services businesses. By automating data hand-offs and exchanges between different units, intelligent automation increases coordination, reduces redundancy, and speeds up cross-functional processes. It also provides a unified view of data through integration, supporting better decision-making. 

When implemented well, the benefits include improved cost efficiencies, faster responses, and reduced errors. The key is employing a combination of automation technologies to achieve end-to-end visibility and integration across an organization. In essence, properly implemented intelligent automation has immense potential to break down information and operational silos to create a truly unified financial services business.

Reduce Risk

Intelligent automation technologies like artificial intelligence, machine learning, and robotic process automation have considerable potential to lower operational and financial risks for financial services businesses. Automated compliance monitoring across processes and transactions helps ensure adherence to regulations and minimize compliance risks. AI-powered fraud detection and anomaly identification systems analyze data in real-time to detect suspicious activity. 

Automated exception handling and remediation reduce errors. The benefits arise from the technologies' ability to analyze vast amounts of data, detect patterns, flag anomalies and take appropriate actions. Properly implemented intelligent automation, therefore, has immense potential to reduce exposure to various risks for financial institutions by automating error-prone manual tasks, obtaining deeper data-driven insights, and enabling faster detection and responses.

Improve Data Quality

Intelligent automation utilizes technologies like artificial intelligence, machine learning and robotic process automation to identify, extract, validate, and integrate data from disparate sources within financial services businesses. These capabilities provide multiple ways to improve the overall quality of an organization's data. For example, AI-powered data extraction tools can accurately parse data from documents and databases. Automated data validation routines detect incomplete, inaccurate, or duplicate information. 

Machine learning algorithms aid data classification and labeling to create consistent data taxonomies. Automated data reconciliation and matching identify and resolve issues across systems that store the same data differently. Combined with Robotic process automation of manual data entry tasks prone to human error, these intelligent automation technologies help ensure data is accurate, consistent, complete, and readily accessible. The result is timely, high-quality information that supports more effective decision-making, risk management, and customer experiences.

Benefits of Intelligent Automation in Financial Services

Here are some key benefits of intelligent automation in financial services:

• Improved efficiency and productivity - Automating repetitive manual tasks frees up employees for higher-value work and speeds up processes. This boosts overall efficiency and productivity.
• Reduced costs - Automation reduces labor costs by lowering the number of employees required for rules-based tasks. It also cuts costs from errors, non-compliance, and fraud.
• Enhanced risk management and compliance - Automated monitoring and real-time anomaly detection minimize risks and ensure regulatory compliance.
• Superior customer experiences - Faster, more convenient, and personalized customer journeys improve customer satisfaction and retention.
• Increased agility and scalability - Automation enables operational processes to quickly adapt and scale up or down based on demand.
• Improved data-driven decision-making - AI capabilities provide clean, integrated data that enables evidence-based strategies and policies.
• Access to talent - Automation helps alleviate talent shortages by freeing up employees for more strategic work and attracting tech-savvy job seekers.
• Optimized workforce - Employees spend more time on higher-value work that leverages human skills and expertise.
• Innovation - Resources freed up through automation can be reinvested in innovation initiatives to drive growth.

Challenges of Intelligent Automation in financial services

Here are some challenges of implementing intelligent automation in financial services:

• Cost - Intelligent automation technologies like AI, machine learning, and RPA can be expensive to deploy and maintain at scale.
• Legacy systems - Integrating automation solutions with outdated legacy IT systems can be complex and costly.
• Skill shortages - There is a shortage of people with the skills to properly implement and manage intelligent automation technologies.
• Limited ROI - Without a clear business case and ROI, it can be difficult to justify the investment in automation.
• Data issues - Automation relies on high-quality data, but financial services firms often struggle with data silos, inaccuracies, and inconsistencies.
• Resistance to change - Employees may resist the change that automation brings for fear of job losses or increased workload.
• Regulation - Regulators need to catch up with new technologies to develop appropriate governance standards.
• Vendor lock-in - Reliance on a single vendor for automation solutions poses risks if that vendor fails to deliver or is acquired.
• Lack of oversight - Automated systems need proper governance, control frameworks, and ongoing human oversight to operate ethically and effectively.
• Implementation risks - Projects often fail to meet objectives due to issues like incomplete requirements, changing priorities, and technical difficulties.

Conclusion

Intelligent automation holds immense promise for elevating performance, boosting profitability, and gaining a competitive edge for financial services businesses. However, a careful, phased approach is required that addresses issues like change management, data quality, cost justification, skills gaps, and governance. When implemented appropriately, the benefits of transforming customer journeys, enhancing employee experiences, unifying operations, reducing risks, and improving data quality through intelligent automation can be truly transformative for financial services firms looking to thrive in a rapidly changing industry. With the right people, processes, and technologies in place, intelligent automation can light the path to the future of finance.