Semantic Automation: Leveling Up Automation to Save Costs in Financial Services

It’s considered the future of business process automation, and the banking industry is paying attention to how semantic automation can benefit the bottom line. Semantic automation, as a component of artificial intelligence, has a growing role to play in financial services. It’s the enhanced ability to understand high-level abstractions and relationships between data points. It includes the processing of unstructured data-expanding automation capa bilities and impact. It speeds up ROI by reducing the amount of coding required to automate workflows, and in turn, enables faster digital transformation.

The world of work in financial services is changing fast, driven by smarter technologies that are helping organizations reimagine how tasks and processes are carried out. SS&C Blue Prism undertook global research with 550 financial services professionals to uncover where progress has already been made, how work models are changing and how change is predicted to continue in the future. According to our research, financial services institutions that have invested in intelligent automation report significant increases in their productivity rates, an improvement in agility and resilience, and higher accuracy and speed in areas like compliance, together with an improved customer service experience. Of the people surveyed, 87% said they had seen digital acceleration in some shape or form.

How Semantic Automation Is Driving Cost Savings

Traditional, rule-based robotic process automation is the most widely used automation technology, but semantic automation is next-level technology. The advanced technologies driving most savings in the banking and finance sector require high-level cognitive skills, such as thinking critically, assessing and providing insights on qualitative and quantitative information, and managing projects. It’s estimated that AI has the potential to add $1 trillion in annual value to the global banking industry, according to McKinsey & Company.

While machine learning, a sub-discipline of AI, can imitate human intelligence, semantic automat ion adds layers of understanding and thereby improves algorithms. This enables businesses to automate high-level, complex workflows.

Why Is Semantic Automation the Right Fit for Financial Services?

The financial services industry has extensive analog processes, operations and data it needs to digitize. Manual processing is prone to errors, low job satisfaction and turnover. Traditional automation technologies struggle with handwritten or visual data, requiring more human-in-the-loop and slower processing. Semantic automation allows different analog data to be classified, organized and validated. Any issues or concerns are flagged for human review.

For example, global financial services firms may have to sift through over a million pages of data across various formats – handwritten, fax, low-resolution images, etc. – to comply with the latest know-your-customer (KYC) regulations. Without semantic automation, this task would be near impossible to complete within a reasonable timeframe. However, we know that this technology increases processing speeds and error rates. As a result, we see businesses save on the opportunity costs of having workers focused on limited-value tasks and any penalties for likely completion delays.

The Power of Three

In addition to digitally transforming analog operations, semantic automation’s comprehension capabilities enhance human workers’ experience by analyzing and offering insights on relational and unstructured data, including derivatives restructuring, corporate lending and wealth management. It means people can spend their time doing what humans do best, and what a digital workforce simply can’t – empathizing, collaborating, networking, creating – all for the good of customers and colleagues.

In addition, digital workers perform ever more complex work, not just across the front, middle and back-office of a financial institution, but across the entire enterprise. Our research indicates that the next evolution will involve three essential components: One-third people, one-third systems and one-third digital workforce.

The task of reconciling accounts, for example, could take an employee about six hours to complete. It’s a complex process, but digital workers equipped with semantic cognitive capabilities can complete this in under a minute, freeing the human worker to focus on more complicated and intricate cases. The task is completed without error and gives 1.2 million minutes back to its human workers. They can now engage in high-value interactions, increasing business revenue and job satisfaction.

Filling the Gap

Leading financial services organizations and banking institutions recognize the need to utilize AI across all operations. Still, many use the technology inefficiently, applying it only for specific uses or verticals. As a result, the valuation gap between leading financial institutions and those falling behind is widening. Decisions around systemic automation adoption will be critical in determining which side of the gap companies land.

In the next 10 years, according to McKinsey, 75-80% of transactional operations like general accounting and payments processing and up to 40% of strategic operations like financial controlling and reporting, financial planning and analysis and treasury are expected to be automated. This trend highlights the need for financial services companies to begin systemically integrating advanced business process automation capabilities into their operations.

A Scaling Solution

When used effectively, semantic automation can deliver impressive results. It’s being increasingly used for its discerning capabilities: Generating, processing and understanding data; engaging and creating connections among different data points in varying formats; and developing decision-enhancing analysis and insights. Taking care of these tasks digitally allows human workers to drive value for financial organizations and focus on highly complex tasks requiring communication, negotiation, leadership, entrepreneurship, and emotional and social understanding skills.

Investing in an intelligent automation platform can help institutions adopt advanced technologies to remain competitive in a digital-first world. Globally, 70% of organizations have piloted automation technology, with those in the financial services most likely to scale such solutions across the business, as reported by McKinsey. The cognitive capabilities of AI are already being utilized to varying degrees through the financial sector, such as with intelligent document processing. The key differentiator among industry players will be the speed with which they invest in these technologies – and early adopters are already ahead of the game.

Joe Collura is Vice President of Solutions Engineering, Americas for SS&C Blue Prism, a Windsor, Conn.-based provider of enterprise intelligent automation technology.