Today, finance departments spend much of their time responding to questions with answers based on structured data sets, such as information from profit and loss statements. For instance, the CEO might want to know how profit will be affected if the price of a business input rises by 10 per cent. Or the CFO might want to know how margins may be affected if there's a two per cent increase in the goods and services tax (GST).
But in the future, finance departments could be able to respond to much more complex problems thanks to cognitive computing. This involves analysing unstructured data and deriving insights from it.
“It's a way of teaching software how to digest and manage a data feed. Once you do that the technology will keep learning and adapting to the information it receives," says Robert Hillard, Managing Partner, consulting with professional services firm Deloitte.
Technology firm IBM popularised cognitive computing with Watson, a computer running software that understands human language and can rapidly pull in multiple data sources to generate insights.
Gavin Diamond, Vice President of Sales, Asia Pacific at IBM's cloud consulting subsidiary Bluewolf, says better engagement with finance department customers is one potential outcome of cognitive computing.
Bluewolf has been working with businesses to create products using cognitive computing, including chatbot software. A chatbot is an application that responds to customer queries through a website. The more customer queries it responds to, the more it learns about what they want to know, and the better it is able to respond to customer questions.
"Customers want to be served online and they want to know invoice details such as when payment is due. It's much more efficient for a technology engine to serve that information to the customer rather than finance staff. This will make businesses more efficient, and should also reduce the cost to serve customers," Diamond says.
According to Diamond, configure price quote is another area within cognitive computing from which finance departments are likely to benefit. This technology could allow an organisation to set business terms based on unique customer information, including how old the business is, publicly available credit score information, and the business’s payment history.
External customers are just one group that may benefit through businesses incorporating cognitive computing into their operations.
Internal applications
Risk and compliance management may be another area that can benefit from the rise of cognitive computing. Software may be able to absorb and help manage multiple risk and compliance frameworks — such as taxes and industry laws — across geographies.
“Loading this information into the system delivers a better understanding of regulatory risks," Diamond explains.
According to Diamond, cognitive computing could also help organisations attract the best and brightest staff members by being able to analyse data on multiple talent sources.
“Big organisations screen multiple candidates at any one time. Unstructured data can help firms identify multiple talent sources and ways to engage with them. Cognitive systems allow you to hire the right talent and position them in the right place in the team," Diamond says.
Robotic Process Automation (RPA) may also benefit finance teams. RPA allows computers to watch processes humans perform, learn how to do them, then repeat them.
Says Hillard: “Let's say a CFO finds a staff member who spends a day every month individually answering emails on invoicing. An RPA tool can watch and learn that process, and automate it, under human supervision. This reclaims staff time and helps lower costs in the long term."
Understanding limitations
While cognitive computing may help deliver enhanced analytical information to firms, experts suggest it is important to understand it cannot replace human intelligence.
“Computers can only work on the data they have. They can't make a cognitive leap," says Hillard. For instance, cognitive computing's analytical techniques can assess the likelihood of three concurrent events, such as a financial crisis, a new set of financial regulations and a trade war. However, technology cannot decide what the business should do if this happens.
“Once you understand cognitive computing's limitations, the finance function can start making decisions about which technologies in the business can and can't be automated, and which functions should be moved to shared service centres or outsourced," Hillard explains.
“Finance professionals are trained to apply their judgement to problems. So preparing for cognitive analytics is one of the most important roles finance leaders should be playing today," he adds.
Key Takeaways on Cognitive Computing
- Understand the potential benefit to external customers.
- Evaluate internal cases where cognitive computing can streamline processes.
- Assess how the business intelligence portfolio may need to be expanded to support cognitive computing.