How Cognitive Computing Can Transform Businesses

Every day an infinite amount of unstructured data is being generated and stored by organizations across industries. To make sense of that data and apply it into effective decision-making, companies increasingly lean on AI-powered solutions. A particularly interesting area of AI – cognitive computing – is one of the forces driving transformation in the modern business environment. So how exactly does cognitive computing make a change?

What is cognitive computing?

First, let's define the term. As Dr. John E. Kelly III, SVP, IBM Research and Solutions Portfolio, puts it, Cognitive computing refers to systems that learn at scale, reason with purpose and interact with humans naturally. Rather than being explicitly programmed, they learn and reason from their interactions with us and from their experiences with their environment. Those systems generate reasoned arguments and recommendations about more complex – and meaningful – bodies of data, as IBM suggests in the report dedicated to computers, cognition and the future of knowing.

The most important part, however, is that cognitive systems can make sense of the 80% of the world’s data that computer scientists call ‘unstructured’.

Where can cognitive computing be applied in businesses?

In banking, cognitive systems can be applied to extract meaningful insights from major sources of unstructured data. Among those sources, professionals from IBM emphasize:

  • Business scenarios involving a process or function that today takes humans an inordinate amount of time to seek answers and insights from various information sources to make a decision or think through a problem.

  • Situations where there is a question and answer (Q&A) requirement that would require users to interact and ask questions posed in the natural language. This might include complex customer engagement scenarios that require deeper understanding and insights beyond question and answer responses provided by traditional programmable customer response systems.

  • Processes or functions that require transparency and supporting evidence for confidence weighted responses to questions and queries.

Effective medical treatments can be developed in the healthcare industry with the application of cognitive systems to clinical data analysis. Moreover, cognitive systems can integrate implications of treatment recommendation for all parties – insurance policy, legal framework, etc. In law enforcement, cognitive systems can analyze data from previous investigation cases to recommend a course of action.

Cognitive computing in banking

In the attempt to secure a place in the ever-changing environment, financial institutions have to adopt modern technological advancements and redefine their relationships with the customer. Cognitive systems offer an edge in finding a place for a bank’s credit card in one’s wallet or app space on a smartphone’s home screen. Professionals emphasize the following ways in which cognitive systems can empower financial institutions:

  • ANZ, which recently reported to be expanding its use of cognitive computing, sees its application in areas like advisory, risk, and back office automation. A particularly interesting area is the integration of internal and external systems. As ANZ CTO Patrick Maes commented, ...we wanted to build capability that was intelligent and that could deal with internal and external sources <...> where we could increase the automation and reduce time to market for approval of unsecured and personal loans.
  • Since cognitive systems enable cost-effective and efficient measuring, monitoring and tracking compliance to financial regulations, they enable efficient identification, collection and use of customer information in seconds possible, i.e., the income tax that fixed deposits over a certain limit are subject to, as ET states.

There are certainly more areas of banking business where cognitive computing can make a difference. While the process of cognitive computing automation may be a complex task for legacy-controlled ecosystems, it is a matter of survival for banks to pursue the implementation.