June 14, 2017 | Written by: Stephen Reiser
Categorized: Banking | FinTech
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The worldwide banking industry experienced profound challenges during the Great Recession of 2008-2009. While the global economy has improved, the pressure on banks is unabated.
Pressures from all angles
Pressures stem from a myriad of sources: competition from fintechs; unrelenting regulatory environment; associated costs of compliance (or non-compliance!); increasingly sophisticated security threats; and, most recently, shifting customer expectations driven in large part by millennials.
Millennials are a fastidious breed. They are tech savvy, mobile and social. They rapidly leverage technology to compare options such as prices, features, and banking reputation when purchasing products and services. More than ever – millennials seek customized experiences without a corresponding increase in prices.
Perhaps nothing evinces the peril faced by banks more than this…: 1 in 3 millennials are open to switching banks within the next 90 days.
Cognitive computing fights doom and gloom
All is not doom and gloom. A number of industry leading banks are transforming to address the challenges. These banks are deploying advanced technology and becoming cognitive.
These contemporary banks are being built on cognitive computing, which became known in 2011 when IBM’s Watson computer defeated the top human contestants on the televised quiz show, Jeopardy.
Cognitive computing systems are based on four key principles:
- Learn and improve by leveraging each new piece of information
- Build speed and scale by using machine learning to handle complex, repetitive tasks
- Leverage subject matter expertise to collate and curate human intelligence for rapid reuse or decision support
- Interact using natural language, context and reason
Cognitive systems are pivotally helping banks enhance customer experiences, uncover new insights, and improve speed and quality of decisions.
Watson Marketing helps find diamonds in the dust
IBM has developed Watson Marketing capabilities to help banks discover insights beyond the abilities of conventional computing.
Like diamonds masked by coal dust, banks possess insights rendered invisible by the sheer size and unwieldiness of massive amounts of unstructured data. Using Watson Marketing analytics, data sources such as images, video and social media can be coaxed to reveal insight. Overarching this effort, IBM Chairman and CEO Ginny Rometty has referred to Big Data as the “world’s natural resource for the next century.”
Banks can create new business models and revenue streams with these insights, make decisions faster and more confidently, and understand their customers in ways that are more personal and insightful. Cognitive banks then can create tailored and unique offerings and experiences for each of their customers.
Augmenting humans intelligence
Watson Marketing in particular uses machine learning to integrate and analyze the relevant data helping banks make informed decisions. Cognitive computing effectively augments rather than replaces human intelligence.
With incisive understanding of customer needs, banks can:
- Make personalized recommendations, engaging customers with the right solution, at the right time and through the right channel.
- Measure customer sentiment in social media and survey data to gain a deeper awareness of needs, wants and intentions.
- Identify customers with comparable issues and proactively reach out to resolve their issues.
- Maximize personalized upsell and cross-sell opportunities.
In my work with financial institutions globally – nothing offers greater prospective impact than the melding of Watson, digitalization, and Big Data. We are seeing breakthroughs being achieved in customer marketing, acquisition, cross-sell, service – and across a spectrum of business/functional areas.
Breakthroughs in branches and call centers
For example, when used in branches or call centers, Watson can crunch massive data in real-time, allowing CSRs to make on-the-spot recommendations for the “next-best-action” for service or for cross-selling or up-selling. It even can help predict which customers are at risk of leaving and why, and recommend actions to retain them, reducing attrition and churn. The effects of Watson are becoming evident in reducing call center costs by 20 percent, dramatically reducing wait times to near zero, and enhancing the customer experience.
Cognitive banking combined with Watson Marketing and the like are incredibly powerful tools, helping leading financial institutions understand customer needs and deliver distinctive user experiences.
For more information about IBM Solutions for Bank Marketers in the cognitive era, visit: http://www.ibm.com/commerce/us-en/marketing/?lnk=buttons-bar-left