Also known as AI and Machine Learning (ML), artificial intelligence is the idea that computers, machines – anything electronic – can think and make decisions similar to or supplementary to humans. The uses of AI are wide ranging and can be built to solve basic models with a yes or no answer, or to process data sets with limitless complexities and permutations.
While there are many theories and opinions about Artificial Intelligence (AI), one thing is certain: AI is here to stay. In the financial industry, AI is poised to become a core element of the digital transformation that banks are currently experiencing.
With the advent and growth of online and mobile banking, AI also represents a significant opportunity for banks to help improve customer experiences and drive long-term profitability. More online activities mean more digital insights, which an AI-enabled application can analyze for engagement trends, risks and recommendations.
Artificial Intelligence and the Digital Transformation
In the financial industry, artificial intelligence is appearing in fraud detection initiatives, loan underwriting and in the popular “Robo-Advisers” that provide online advice to investors with minimal human interaction.
We have been living with, and benefiting from, artificial intelligence for decades. Examples from our modern daily lives include Apple’s Siri and Amazon’s Alexa, the auto-complete feature of popular search engines, and email spam filters.
And according to Accenture’s Business Technology Vision 2017 report, more than 78% of bankers believe that AI can enable simple user interfaces that will help banks create a more human-like customer experience. The majority believe that AI will revolutionize the way banks gather information and interact with customers.1
But is AI right for every organization?
More than 78% of bankers believe that AI can help banks create a more human-like customer experience 1
Pros and Cons of AI for Financial Institutions
Implementing AI has challenges, including cost, data quality, ethical concerns and appropriateness. Let’s break them down:
- Cost: Launching and scaling an AI initiative can run into tens of millions of dollars (or more), depending on the scale and goals.
- Data Quality: AI removes some of the human factors, which generally increases data quality. However, the data controls organizations put in place may or may not prevent bad data from entering the system and negatively influencing an AI-enabled initiative.
- Ethical Concerns: Bank executives “agreed that ethical concerns pose a significant obstacle to the application of AI.” Almost 90% said their employees, vendors and customers have concerns.2 And in the tightly regulated financial services industry, institutions must consider the potential “black box” scenario in which an AI initiative does not have the level of transparency the current regulatory climate requires.
On the positive side, AI-enabled initiatives have the potential to add predictive knowledge, improve customer experience, and enable large banks and FIs to compete with the emerging fintech competitors.
Using AI to Improve Customer Experience
Even with the challenges identified above, 82% of US bankers think AI will revolutionize the way banks gather information and interact with customers.3 AI can help banks and financial institutions find meaningful patterns in seemingly disparate data sources, and applying the AI-enabled segmentation model in finance has broad support.
For example, AI has significant potential implications for finding the best products and services to customers who are underbanked/unbanked or have thin credit files. Using an AI-enabled application, an organization could also begin segmenting and personalizing offers to appeal to individuals rather than large cohorts of customers and prospects.
Other potential improvement areas include fraud identification and managing risk. In an era of increased vulnerability and unprecedented data breaches, AI holds potential to help companies predict fraudulent activities as well as potential attacks, mitigating the risk of such events.
82% of US bankers think AI will revolutionize the way banks gather information and interact with customers 3
An AI-Enabled Future
Cathy Bessant, Chief Operations and Technology Officer for Bank of America, recently observed, “There is no doubt AI is the term of the day, but we have been using automated intelligence for a lot longer than people think.” Credit score models and data analysis may already exist in many FIs, but as Bessant says, “[a]utomated intelligence is often better, more predictable, faster, cheaper, has a lower error rate – as long as our algorithms work.”4
The movement towards a data-driven future is well underway. The digital transformation of the financial industry will continue to accelerate, and AI will be a driving force in the strategy and vision of the next generation of leading FIs.
1. Accenture. (2017). Accenture Banking Technology Vision 2017 (Rep.).
2. Infosys. (2017). Amplifying Human Potential Towards Purposeful Artificial Intelligence (Rep.).
3. Marous, J. (May 16, 2017). Banking Must Move From Mobile-First to AI-First. The Financial Brand. Retrieved June 21, 2017, from https://thefinancialbrand.com/65338/banking-ai-ui-artificial-intelligence-data/?edigest
4. High, P. (June 19, 2017). The Future Of Technology According To Bank Of America’s Chief Operations And Technology Officer. Forbes. Retrieved June 22, 2017, from https://www.forbes.com/sites/peterhigh/2017/06/19/the-future-of-technology-according-to-bank-of-americas-chief-operations-and-technology-officer/#1514812377c5[/vc_column_text][/vc_column][/vc_row]
