The entire financial services industry is being inundated with articles and presentations about the business implications of artificial intelligence (AI). Banks and credit unions are becoming aware of the potential of these technologies and are beginning to explore how AI could enable them to streamline operations, improve product offerings and enhance customer experiences.
According to Deloitte’s white paper titled AI and You: Perceptions of Artificial Intelligence from the EMEA Financial Services Industry, AI today can be described in terms of three application domains: cognitive automation, cognitive engagement and cognitive insight.
- Cognitive automation: In the first AI domain are machine learning (ML), Robotics Process Automation (RPA), natural language processing (NLP) and other cognitive tools to develop deep domain-specific expertise and then automate related tasks.
- Cognitive engagement: At the next level of the AI value tree lies cognitive ‘agents’: systems that employ cognitive technology to engage with people, unlocking the power of unstructured data (industry reports / financial news) leveraging text/image/video understanding, offering a personalized engagement between banks and customers with personalized product offerings and unlocking new revenue streams.
- Cognitive insights: Cognitive Insights refer to the extraction of concepts and relationships from various data streams to generate personalized and relevant answers hidden within a mass of structured and unstructured data. Cognitive Insights allow to detect real time key patterns and relationships from large amount of data across multiple sources to derive deep and actionable insights.
In the report, Getting Ahead with AI: Transforming the Future of Financial Services, Efma provides AI opportunities, challenges, recommendations, and a number of case studies illustrating how AI could transform the financial services industry. According to Efma, “AI presents a huge number of opportunities for retail financial services firms, who, when able to exploit their growing data repositories, can better meet regulations, increase their bottom line, improve the customer experience and more.”
Financial services organizations realize they have a head start with the application of artificial intelligence, since they have large data sets and experience with analytical tools. From payment services to everyday banking, insight is captured that can make AI more powerful.
Banks and credit unions are using AI algorithms to assist with a variety of internal and customer-facing processes. What is helpful is that consumer indicate they are willing to share personal insight if there is a value trade-off. According to Accenture, “67% of customers will grant banks access to more personal data, but 63% want more tailored advice, and the same number demand priority services, such as expedited loan approvals, or a monetary benefit, such as more competitive pricing, in return for the information they share.”
Using the components of machine learning, natural language processing and cognitive computing, there are several AI applications within banking. These include:
- Fraud detection: AI has the ability to identify fraudulent behavior while it is happening, as well as identify what the next pattern of suspicious behavior will be. Location data can assist with this process.
- Meeting regulatory requirements: Technology can be used to ensure that regulatory requirements are met and that data is kept with monitoring done on a real-time basis. This allows issues to be flagged a lot sooner.
- Lowering costs and increasing revenue: Infosys reports that AI’s biggest opportunity lies in automating the frontline. “The benefits of engaging with customers in a more automated and intelligent way offers significant cost savings, with the risk being spread over millions of customer interactions.” Customer facing virtual assistants and back office robotics will be commonplace in the near future.
- Improving the customer experience: AI provides the opportunity for improved and faster decision making by deriving deep and actionable insights (e.g. customer behavior patterns). Some of these interactions will be with new voice or chatbot technology while other applications will be behind the scenes, supporting marketing communication.
- Boost customer engagement: Artificial intelligence will assist in the creation of customized and intelligent products and services, with new features, more intuitive interactions (e.g. speech) and advisory skills (e.g. personal financial management).
Accenture’s recent Banking Technology Vision 2017 found that more than three-quarters (78%) of bankers believe that AI will enable simpler user interfaces that will help banks create a more human-like customer experience. In addition, four out of five respondents (79%) believe that AI will revolutionize the way banks gather information and interact with customers. Finally, three-quarters (76%) believe that within three years, banks will deploy AI as their primary method for interacting with customers.
Strategic Challenges of AI
As with any new endeavor, there are several challenges associated with the development and application of AI solutions. With most financial institutions in the learning phase, concerns revolve around data security, organizational impacts, the integration of new technologies and the understanding of use cases and ROI benefits.
According to Efma, one of the biggest challenges is finding the right talent. With only slightly more than half of survey respondents (55%) stating they have identified an AI leader within their company, more than half of those have appointed the head of innovation as the leader. While this assignment may be fine initially, external hires will usually be required as applications get more complex.
Another ‘people’ issue is the impact on current employees of financial institutions. In some cases, current employees will not be well positioned for the ‘new age of banking.’ In other cases, the transformation of labor caused by the advances of AI will eliminate some positions entirely.
Alternatively, there are many who believe that automation will actually increase hiring. For instance, 91% of Efma/Deloitte survey respondents believed that new cognitive technology will either empower or support employees, rather than replace them.
Making AI Part of Banking Ecosystem
The potential of open banking and artificial intelligence are intertwined, making up the foundation for a new banking ecosystem that will most likely include both financial and non-financial components. By partnering with fintech providers and data analytic professionals, the power of organizational data and insights can be realized. The partnerships and structure decided upon today will determine an organization’s competitive differentiation in the future.
At Efma’s Operational Excellence Council meeting, it was explained that multiple providers are offering AI-based solutions and, as a result, banks need to navigate between specialist players and AI powerhouses. The goal will not to become more automated and less personalized, but to use technology and customer insights to become a lot more personalized and contextual.
The banking industry is still in the early stages of developing strong AI solutions. While these solutions can definitely impact the cost and revenue structures of financial organizations, the real potential is with how artificial intelligence can improve the customer experience.
According to Efma, there are four key recommendations that experts make to financial services firms who are looking to effectively exploit the value of AI. These are:
- Look to invest, learn and pair up with experts from outside of the industry
- Make use of cognitive computing to make better use of data
- Implement the right mix of platform technologies
- Strive to maintain a human touch.
Following these recommendations is a great starting point for any organization looking to respond to the increasing demands of the digital consumer.