Banks are beginning to explore how artificial intelligence is reducing costs, increasing revenue, reducing fraud and enhancing customer experience. Below are some real-world examples of how artificial intelligence and RPA are being used in banking. While there are challenges, it’s time to invest, learn and partner with experts from organizations of all sizes that can help exploit the benefits of AI.

News and articles about the business implications of artificial intelligence (AI) are flooding the whole financial services sector. Banks and credit unions are becoming more aware of these technologies’ potential and are beginning to explore how AI could allow them to streamline operations, improve product offerings and enhance the customer experience.

According to Deloitte’s white paper AI and You: Artificial Intelligence Perceptions from the EMEA Financial Services Industry, AI today can be represented in three application areas: intelligent automation, intelligent interaction, and intelligent insight.

    1. Intelligent automation: Machine learning (ML), Robotics Process Automation (RPA), natural language processing (NLP) and other intelligent tools are used in the first AI domain to develop profound domain-specific expertise and then automate related tasks.
    2. Intelligent interaction: There are intelligent’ agents’ at the next stage of the AI value tree: systems that use intelligent technology to engage with people, exploiting the power of unstructured data (industry reports / financial news), leveraging text / image / video awareness, providing personalized communication between banks and customers with tailored product offerings and creating new revenue streams
    3. Intelligent insights: Intelligent insights refer to the extraction of concepts and connections from different data sources to produce customized and meaningful responses concealed within a mass of structured and unstructured data. Intelligent insights allow the identification of key trends and relationships in real-time from large amounts of data from multiple sources in order to extract profound and actionable insights.

As outlined in a recent report by the European Financial Management Association, Getting Ahead with AI: Transforming the Future of Financial Services, AI provides opportunities, challenges, recommendations and a series of customer successes illustrating how AI has transformed the financial services industry. According to European Financial Management Association, “AI presents a huge number of opportunities for retail financial services firms who can better meet requirements, increase their bottom line, enhance the customer experience and more if they are able to exploit their increasing data repositories.”

The Opportunities For The Financial Services Industry

Financial services organizations realize that they have a head start with artificial intelligence application, as they have extensive data sets and experience with analytical tools. From payment services to day-to-day banking, insight is captured that might make AI stronger.

Banks and credit unions use AI algorithms to support a variety of internal and customer-oriented processes. What is helpful is that when there is a value trade-off, consumers indicate they are willing to share personal insights. According to Accenture, “67 percent of customers will grant banks access to more personal data, but 63 percent want more tailor-made advice and the exact same number demand priority services… in return for the information they share.” These include:

  1. Fraud detection: AI has the ability to flag fraudulent behaviour while it occurs and identify what will be the next pattern of suspicious behaviour. Upon this process, location data can help.
  2. Compliance with regulatory requirements: Technology can be used to ensure that regulatory requirements are met, and that data is kept in real-time with monitoring. That allows problems to be flagged much sooner.
  3. Reducing costs and increasing revenues: Infosys reports that Automating the frontline is the most significant opportunity for AI. The value of engaging with customers in a “… automated & smarter way offer significant cost savings, with the risk spreading across millions of customer interactions.” In the near future, customers facing virtual assistants and back-office robotics will become commonplace.
  4. Improving the customer experience: AI offers the opportunity to make better and faster decisions by deriving insightful and actionable insights (e.g. trends of consumer behaviour). Some of these new types of interactions will be with voice or chatbot technology while other applications like RPA, supporting communication in marketing.
  5. Strengthening customer engagement: Artificial intelligence will help create customized and smart products & services, with new features, more intuitive interactions and advisory capabilities (e.g. personal financial support and management).

Accenture’s recent Banking Technology Vision 2017 discovered that more than three-quarters (78 percent to be exact) of bankers believe that AI will allow for simpler user interfaces to help banks create a more human-like customer experience. However, four out of five respondents (79 percent) agree that AI is going to revolutionize the way banks collect information and communicate with clients. Furthermore, three-quarters (76 per cent) expect banks can implement AI as their primary method of communicating with customers within three years.

At A Strategic Level There Are Some Challenges For AI

As with any new endeavours, the creation and deployment of AI technologies pose many challenges. With many financial institutions in the learning and early deployment phases, questions revolve around data security, operational effects, adoption of new technologies, and awareness of use cases, as well as benefits from ROI.

One of the biggest challenges, according to the European Financial Management Association, is finding the right talent. With just over half of survey respondents (55 percent) claiming to have identified an AI leader within their company, more than half of them have appointed the innovation leader as the leader. While this assignment may initially be fine, as applications become more complex, external hires will typically be required.

Another “people” problem is the effect of the financial institutions on current employees. In some cases, the current employees will not be well-positioned for the’ new banking age.’ In other cases, the labour transformation caused by AI advances will completely eliminate some positions. Instead, there are many who believe that recruiting really increases with automation. For example, 91 percent of respondents to the European Financial Management Association / Deloitte survey assumed that emerging intelligent technologies would motivate or help workers, rather than replace them.

Including AI As Part Of Your Banking Operations

Open banking and artificial intelligence potentials are intertwined, forming the basis for a new banking technology system that will more than likely include both financial and non-financial components. The strength of the corporate data and insights can be realized by collaborations with fintech companies and data analytics professionals. The alliances and arrangement decided today will in future assess the strategic advantage of a company.

At the meeting of the European Financial Management Association’s Operational Excellence Council, it was clarified that several providers offer AI-based solutions, and banks need to negotiate between specialist players and AI powerhouses as a result. The goal is not to become more automated and less personalized, but to make much more personalized and contextual use of technology and customer insights.

The banking sector continues to be in the early stages of developing robust AI solutions. While these solutions can definitely impact financial organizations ‘ cost and revenue structures, the real potential lies with how artificial intelligence can enhance the customer experience.

According to the European Financial Management Association, four main recommendations are made by experts to financial services firms that are looking to efficiently leverage AI’s value. Such are:

  1. Search for innovation, networking and matching with experts from outside the industry
  2. Make use of intelligent computing to make better use of data
  3. Use the right mix of application technologies.
  4. Push to keep a strong human element in your critical operations.

Following these guidelines, any company aiming to adapt to the increasing demands of the digital customer is a great starting point before looking to scale and exapand the value these technologies bring.