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    Banking & Finance

  • Personalizing the customer experience

    The AI Association supports policies that encourage responsible innovation in financial services, from national banks to startups. We support policies that empower banks to innovate and partner with startups to deliver customers the innovative financial services they love while ensuring they get the protections they deserve.

     

    In banking, AI promises to add efficiencies that can provide more Americans with access to safe and fair financial products. AI can also help banks extend credit to more borrowers, enhance the customer experience, improve fraud detection, lower the cost of offering services, and more.

     

    We do not believe added regulation will benefit banking institutions nor their customers, as existing regulation covers all business processes and applications in which AI could be used. These exciting new technologies serve to improve upon how we operate, and trust is needed in the experts and current processes. Through education and community engagement, AI can deliver incredible innovations to the financial services industry, serving the value of both financial institutions and their customers.

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    Enhanced Customer Engagement

    Online wealth management services provide automated algorithm-based portfolio management advice without the help of a human counterpart. This solution engages with the user online to develop an appropriate portfolio. Algorithms can then regularly rebalance the portfolio to maintain the original investment guidelines, while operating at lower costs.

  • AI is not a replacement for employees - it's a tool to release pressure points, and derive greater creativity and value from the workforce

    1

    Transform Relationships

    Using AI, people will be able to spend more time on exceptional work: the 20% of non-routine tasks that drive 80% of value creation.

    2

    Re-imagine business models and processes.

    Smart machines will continually review end-to-end processes and apply 'intelligent automation of process change' to refine and optimize

    3

    Illuminate dark data

    Companies will applyAI to greatly enhance large data analytics, evolve algorithms with transactional data faster, and combine data in new ways to discover trends.

  • Overview - AI in Banking

    AI has the potential to apply to many areas of banking. The terms AI encompasses a broad array of interrelated technologies. The following technologies are the most common in banking today.

    Machine Learning

    Machine learning allows systems to learn and improve as new information is made available without specific programming instructions. The technology can be leveraged for both front and back office applications, including tailored portfolio management and fraud detection.

    Robotic Process Automation

    RBA enables organizations to automate tasks across applications and systems as if a human were performing them. This reduces repetitive data management tasks between and within business units for a significant improvement in overall operational efficiency.

    Natural Language Processing

    The subfield of AI tasked with both understanding and generating contextually accurate human language, NLP has wide ranging applications across the value chain from customer service to efficiently compiling industry standard reports.

    Speech/Object Recognition

    Allows systems to identify objects or words within images and understand spoken language. Like NLP, voice and image recognition tools provide value in customer service, legal and compliance monitoring of company data, as well as increased customer interface security on mobile devices through facial recognition.

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