ARTIFICIAL INTELLIGENCE — The Benefits and Challenges for Financial Institutions BY JULIA A. GUTIERREZ, Director of Education, Compliance Alliance The technologies of artificial intelligence (AI) are becoming an integral piece of the world we live in. These technologies are being deployed across a plethora of fields ranging from simple devices, such as cell phones, to more complex technologies, such as autonomous vehicles or the diagnosing of diseases. AI is even rearing its advancing technological head into the playing field of banking. It is a constantly evolving technology that many industries are jumping into while others are slowly pushed into in their efforts to thrive. For banks, it’s critical to embrace the advancements of the future but also to consider the security and regulatory requirements and overall risk to the organization and its customers. WHAT IS ARTIFICIAL INTELLIGENCE? Artificial intelligence is a term that commonly references the various technological capabilities that allow for the analysis of data and the identification of patterns to make decisions and impact an outcome. Some examples of these AI-type activities or branches include machine learning, natural language processing, robotics process automation and speech and object recognition. Machine learning is a branch of AI and computer science that focuses on the use of algorithms and data to imitate human learning patterns, while gradually improving accuracy. With machine learning, the system learns and improves as new data is made available. Another branch of computer science and AI is natural language processing. This branch of AI enables computers to process human language, received through text and spoken words, and to understand the meaning and intent. It basically allows a computer system to understand the semantics of conversational language. The AI branch of robotics process automation, also known as software robotics, is the use of applications and systems to perform human-like tasks. It uses intelligent automation technologies and rule-based software to perform business process activities at a more efficient volume, reducing the need for human resources or involvement in the task. Finally, the AI branch of speech recognition enables a system to identify and process human speech into a written format. Speech recognition may also be referred to as automatic speech recognition, computer speech recognition or speech-to-text. This AI technology is often confused with voice recognition which focuses on identifying an individual user’s voice. However, speech recognition focuses on translating speech from verbal to text. Each of these artificial intelligence branches are utilized throughout financial institutions and countless other industries around the world. THE BENEFITS OF ARTIFICIAL INTELLIGENCE Artificial intelligence is used in various fields and applications ranging from online shopping, advertising and machine translation enabling cross-language communication, to improving the overall operations and cost efficiency of financial institutions. The use of AI technologies in financial institutions can drastically reduce operational costs while significantly increasing productivity. With its broad range of uses, AI can potentially aid financial institutions in reducing costs associated with products and services, and it can enhance the overall customer experience as it bridges the gap between customer convenience and relationships. AI can benefit a financial institution’s lending process as it can expand credit access, assist in financing decisions, decrease underwriting times and costs and enhance both the borrower and lender experience. AI can be beneficial throughout other areas within financial institutions, such as identity validation and real-time anti-fraud monitoring. The opportunities and benefits when it comes to AI and financial institutions seem to be endless. But there have to be challenges, right? ARTIFICIAL INTELLIGENCE CHALLENGES Artificial intelligence isn’t perfect. Like any other enhancing technology, AI comes with its own set of risks and challenges. Some of those risks and challenges include system integration and a gap in skills. With system integration, the data behind Utah Banker 18
RkJQdWJsaXNoZXIy MTg3NDExNQ==