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How artificial intelligence makes financial services institutions more efficient
AI is most effective when it augments human workers and enhances business outcomes, rather than simply replacing humans with bots and automating processes.
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Illustration of financial technology (fintech). (Shutterstock/File)
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he financial landscape has been rapidly evolving with the rise of financial technology (fintech) companies and startups that are more agile and technologically advanced. This has led financial services institutions (FSIs) to revise their business models and evaluate how they can integrate technology into their operations.
Robotic process automation (RPA) is no longer a foreign term in the financial field. Pairing RPA with artificial intelligence (AI) creates intelligent process automation (IPA) that works as a catalyst in digital transformation in FSIs.
Like many other industries, the financial field is heavily reliant on documents and legacy systems. Large numbers of transactions that generate documentation happen daily. With IPA, it is easier to bridge the legacy systems and create a uniform approach to data management.
IPA plays key roles in driving process efficiencies, improving quality and scalability. Minimal-value work will be eliminated without a significant overhaul of underlying systems and efficiency will be increased through automated workflows.
Automation has the potential to alleviate staff from laborious and repetitive tasks and focus on industry knowledge and expertise to create greater value. According to McKinsey, many companies across industries implementing IPA have obtained impressive results – 20-35 percent cost efficiencies and 50-60 percent reductions in process time. Hence, there is a need for FSIs to stay ahead of the game and keep up with the pace of advancing technology.
IPA can be applied across different back office operations in FSIs in many different ways. In trade finance, IPA automates letter-of-credit processes by extracting key information from documents and checking against international banking rules and standards for compliance. In insurance underwriting, IPA helps to auto-decline and auto-route insurance applications, evaluate risk and recommend coverage. In credit underwriting, IPA analyzes financial documents such as annual reports and analysis reports to automate credit memo generation.
One of the core technologies powering IPA is machine reading comprehension (MRC), a key natural language processing (NLP) technology that reads and understands text in its true semantic meaning. In the past two years, it has progressed significantly to be comparable to a human’s comprehension capability.
Why is MRC important? Many of the documents back offices deal with are unstructured – they are scanned paper documents (e.g. invoices) where information placement is unpredictable, information is displayed in complex table format and information naming is not standardized. Therefore, traditional rule-based or template-based information extraction is not sufficient. MRC is needed to understand text as well as its context to properly identify relevant information, and in turn, inject cognitive intelligence into process automation.
AI is most effective when it augments human workers and enhances business outcomes, rather than simply replacing humans with bots and automating processes. FSIs must learn how to manage humans and machines together to successfully deploy AI.
FSIs today are facing increasing demands to maintain a lean operation while also delivering exceptional client experience at the lowest cost. IPA makes it possible for financial institutions to achieve these goals and remain competitive in the dynamic environment.
To conclude, RPA and AI in FSIs refer to the use of intelligent process automation to execute repetitive tasks. The human staff are freed to handle more productive work, thus leading to enhanced staff satisfaction. This will then lead to long-term sustainable growth.
Given all the listed benefits, the case for IPA in FSIs is compelling. By leveraging AI to its full potential, FSIs may enable a massive rise in their capacity and agility. (kes)
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The author received his Ph.D degree in Computer Science from the Institute of Computing Technology, Chinese Academy of Sciences. His research focuses on AI and he has published over 60 research papers in top conferences and journals. As a tech entrepreneur, Luan founded and runs AI and big data company 6Estates, focusing on back office automation and intelligence with big unstructured data in the financial domain.
