How AI Is Making Inroads in the Financial Service Industry in 2019 and beyond

How AI Is Making Inroads in the Financial Service Industry

Technological advancements are making inroads in every sector and banking is no exception. In fact, the financial industry is the earliest adopters of smart technologies like artificial intelligence (AI), big data analytics, etc. Conventional legacy banks such as JP Morgan have been the frontrunners in the adoption of these disruptive technologies.

Artificial intelligence particularly has changed the way banking services are being provided. Traditional banks are shifting to this cutting edge technology and entering the league of financial technology (fintech) companies. But how is this technology being leveraged continues to be an eluding subject and how AI is going to benefit remains unknown to many. To provide a light on this, vital use cases of AI and its sub-division machine learning are being talked about in detail. This will enable the banking industry to get a birds-eye view on how to optimize banking operations and reduce human interventions in some key processes.

AI for Personal Finance and Insurance

Transaction bots as advisers: In the financial service industry, transactional bots are used to offer users financial coaching and advise regarding products. It works as digital assistants which help a user navigate through their financial plans, savings, and spendings. Built using natural language processing (NLP), a type of machine learning language, which understands the data and converts it into meaningful insights that are understandable for humans. Further, layers of product recommendations, reminders for upcoming renewals, transaction limits exhaustion based on customer data can also be added.

A real-time example of transaction bot is Ella which has been devised by Sun life which helps users get information on benefits and pensions by letting them stay on top of their investment plan.

Visualization bot for search requests: The AI bot leverages transactional data which is then processed using NLP to detect the meaning of request generated by users. These requests could be with respect to balance enquiry, general account information, etc. which are processed and displayed thorugh visualization bots. For instance, the Bank of America uses one such bot called Erica which acts as digital financial assistance through which customers can access financial information with respect to ones bank account.

Screening Client Risk Profile: AI is an excellent tool that can help banking managers effectively screen the risk profile of a client just by using the categorisation feature of the technology. Categorization based on low and high-risk profiles is segregated using historical data. To enable this categorization facility, classification models such as XGBoost and Artificial  Neural Network are equipped with historical client data.

Underwriting, Pricing and Credit Risk Assesment: Insurance companies provide underwriting services mainly for investment and loans manually which becomes cumbersome. With AI-powered models, instantaneous assessment of the credit risk is provided enabling customized and adaptable funding solutions to be provided to clients. AI Decision Algorithms are used and trained on earlier used payout models and underwriting models having varied classifying process.  This speeds up the underwriting process and improves user experience.

Contract analyzers: For banking managers, analyzing contracts forms part of repeative tasks that are manually done consuming a lot of time. This task can be delegated to machine learning technology. First, optical character recognition (OCR) can be used to digitize hard copy documents to soft copy post which business logic, a particular command for a similar type of data is used to interpret, record and a correct large number of contracts. Similar to formulas used in excel such as If this box is checked then it should be marked as red can be added to the model and trained on existing contracts to replicate the same on new contracts.

AI Set To Be Indispensable

The banking industry is riding high on digital wave and every bank small and big are turning to automated processes. Apart from the aforementioned functions of AI, other facilities such as making predictions, and valuation models are some of the other use cases which are disrupting the financial service industry. It is further set to expand with increasing success cases that have set examples for small banking companies to adopt these technologies. Undoubtedly, AI has become an indispensable tool for many companies as it has reduced the manual efforts of employees by generating accurate information and predictive analysis. The bots have successfully replaced the human interface with an even more personalized user experience which is unmatched.

By Mila Jones, who is a Senior Business Consultant, with rich experience in the domains of technology consulting and strategy, she works with both established technology brands and market entrants to offer research inputs and insights on leveraging technology as a source of strategic competitive advantage. She is a prolific author and shares her expertise with tech enthusiasts on popular digital publishing platforms. She loves not only to write about several topics but also loves to explore new ideas about Lifestyle, Travel blogs and many more.

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