AI and machine learning are revolutionising all sectors in the global economy with banking and financial institutions being no exception to this trend. They are adopting latest software and bots to change the face and image of their industry and offer extraordinary services to their existing and future customers.
Banking and financial sectors have been using some form of machine learning to keep track of data but it is usually tedious and manual in nature. With high volume of data, accurate historical records and the quantitative nature of financial institutions, this sector is particularly suited for artificial intelligence.
Here are some scope of usage:
Improved customer support
How many times have you been irritated by the lack of real solutions when calling any bank helpline numbers? Machine learning is expected to change this picture with its intelligent solutions. Customer support will be aided with previous accounts details to help the system provide quick and helpful response .
Enhanced data quality
Machine learning and AI will certainly enhance the quality of data. Right from collection to sorting and filtering complex and cumbersome calculations, a lot can be managed by modern day software and bots. It saves a large amount of manpower and yields higher accuracy in data.
Fraud prevention
Artificial intelligence plays an important role in data security which is one of the greatest responsibilities and concerns of banking and financial services. Preventing financial frauds and data robberies are two key areas where AI has been a game changer for financial institutions.
Digital financial assistants
Allo, Siri and Cortana are pioneers in the space of digital assistants. For financial institutions, these assistants are going to be the new big thing and AI and machine learning are the key propellers of this huge change. Assistants will help the banks to maintain a personal relationship with each employee without having to spare their human resources. Digital assistants will provide quick and accurate info based on account holder’s transactional history and activity, improving responsiveness and TAT numbers.
Customized marketing strategies
Deriving from marketing analytics, data coming in from various platforms and touch points like website, app, social media, and even offline media, marketing strategies can be tailored for a set of similar account profiles. The results can also be used for intuitive intelligence that can guide personal financial assistants.
