Author: Sushil Nanda
Technology is making the financial sector more efficient, but there is a huge learning curve involved. Sushil Nanda examines how to navigate through the change
Finance is the backbone of any country. Emerging technologies such as robotics and AI are transforming the financial systems to become automated and digitalised.
On the other extreme, these emerging technologies, can also expose financial institutions to risk on many fronts, for which the impact may have global ramifications. What should a company do? The smart organisations need to find the middle ground and embrace the AI journey without introducing risk.
Without digging to deep, I would like to bring your attention to one specific area and ask you to establish whether there is any synergy.
You might be surprised about the volume of trades, derivatives, trade confirmation, FX, cash transactions that organisations receive via fax even in 2019. Though it may sound simple, imagine processing 50-100k faxes a month, with each fax containing a varying number of transactions that have 20-30 financial data points which need human or machine intelligence to read and understand it before it moves to the next destination.
Further to this, authorised signatures on the documents need intelligences that can detect the signature against a multi-page authorised list.
To act on such volume, a mid-to-large size organisation will require the support of a large workforce who may not like doing this task for rest of their life. Additionally, if due to lack of attention, someone misses a zero in any amount field, imagine the financial losses, penalties and undermining client confidence that could occur. It could impact the firm’s reputation and lead to them losing clients.
By using AI computer vision and machine learning organisations can digitalise the manual inputting of financial data points, reducing risk and improving cycle time. Organisations can then send information electronically and attempt to change client behaviour to eradicate sending faxes.
Applying AI to solve a business problem is like a science experiment and not black and white, there is a learning curve involved here, where the machine will take time to learn like a human. Unless we train the machine with the right data by a qualified SMEs, it will fail. In short, if you can survive with a rotary dial phone and not having a smart phone then you can survive your financial institution without embracing AI.
Sushil Nanda is a VP in Robotics & AI at State Street, specializing in understanding, assessing and identifying business problems that can be addressed with Robotics and/or AI, along with associated applications, to give a better client experience by automation & digitisation
