Artificial Intelligence (AI) will separate banks from losers. This is as per 77% of banking executives who are surveyed during COVID-19. The COVID-19 will increase the utilization of AI, making the effective governance more urgent. The report, “Economist Intelligence Unit (EIU)” recognizes data bias, “black box” risk and inadequate human oversight as main concerns. This global review consolidates results from 25 regulatory reports to provide deeper insights and guidance on the utilization of AI in banking.
Data bias, “black box” risk, and inadequate human oversight are the key governance issues that banks are facing using AI, as per the Economist Intelligence Unit report “Overseeing AI: Governing artificial intelligence in banking”. This report is on the basis of a review of worldwide regulatory guidance on AI risks and governance in banking, which is carried out by the EIU on behalf of Temenos (SIX: TEMN, the banking software company.
The findings of the report are going to be discussed on the webinar “Rules of the game changer – governing AI in banking” on 23 July with CWB Financial Group, TSB Bank, and Temenos.
The report reveals that Artificial Intelligence is the main focus for technology investment for banks. This further highlight that 77% of banking executives agree AI will separate winning from losing banks. AI is predicted to hold its importance after the COVID-19 pandemic as banks now look to new technologies to assist them adapt to changing needs of the customer and compete with new market entrants. The EIU report also reveals that making sure ethical, fair and well-documented AI-based decisions are going to be crucial for banks deploying AI technology.
The global EIU report shows main governance challenges and distils regulatory guidance for banks using AI, involving:
- Ethics and fairness: banks need to develop AI models that are ‘ethical by design’. AI use cases and decisions must be monitored and reviewed, and data sources regularly evaluated to make sure that data remains representative.
- Explainability and traceability: steps that are taken to build AI models should be documented so as to completely explain AI-based decisions to the individuals they impact.
- Data quality: bank-wide data governance standards must be established and applied to make sure data accuracy and integrity and avoid bias.
- Skills: banks need to make sure that the right level of AI expertise across the business with focus to build and maintain AI models, and oversee these models.
Prema Varadhan, Chief Product Architect and Head of AI, Temenos, commented: “AI is changing the face of the banking industry. It gives banks the ability to process more data in real time, and learn from customer behaviors, helping them to bring operating costs down and hyper-personalize their services.”
“Banks are using AI to transform their customer experiences and back-office operations so ensuring that the technology is deployed ethically is more important than ever. “White box” models, like Temenos’ Explainable AI (XAI), can explain in simple human language how decisions are made and win the trust of regulators and customers alike.”
“As the custodians of customer data and trusted advisors, banks have a responsibility to adopt transparent, explainable AI technology – those that do stand to gain the competitive advantage in the new normal.”
The EIU review cites data bias, resulting in discrimination against individuals or groups of people as among the most prominent risks for banks using AI. Commenting in the EIU review, Prag Sharma, Senior Vice President, Citi Innovation Labs, said: “Bias can creep into AI models in any industry, but banks are better positioned than most types of organizations to combat it. Maximizing algorithms’ explainability helps to reduce bias.”
Pete Swabey, Editorial Director EMEA – Thought Leadership, The Economist Intelligence Unit, said: “AI is seen as a key competitive differentiator in the sector. Our new study, drawing on the guidance given by regulators around the world, highlights the key governance challenges banks must address if they are to capitalise on the AI opportunity safely and ethically.”
