April 17, 2020 | Written by: Samson Tai and Joseph Ma
Categorized: AI | Security
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Artificial intelligence (also known as Augmented Intelligence) is becoming more than another popular buzzword. The emerging technology is becoming part of our daily lives, with many enterprises viewing it as the new driver for business growth.
As enterprises speed up their adoption of AI in business, the spotlight shifts to its governance. In banks, decision makers and senior management team members are calling for a better governance framework along the lines of FAT (fairness, accountability and transparency).
Regulators are taking note. Hong Kong’s currency board and de facto central bank, the Hong Kong Monetary Authority (HKMA), published its guidance to Hong Kong Authorized Institutions for customer protection when using big data and AI (BDAI) along with high-level principles on AI. Authorized Institutions include banks, restricted license banks and deposit-taking companies.
The guidance advises Authorized Institutions to be mindful in planning, designing and implementing a wide range of BDAI applications that use personal data from customer interactions. The data can help BDAI applications to improve business efficiency, simplify customer risk profiling, pinpoint money laundering activities and detect fraud.
This guidance answers three important issues that face all BDAI initiatives in banks:
- Enforcing a code of practice covering customer data protection, corporate accountability, fairness and explainability of outcomes, and actions from BDAI.
- Determining the method for certifying BDAI solutions that meet the guidance requirements.
- Identifying products or services for testing how well the BDAI solutions comply with the high-level principles on AI.
BDAI applications in banking do not operate alone and often involve many diverse groups working together. These can range from business leaders and frontline staff to IT vendors and in-house IT teams. An established guidance can help to set the rules before adverse customer sentiment develops from bad experiences with early adopters.
A cornerstone framework can help Authorized Institutions to achieve AI at scale. IBM’s AI@Scale offers one that comprises 6 dimensions: Strategy, Operating Model, Data & Platform, Operations, Change Management and People & Enablement.
The framework also offers a rich set of solution assets, including a maturity assessment model, a reference architecture and IBM’s best-in-class AI governance tools, such as IBM OpenScale and AI Fairness 360 Toolkit. Together, they help Authorized Institutions to take a holistic route to addressing HKMA’s 12 guiding principles.
Authorized Institutions can use a four-step approach to deploy the AI@Scale framework:
- Step 1: Assess the gaps in the existing process, methods and tools
- Step 2: Evaluate and build an enterprise-wide framework
- Step 3: Adopt the framework with quick-win pilots
- Step 4: Scale to implement the AI ecosystem in production
The age of AI is already here. Far from another industry buzzword, AI is already offering a multitude of benefits for Authorized Institutions that remove inefficiencies, take user experience to the next level and offer new revenue opportunities across the banking value chain.
Proper AI governance can help to navigate the many challenges and issues concerning bias, personal data usage, explainability and compliance. It is a must-have if you do not want your AI journey derailed.