Welcome back to the second instalment of our blog series which explores the dynamic interplay between generative AI and the banking, financial services, and insurance (BFSI) sector in Southeast Asia. In our previous post, we explored the transformative potential of generative AI in reshaping the landscape of BFSI. Building upon that foundation, let's zero in on a few key areas.

Risk and compliance
The financial services sector primarily revolves around the risk function. The need for objective, accurate and timely data is imperative for regulation, compliance, and risk reporting. The spectrum of responsibilities within this realm is vast – ranging from data aggregation and aligning it with risk profiles to ensuring compliance with global and local regulations, all while benchmarking against internal risk frameworks and industry peers. This makes it a fertile ground for generative AI to be deployed.

Through strategic training on historical data and regulatory blueprints, generative AI can emerge as a game-changing ally – capable of automating a substantial 40-50% of these intricate tasks. It can also be the sentry that raises red flags upon detection of parameters values crossing regulatory stipulations. Imagine a scenario where no conditions are overlooked due to human oversight or fatigue – ensuring 100% compliance at all times.

Customer service
Hyper-personalized services delivered in near real-time will be defining the nature of customer service. Whether it is opening an account, simple-medium complexity query resolution, card issuance or basic loan approval, generative AI can upend these services through personalization and speed. Areas like credit checks, KYC, as well as reward and loyalty programs too can undergo a sea change due to generative AI’s ability to analyze vast amounts of historical financial data, transaction records, and customer behaviour patterns.

Microsoft recently introduced generative AI into their digital contact centre platform so that generative AI can be integrated into every step of the service journey. This includes voice biometric authentication, sentiment assessment, message translation and call transcription, all in real-time – plus virtual assistants, AI Copilot and conversational AI.

Wealth management
Generative AI can be a copilot to advisors across wealth functions. Financial planners and asset managers can generate data-centric skeletal financial plans through generative AI and refine them to align with the client’s risk tolerance and financial goals.

By simulating various market scenarios and stress-testing portfolios, AI-powered tools can provide insights into potential risks and guide the selection of risk-mitigation strategies.

Training and modeling will be key for success, requiring tremendous amounts of historical data, new models, and integration with the bank’s own investment strategy, including risk-tiering of customers who receive this advice. On the customer front too, AI generated report summaries can help clients save valuable time.

Challenges posed by generative AI
Specific challenges do threaten to derail generative AI adoption in the BFSI sector if not addressed appropriately:

• Data privacy and security: The safety of sensitive financial data is paramount. The fact that generative AI relies on big datasets makes it all the more imperative that financial information remains secure.
• Bias and ethical considerations: Generative AI can inadvertently amplify biases in the data it is trained on. AI-generated content may also be misleading, inappropriate or harmful, leading to ethical considerations. Striking a balance between innovation and responsible AI deployment is crucial.
• Compliance and context: Adhering to local and global regulations is a prerequisite for AI adoption in the financial services sector. AI models can run into hurdles when they fail to understand local contexts and nuanced linguistic elements such as sarcasm and humour.
• Transparency: The opacity of AI algorithms poses challenges in understanding how decisions are reached. AI "black box" models often result in accountability and trust issues among regulators, clients, and stakeholders.

The landscape is ripe with significant opportunities spanning diverse use cases for BFSI players to embrace responsible AI deployment. Industry players must equip themselves for the transformations that generative AI will usher into the sector, all while ensuring accountability, compliance, and ethical considerations remain at the forefront.

Learn more about how generative AI will impact financial services in Southeast Asia here.