→ The Rise of AI & ML – Implications for Banking and Financial Services

Presenting My Two Cents – January 2024 edition.

This month we are exploring the exciting developments happening around artificial intelligence (AI) and machine learning (ML) in the finance industry.

As digital transformation continues to accelerate across financial services, advanced technologies like AI and ML are enabling organizations to operate more efficiently, gain valuable insights from data, and deliver highly personalized experiences.

Adoption of these innovations also comes with ethical considerations that the industry must grapple with.

?? Key Developments Driving AI/ML Adoption

Several interrelated factors are fueling the momentum behind AI and ML in finance:

• Accelerated digital transition - COVID-19 necessitated rapid digitization across financial services, setting the stage for AI/ML tools to power everything from customer service chatbots to back-office automation.
• Data proliferation - Vast amounts of data generated across finance operations offer invaluable training data to "teach" machine learning algorithms.
• Increasing compute power - Access to cloud-based computing capacity allows complex ML models to crunch big data more rapidly and cost-effectively.
• Rising customer expectations - Today's consumers and business clients anticipate highly personalized, instantaneous service capabilities enabled by AI/ML.

As these trends converge, financial institutions are tapping AI/ML's potential to transform legacy business models. Incumbents and fintech disruptors alike recognize AI/ML's indispensability.

A 2023 Nvidia survey showed that most financial services practitioners believe they have not invested fast enough in being ready to take advantage of generative AI.

Key Use Cases Reshaping Finance

While AI/ML applications in finance are wide-ranging, a few high-impact use cases stand out:

• Enhanced Predictive Analytics - Sophisticated machine learning algorithms help uncover insights from data to better forecast everything from market trends to credit risk to propensity to churn.
• Enhanced Security - By detecting patterns and anomalies, AI algorithms help institutions guard against fraud and cyber threats
• Hyper-Personalization - Leveraging vast data from customer interactions and transactions, ML tools create tailored product and content recommendations.
• Process Automation - Bots and robotic process automation eliminate tedious manual processes across functions like KYC onboarding.
• Enhanced Security - By detecting patterns and anomalies, AI algorithms help institutions guard against fraud and cyber threats.

As these use cases highlight, AI/ML allows financial organizations to scale services, spur innovation, tighten risk management, and strengthen operational resilience.

For example, although CFPB warned that banks' use of AI could reduce trust, Neobank Dave's new chatbot actually achieved an 89% resolution rate, demonstrating the technology's ability to efficiently address customer inquiries when implemented thoughtfully.

Key Ethical Considerations

However, as AI/ML becomes further ingrained, pertinent ethical questions arise that the industry must address:

• Potential for bias encoded within algorithms
• Lack of transparency around certain "black box" AI models
• Responsible for handling sensitive customer data
• Job displacement risks associated with automation

When looking at the regulatory landscape, it’s at an embryonic stage at present. As firms work to address ethical issues, a tricky balancing act emerges between not hampering progress and respecting necessary guardrails.

However, establishing sound governance doesn’t necessitate hampering progress. The firms able to advance AI/ML through a principled lens stand to solidify market positioning plus public trust.

By implementing oversight frameworks, emphasizing responsible data practices, auditing algorithms, and upholding principles aligned with organizational values, financial institutions can propel AI/ML's benefits while safeguarding stakeholder interests.

The path ahead will challenge firms to strike this crucial balance.

?? My Two Cents Worth

In my view, striking an optimal balance between rapidly deploying AI/ML tools and carefully assessing their implications presents a key challenge ahead.

Amid fierce competition, the temptation exists to charge ahead without building appropriate guardrails.

However, establishing sound governance doesn’t necessitate hampering progress. The firms able to advance AI/ML through a principled lens stand to solidify market positioning plus public trust.

Priorities financial institutions should emphasize involve:

• Rigorous testing regimes to minimize algorithmic biases and errors
• Allowing customers visibility into how AI informs decisions impacting them
• Proactive engagement with regulators around evolving best practices
• Upskilling workforces in AI literacy and complementary skills less susceptible to automation

If stakeholders collectively commit to ushering these technologies guided by transparency and accountability, I believe AI/ML innovation can profoundly democratize access to high-quality financial services.

?? Closing Thoughts

As AI/ML become integral to driving finance's digital future, they introduce vast possibilities along with heightened responsibilities. Technology is not ethically neutral. It reflects and amplifies our priorities as creators.

The institutions that thrive in this climate will align emerging capabilities with the values of transparency, accountability, and democratized access that build trust and shared prosperity.

Those laying these foundations today stand to shape a more inclusive and empowering financial system for generations to come.

What AI/ML applications in finance excite or concern you? How can we steer these tools toward serving broader societal interests?

?? Banking Sector Month in Review

• Citi to cut 20,000 jobs through 2026, swings to $1.8 billion loss (via Khaleej Times )
• ‘Magnificent Seven’ Warning, IPO Return Among BofA's 10 Surprises on Wall Street (via 彭博资讯 )
• The Bond Market Rally Is Overlooking a Soaring $2 Trillion Debt Problem (via Yahoo Finance )
• Last year was likely the best ever for JPMorgan. It may not be able to do better in 2024 (via Yahoo Finance )
• ‘$16 Trillion By 2030’—Crypto Now Braced For A 2024 JPMorgan And Wall Street Earthquake Amid Bitcoin, Ethereum, Solana And XRP Price Boom (via Forbes )

?? Next Edition Preview: The Rise of Neobanks and Challenger Banks