Accelerated Innovation-AI using AI in Financial Services - To Grow Business and Make Life Better

January 31st 2025 | 33rd edition, 'Being Human in the Age of AI 'series of the Mindvista newsletter. The goal is to explore and present new ways of thinking and ideas for driving agency and adoption of AI for self, enterprise, and society.

Editions so far : 15 editions on work and life ; 8 on enterprise adoption of AI ; 7 on AI for public good (healthcare and finance); Accelerated Innovation AI with AI - 1 on Deepseek AI disruption

Future editions AI on AI : Financial Services, Healthcare, Technology, Retail and CPG, Energy and Materials, Industrial, Infrastructure, Travel Transportation and Logistics, Media and Entertainment and Agriculture.

These editions I believe could help increase your awareness of AI and its impact, exploration of ideas, find ways to be part of A initiatives. The aim is to thrive in the Age of AI.

If you agree, do subscribe so as to not miss the Mindvista Newsletter editions in your feed at -https://www.dhirubhai.net/newsletters/mindvista-7205504077915443200/.

Context Recap

2024 has seen an early majority of enterprises begin the adoption journey for AI in the enterprise . The statistics are telling when you compare AI adoption in 2023 vs 2024:((See Side Bar) .

Yet lot of the POCs and pilots are about saving costs by reducing labor and process cycle times . For instance Klara, the leader in BNPL (Buy Now Pay Later) , who has been an enthusiastic AI adopter is on record that AI implementation for customer service output is the equivalent of 700 staff and in future all jobs including CEO’s! can be done by AI.

While no one will argue against improved efficiency, focusing solely on cost efficiency misses the opportunity to think anew and use AI to drive grounded disruption and create new services/ products and revenue. In the 19th edition of the Mindvista newsletter for example illustrated new ideas for Apple , Marriott and LinkedIn. We also wrote about Bi Modal Enterprise AI adoption in the 14th edition,

Coincidentally, the latest(January 2025)research from Mckinsey has shifted focus in AI from adoption to agency.

Titled - “Superagency in the workplace: Empowering people to unlock AI’s full potential “ the research presents interesting and supportive of this view:

• 47% of the C-suite say their companies are developing gen AI tools too slowly
• 80% of companies have seen < 5% revenue impact; 40% have seen increase in costs by 20%
• 3x more employees are using gen AI; it is much more than their leaders imagine and yet 2.4x C-suite are more likely to cite employees readiness as a key barrier
• Employees are ready for AI; now leaders must step up.

How Can Leaders Step Up

As quoted in the 32nd editon, Dr APJ Abdul Kalam, the former President of India, said- “Small ambition is a crime” . There is no room for small ambition on technology .

The Mckinsey research also provides a framework with six success factors (roadmap, talent, operating, technology, data and activation and scaling).

In the AI for AI series we started with AI disrupting itself about Deep seek (32nd edition) and will explore conceptual and real-world examples of innovation to create new services/products for revenue creation and improving life in all key industries.

AI in Financial Services (FS)

Historically. Financial Services (Banking and Capital Markets) has been the largest investor in IT amongst all industries. Over time, the sustained investments have created complex and yet efficient and reliable IT that runs 24 x 7; is global in footprint and compliant to local regulations in every jurisdiction. It turns out that despite the advanced state of IT and necessary caution and compliance constraints, FS also has several excellent real world innovations in FS using AI.

While not being a comprehensive or a complete list, here is an illustrative set of five very interesting AI led innovation in FS in three in core business functions- lending, annuity and wealth management and finally surprisingly on IT itself.

1. Lending Innovation - Kiva - Microcredit

Kiva uses AI algorithms to assess credit risk for microloans, allowing them to serve entrepreneurs in developing countries who lack traditional credit histories. Their AI model analyzes alternative data to make lending decisions, thus opening up new markets for microcredit.

AI Utilization: Kiva indeed uses AI to expand microcredit access. Their system employs machine learning algorithms to analyze alternative data for credit risk assessment, which includes:

• Social media activity
• Mobile phone usage patterns
• Payment history from non-traditional sources
• Kiva's models retrain weekly using new repayment data from 80+ countries"

This allows Kiva to make lending decisions for borrowers who do not have conventional credit scores. The AI model helps in identifying patterns and correlations that traditional credit scoring misses, thereby enabling Kiva to serve a new market of underbanked individuals and entrepreneurs.

2.Lending Innovation - Upstart - Underserved

Upstart is a leading AI lending platform that partners with banks and credit unions to expand access to affordable credit.

They leverage AI to transform traditional lending processes, using over 1,500 variables beyond credit scores to assess borrower creditworthiness. Their AI-driven platform employs machine learning models for data-driven credit assessment, automated underwriting, and dynamic risk adjustment. Upstart's AI enables higher approval rates, potentially lower interest rates, and promotes financial inclusion by reducing bias in lending decisions. The platform provides a seamless, digital-first experience with personalized loan offers, integrating with financial institutions to scale AI-driven lending solutions efficiently.

With Upstart, credit unions can approve over 43% more borrowers than traditional credit score-based models with low default rates.

3.BlackRock LifePath Target Date Funds With An Annuity

BlackRock's LifePath Paycheck is an AI-driven retirement solution that dynamically adjusts investment strategies based on individual retirement goals, life expectancy, and market conditions. It's designed to provide a "paycheck" in retirement, redefining how retirement funds are managed.

AI Utilization: While the primary innovation in LifePath Paycheck is the product design (offering a pay check-like income in retirement), AI plays a critical role behind the scenes:

• Dynamic Asset Allocation: AI algorithms are used for real-time portfolio management, adjusting investments based on current market conditions, participant age, and personal risk profiles.
• Predictive Analytics for Longevity and Financial Needs: AI models predict life expectancy and future financial needs, ensuring that the retirement strategy adapts to both individual circumstances and broader economic trends like inflation rates or market volatility.
• Risk Management: AI helps in managing the financial risk associated with providing guaranteed income streams, by modeling various economic scenarios and adjusting strategies accordingly.

4.Betterment (Wealth Management)

Betterment is notable for its AI-driven robo-advisor service, which has expanded wealth management to a broader audience by offering low-cost, personalised investment advice.

Their AI creates and manages personalised portfolios based on individual risk profiles and financial goals. Betterment's AI processes 14TB of market data daily for portfolio adjustments . Other key innovations include automated tax-loss harvesting, behavioral finance insights to prevent common investment mistakes, and goal-based investing that adapts strategies as user needs evolve.

Betterment's AI also powers scenario analysis tools, simulating various market conditions to enhance financial decision-making and education,

Accelerated Innovation - Business and Social Impact of AI

Being private we don't have revenue or growth numbers for all to report but there are lead indicators that they are very successful-

• Kiva has disbursed $2B loans , secured a $7M seed funding and won best peer to peer small lending US News and Money.
• Upstart reported 3Q'24 revenue of $162M, 27% growth sequentially. They won the best lender award from CNBC for borrower with no credit history and looking for longer term, their raison' d etre.
• Betterment serves over 900000 customers with $50B AUM. It has won several awards as the best robo advisor platform.
• Blackrock LifePath is the fastest growing lifetime income target-date strategy in the defined contribution market. They closed 2024 with $16B AUM and crossed 200000 US worker annuity holders.

This does not mean there are no challenges or they have reached maturity.

Kiva faces 12% default rate for example a tradeoff for financial inclusion. Upstart's models already undergo quarterly fairness audits under CFPB guidelines and there is a need to test models continously for ethics and bias even is at grows. Likewise BlackRock's AI complies with ERISA fiduciary rules through explainability which they need to do continously.and LifePath still is a very small part of BlackRock’s $11.5 trillion AUM.

But the hard part, to begin has begun.

5.Block (formerly Square) - FS Tech Open-Source Disruption

While these AI driven innovation have created new revenues from new services and new markets, Block did something unprecedented, open-source AI Agent the latest in AI in FS industry where technology edge is fiercely guarded.

Block, formerly known as Square, Inc., is a technology company that provides a range of financial services and business tools. Founded by Jack Dorsey and Jim McKelvey in 2009, Block's mission is to empower the economy by making it easier for anyone to start, run, and grow a business. The company is best known for its Square hardware and software solutions that enable merchants to accept card payments on their mobile devices, significantly simplifying the payment process for small businesses.

Block has launched Goose, an open-source AI agent, marking a significant departure from the conventional secretive approach to technology in financial services. Goose integrates with Block's existing platforms like Square and Cash App, allowing for automation of various tasks through AI. By making Goose open-source, Block has essentially invited the global developer community to contribute to, enhance, and adapt the technology for a multitude of applications, especially within the financial services sector where proprietary tech has long been the norm.

Block's Open-Source Benefits:

With Block’s open-sourcing of Goose in a traditionally closed industry marks a disruption and everybody gains as we see with open-source in general- democratization of AI tools, faster innovation and interoperability and flexibiility.

What needs a special mention is how Block benefits in addition from this bold move. it establishes Block as a pioneer in open innovation within finance, potentially attracting a broader developer community to contribute to its ecosystem and gain favor with customers who value open-source tech. FInally it also encourage partnerships and integrations, expanding Block's reach and influence in the financial technology space.

Takeaways

These five examples - from Kiva's microlending to Block's open-source initiative - demonstrate how AI can create new value in financial services through both product innovation and radical openness. While each took different approaches, they all moved beyond mere efficiency gains to unlock new markets, serve new customers, or create entirely new business models. As enterprises look to increase their AI investments, these success stories offer valuable lessons for achieving meaningful business impact.

The Mckinsey research also mentions that the C - suite of 92% of companies plan to increase their investment in the next 3 years but also expect “ Super Agency” and that AI should deliver more than 5% revenue growth in next three years . Currently only 20% achieve that and the research calls out the the need for big ambition.

To this, we add that big ambition means creating new services/products using AI and disrupt status quo.

We live in a world where the art of possible is getting democratized. Being efficient is one and being disruptive is another. Both are paths to pursue.

To do the disruptive, the key questions to ask are:

1.What are the hard problems to solve in your business and function?

2. What will be the value that can be created by solving this problem?

3. How will AI enable the solution?

4. What is internal and external (partners) agency needed to plan and execute?

5. How do I be part of this change in your industry with your know how and skills ?

Please share your comments, thoughts and ideas on the above and views on industry focus.

Final Word

In the last edition we saw a small team at Deepseek disrupt AI itself and here we see real examples in Financial Services. No doubt we will find impactful and exciting ones as we cover key industries in the upcoming editions.

In democratized AI, Any one, any team, any where can do any thing if they can, if they have the courage, intelligence and tenacity.

And the time is now.

What a promising start to 2025—the first year of the next quarter-century.

Explore and stay tuned for more!

Cheers

Side bar Enterprise AI adoption

• In 2023, 55% of companies had integrated AI into at least one business function. By 2024, this number jumped to 72%, representing a substantial leap in adoption ( Source : Statista)
• In 2023, only 18% of organizations had deployed AI in production, with 24% engaged in pilot projects By 2024, nearly a third of businesses were running AI in production, and the share of organizations with mature AI initiatives doubled from 4% to 8% (Source: Enterprise Strategy Group)
• 92% of respondents reported an increase in AI use in their organization over the previous 12 months’ ((Source: Enterprise Strategy Group)
• Organizations are pursuing multiple AI experiments, with most running 20 or fewer experiments or POC and over two-thirds said that 30% or fewer of their experiments will be fully scaled in the next three to six months.(Source: Deloitte)