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Signals from our talks with Banks/NBFCs/Unicorn founders & trying to reach the OpenAI team, the RBI Innovation & NPCI teams & community forums
Why should we all care at All? Decision Intelligence, World Model? What is OpenAI going to release next? What is Jev? What’s Decision Intelligence? What’s a Financial World Model?
There are real signals of new & biggest infra that may emerge. These include:
- Decision-Intelligence-as-a-Service at population scale
- Proprietary in-house Decision Intelligence Infra
- Multi-Model Workflows involving mix of World Models, Decision Models & LLMs
- Public-Pvt Decision Intelligence infra & Open-Source innovation acceleration by Regulators like RBI & NPCI
- In 8 min video, we also understand Jev vs OpenAI, Vaayu Financial World Model concepts in real applied scenarios. Not theories.
And we find above topics are & how to attempt to align it to the big boys work. That is OpenAI, RBI, NPCI & Enterprises.
First – Understand the success & arbitrages worth aligning to in the market. Why should we even care about Big Boys.
OpenAI probably succeeded because it aligned what Google was building around it
DeepSeek succeeded because OpenAI was building around Reasoning
Cursor succeeded because Big Tech was building around automating coding
Indian IT succeeded because US IT was doing it & it aligned India’s strength to a market event.
You see, any outsized returns have an iota of possibility when you have Arbitrage.
And above are the arbitrages. At Vaayu, one of our axes is to align our long horizon work to market directions. Capturing arbitrages.
Arbitrage is – you do something & stumble on something valuable that others have yet to catch up.
Deepseek, Cursor & any other startup – made it like this. What we call – being at right place at the right time with right preparation.
They were part of a tiny community that built before the world knew. But there were already signals of what Big Tech was building
In above video, we showcase what OpenAI and Microsoft, Jev are releasing.
But we create benchmark comparisons of the Vaayu Financial World Model
While World Models are used for Robotics, Autonomous Driving, and humanoids. We adapt World Models to Finance.
Financial World Model tell – What’s the next move that a financial institution should take that maximizes ROI at lowest risk.
We are also trying to reach OpenAI team for further customisations needed by BFSI Industry.
Have a look at the 8-min video to see the things in action & learn/know with practical usage of World Models in Finance.
Build your Arbitrage.
The Public-Pvt Digital Decision Intelligence Infra – RBI & NPCI work
Our team also interacted with RBI & NPCI. It’s sort of amazing, the push for innovation. We estimate that new Public-Pvt Decision Intelligence infra may emerge.
Vaayu’s work is around building core infra where the biggest black swan events may happen.
Data Center & Intelligence-as-a-Service by Unicorn startups by monetizing data
Our team also reached to Unicorn startup founders. Including Fintech, Lifestyle & Quick commerce brands. They are sitting on tons of data. Which can be converted into Decision intelligence & served via hosted models or Data centers.
Build Some, Buy Some, Lock none – Decision infra at Banks & NBFCs
- Build Some, Buy Some, Lock None – A senior leader in Banking summed up the approach. It exactly matches what we hear from talks with marquee C-Suie and fintech companies
- Small is fast & low cost – Banks have constraints on Unit economics. Especially while working at scale for new-to-credit financial inclusion. C-suite recognize this.
- SOP – Sovereign, On-premises, Proprietary – Decision Intelligence infra has to be proprietary for many reasons. First, the core intelligence should remain within the enterprise. Second – enterprise needs full control of it – so if you aim to change it, you should be able to do it.
Benchmarking Vaayu Finance World Model with Typed Decision Models – OpenAI & Jev
OpenAI’s Decisions API and the emergence of Jev’s specialised decision models represent an interesting evolution in AI: moving from generative intelligence towards structured, outcome-oriented decision-making.
For financial institutions, this raises an important architectural question:
Should banks build their Decision Intelligence infrastructure around external decision models, or develop smaller, specialised Financial World Models that they can own and operate?
But how do you decide? First & foremost is benchmarking now,how your own models with newer architectures.
Above is a small Vaayu Financial World Model. We don’t claim it is the best yet. But it shows that a much smaller model built on premises for a bank can be quite competitive. This is built on Credit Card default data. Since, we didn’t have access to actual Master data from the bank, we created some synthetic data.
Results show that the outcomes may be promising for a proprietary model trained for banks.
- One – you can see the latency is remarkably lower. Because we deployed a co-located model. This is often used deployment in investment banking to save on latency.
- Second – Cost is much less & trained on proprietary data
- Third – Fully on-premises & full control for the bank
But the major Alpha for Decision Intelligence with World Model
But the major benefits & differentiation of architecture are this:
- This is a World Model. Which can not only give decisions; it can predict multiple outcomes of the action. Eg., how will the overall customer’s state evolve for different actions. Eg – if you offered a top-up on the existing limit – does the propensity of default increase
- Long-range & multi-dimensional reasoning – Do certain events cause 2nd-order & 3rd-order effects down the line after 3-6 months? Eg withdrawal of a subsidy can cause credit stress in certain industrial zones for Solar industries.
- Financial Modelling, not text – One of the reasons even a smaller Financial World Model is becoming competitive is that the model is trained to understand rich relationships between various dimensions of data in a financially native way. It’s different from those that are primarily text- or image-based.
Below are some examples of end usage at the application layer of Decision Models. Which generate interesting events, triggers, arbitrages & then can be tied with autonomous actions
Custom-built World Models
but they reinforce the importance of specialised decision intelligence. Any organization thinking fo Decision Intelligence infra should first have a latest World Model, with organisationDecision Models benchmarked against existing models.
Exploring Design Partnerships
We have been presenting our work to multiple companies across financial services and other industries.
We are now evaluating design partners who would like to explore this approach around specific business problems.
The starting point can be one well-defined use case.
We can understand the existing systems, establish a baseline and benchmark current approaches against specialised models and Vaayu’s World Model.
Over an initial six-month engagement, the objective would be to identify where the technology can make a measurable difference and map the potential economics.
Successful experiments can then move towards deployment through Forward Deployed Engineering.
We believe design partnerships are important for deeptech development. They allow research to be tested against real business conditions, rather than only laboratory benchmarks.
About Vaayu
Vaayu is building deeptech AI infrastructure for enterprise decisions, including custom World Models, specialised reasoning models, R&D-as-a-Service and Forward Deployed Engineering.
We are currently exploring design partnerships with enterprises interested in building proprietary AI capabilities around their data and business decisions.
Further reading: JEPA and World Models for Banks by Vaayu
Related discussion: Vaayu’s presentation at Bajaj Finserv