#58 Riding the Third Wave: Kamal Budhabhatti’s Journey from Mobile Banking to AI Transformation in Africa - Lessons for Digital Banking Platforms

After revolutionising Africa’s financial sector with mobile banking and super apps, Kamal Budhabhatti is now leading the charge into AI, defining the future of digital banking on the continent.

Artwork by Mary Mogoi - Website

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One can almost trace the origins of Africa’s digital banking industry to two gentlemen in the late 80s and early 90s when Barry Ryan and Justin Chinyanta founded Fintech International Group, now part of Loita Group. The two men were former Citi Executives and they had seen a gap in the provision of digital banking services. Banks and MicroFinance Institutions were being formed left right and centre and app-server technology was coming into the mainstream due to the growth of the internet and networking technology. Banks needed to modernise their technology from their core banking systems all the way to their customer facing systems Western software was too expensive and therefore local solutions needed to be built. Fintech was indeed a pioneer and built systems across the continent. This company birthed a number of digital banking companies such as Eclectics and many others. It can be considered the Fairchild Semiconductor company for Africa’s digital banking boom.

Whereas Barry and Justin came from the storied halls of Citi and HSBC, Kamal Budhabatti took a more circuitous route. He came to Kenya initially as an immigrant worker, toiling in one of the numerous manufacturing facilities scattered across Nairobi’s Industrial Area, an industrial expanse sandwiched between the Jomo Kenyatta International Airport and the Nairobi Railway Station. This stint didn’t end well and he was soon to be deported back to India by his employer. Whilst in Nairobi as a labourer, he had started dabbling in technology, building primitive banking software. Not to be deterred, in India, he found a way back to Kenya now as an entrepreneur and with the laser-like focus to build something of his own. Kamal got to work building banking and microfinance software. He got a break in the early 2000s, working with Dr. James Mwangi of Equity Bank to build Bankers Realm, the core system that Equity used until they upgraded to Finacle. Dr. Mwangi taught the young Kamal all about banking and particularly how bank ledgers worked, on his part, Kamal taught Dr. Mwangi all about technology. This initial break laid the foundation for what is now Craft Silicon. A sprawling digital banking business with deployments all across Africa and Asia. With over 150 million people using their digital banking products everyday and with the company making revenues of just under US$ 100 million annually. Craft Silicon is a major player in Africa’s core and digital banking market. Their systems are deployed in every African country bar South Africa. It’s a testament to the grit and determination that made Kamal take that second journey back to Kenya.

Source: Craft Silicon

In 2016 together with Safaricom, Kamal launched Little Cab. Little Cab is a super-app modelled around the South East Asian super apps such as GoTo and Grab. It’s built around the idea of daily life services such as mobility, food and entertainment. In his words, the idea of founding Little Cab “stemmed from a concern that banks would eventually develop their own technology in-house, diminishing the need for companies like Craft Silicon”. Little Cab is arguably East Africa’s largest Fintech super-app with over 5 million users. Whilst it competes with Uber and Bolt, it has found a niche in corporate services given its ability to build custom solutions for corporate clients.

Kamal has built his companies in such a way that he’s free to focus on his core skill of being a technical innovator. The first time I met him at his office, I was taken aback by not only his diminutive and gentle stature, but also his blood shot eyes, reflecting a week of all-nighters. As the self-described Head of Product Dreams and Designs at Craft Silicon and Little, Kamal spends his time ideating and solving hard technical problems.

Having successfully rode the first technology wave of the early 2000s with Craft Silicon and the second smartphone era wave by building Little Cab, Kamal is best placed to ride this next wave of AI. Who better then, I thought to myself, to walk us through how the digital banking industry should navigate the AI wave. What keeps him up at night? What core advantages does Craft Silicon have and what are the challenges and opportunities that will be thrown up by this AI wave? His insights should be useful for the entire digital banking space. 

I sat down with Kamal one Friday afternoon at his office for a long-ranging conversation on AI and Fintech. The article will cover the following;

1. Why Digital Banking Platforms need to embrace AI;

2. How Craft Silicon is approaching AI;

3. Practical guide on executing AI as a digital banking platform;

4. How to commercialise AI as a digital banking

5. Some thoughts around the future and the role we play in it;

Why Digital Banking Platforms need to embrace AI

I wrote before about AI in financial services, the first part covered what AI is and I went quite deep. The second article was based on some predictions of what will happen to the banking industry. One of the predictions I made was that Digital Banking platforms are on shaky ground given that banks will have the capabilities to bring everything in-house. It’s a framework that Kamal has shared and maybe not to the same extent as me. Kamal’s move into AI is borne out of both commercial logic and existential fear.

In terms of commercial logic, the fundamental difference between machine learning and neural networks was so big that Craft Silicon realised that this is a complete paradigm shift in terms of technological capabilities. I asked Kamal why Craft is investing in AI and what’s informing this move into AI and he had this to say;

Kamal: So, before ChatGPT came in, we were trying to do a lot of things in machine learning because we have so much data with us, and if today I aggregate all the customers between here and India, we're actually crossing 150 million consumers using Craft Silicon. We have so much of this data, and we then at some point started writing machine learning algorithms for credit scoring. Okay, we tried, but it didn't come up the way we had envisaged. And then at some point, the chatbots came in, ChatGPT came in, Big Data came in. And I think it just changed everything. We looked at our data, and we quickly realised that this is the future. Everyone would require something to do with AI, and AI is not going to be a separate component. It has to be embedded in your day-to-day operation. So it's not like, this is my AI software, it has to blend in with what you are doing.

Samora: Yeah, so I've got two questions there. So machine learning is just putting structured information within an algorithm, whereas what we've seen in Chat GPT is more around unstructured data and  deep neural networks. So when you said that the machine learning thing didn't work, was it an architectural thing, or was it more of the business dynamics?

Kamal: No, it didn't work in a way that I think the neural networks were able to deliver better outcomes. So, at that time when we were just doing machine learning for us, even the customers appreciated it was giving good results. But now, when we look back we would say, "Oh my god, that thing we were doing was pretty, you know," in a bad state.

Samora: Exactly.

Kamal: So, on AI, I think conversational AI is going to be also quite big even in the banking industry, not for decision making, but for taking off some of the load from the customer. The best way to interact with AI, I personally think, is going to be voice. So we are working on voice, we are working on text, and we are also working on images, but everything currently is revolving around our existing customers, our banking and fintech customers. 

In essence, tinkering with both machine learning and neural networks given his role as the chief scientist at Craft Silicon led Kamal to the natural conclusion that AI is a platform change that should inform the next wave for Craft Silicon. In fact, the discussion focused on how it’s a matter of life and death for digital banking platforms;

Samora: I think that's very important when you're having such a platform change to have someone who's just spending time thinking, learning and reading about this stuff.

Kamal: Yeah.

Kamal: Because for us it's also survival. We are in that mode. If we don't take that step at the moment and the companies that are not taking this seriously, if another company doesn't think of it the way we are thinking, maybe in a few years they will become irrelevant.

Samora: Yeah, a lot of people in that industry are going to become completely irrelevant because it's a 100 times improvement. So if you have a bank that has fully functioning AI and it's helping customers in all sorts of ways and you have a bank that's still using plain mobile banking, it's not even a comparison, even the shareholders will tell that bank what the hell are you doing? 

Kamal: Yeah.

Kamal: And so it's a big change for us and I think many of these companies. We need to take this very seriously. This shift has to start happening as soon as possible otherwise at the last moment it can fall apart.

The AI opportunity for digital banking platforms is based on a technical realisation that AI is a platform shift and therefore, there needs to be renewed focus on AI enablement. This renewed focus will cause further disruption in the industry and will be an existential risk for many existing players if they don’t pivot towards AI enablement.

The obvious next discussion therefore is, what approach should be taken to pivot from traditional digital banking platforms and towards AI enablement?

How Craft Silicon is approaching its AI Journey

While there may not be a sure fire way of ensuring success in becoming an AI enabler for the banking ecosystem, Kamal’s approach is based on logic and hard earned commercial experience. It reflects a mix of caution and boldness that comes with decades of building scalable banking systems across the continent.

Experimentation & The Need to Build Trust

AI is full of unknown unknowns given the state of constant innovation that is happening at the edge of AI and the uncertainty as to how the final end state for consumer financial services will be. Given this, Craft Silicon is focusing on both building trust and constantly experimenting. Kamal started off this section by asking my about my views on something they’re working on;

Kamal: We are doing something, I want to validate that with you. So, what we want to do, as the first thing, is, on your mobile banking, because that's what we want to pilot with. Before even a customer logs in, there is a chatbot. And in both voice and text, a customer can ask for any information about the bank. Once he logs in, then the customer is already authenticated. We put the data for that customer, and let the customer interact with that data. So, it's not going to make any decision on his behalf, but the retrieval of the information is going to be on a separate level. I need to see my account balance. I don't need to go to this app and navigate numerous buttons. I could just ask or I could just speak to it, and it gets me the info. That's the first thing that we want to roll out, very basic.

Samora: You made some good points around it being like a multi-step thing. You won't start at the end. You won't start with this advanced AI that does everything for you. In so far as it's a first step, that's great. The way I think about AI, especially in financial services, is that it should enable things that weren't possible before, in a much more dramatic fashion. When I look at myself, I've worked in a bank. And then when you leave, you look at yourself as a customer, not a banker, right? You leave that industry and start looking at banking apps the same way you look at them as a customer, not as a producer. And the thing that I always think about is that I have financial objectives. I have financial goals, and I need this thing to help me reach my financial goals. I think that's one of the main things, so I think when you're launching, that that's fine in so far as it enables people to start interacting with their bank like they would with an AI.

This idea of experimenting and starting with an MVP if you will is built on the idea of trust. Kamal expounds on this;

Kamal: Yeah, I think the reason we approached it like that is I feel that a customer needs to build trust with the AI components.  From day one, if you let the AI start advising you, I think confusion will start happening because it might advise something, and I might not take that advice, or I might blindly act on the advice, and fail. I would then never come back to it ever again. So, I think this journey of giving, in, in slow doses, is to gain the trust of a customer. Okay, fine, today you do this. Come tomorrow, maybe he'll say, "Okay, send airtime to my wife, my daughter," and the system will be able to do some financial transaction of a smaller level then grow from there.

Samora: And if you think about it, that's how ChatGPT has done it, right? They just launched ChatGPT. The whole idea was, "What is the form factor for AI?" Their innovation was that the form factor should be a chatbot, and then slowly they added voice. Slowly they've added a number of things, and a lot of people now discuss really personal things with ChatGPT. As a starting point, get someone used to AI, right? And I think it's going to be like a real game changer, in the sense that  you now have a relationship with your bank.

It’s a very logical approach and I brought out the parallels with ChatGPT given the way people are now using ChatGPT. The video below shows the kind of trust people can build with their ChatGPT given the advanced voice features. It’s this trust that Kamal thinks is critical to build from the start and that can only start with small, timed releases;

Ever the instigator, my thinking was that, if Craft Silicon has access to all this data and has built expertise in AI; why not build a customer proposition that sits in between banks and truly empowers the customer. Ultimately, with their visibility, they can add more value to the customer this way and dis-intermediate banks to a level. His response reflected the caution that is required when there are so many unknowns;

Kamal: It’s something that you know we had also thought of it that should we go out as an independent player working across you know all the financial institutions? or pick up somebody and start from there? We felt that to start with we need to hold hands with somebody and then that's what we are doing. What you are saying though I think is completely something that will happen at some point because a customer needs to get more and more choices where everyone will start communicating with each other. The Customer is least bothered about what is coming from where he just needs financial services delivered to him.

This caution is warranted, so how do you choose the bank you will work with and how do you work with them?

Choice of Bank

Given the need to experiment and the need for speed, Kamal thinks that wasting time with politics is a drag. Rather, it’s important to find a commercially minded bank that wants to get started on these experiments.

Kamal: The big banks are all our clients or we deal with every bank in this country and every bank in East Africa. I think we deal with most and several other banks outside East Africa. Picking up the right bank is very critical. I don't want to go to Bank K, I don't want to go to Bank E for this. However a bank like Bank N for example and Bank S, you know these are the banks are big enough but also agile enough.

Samora: Yeah. My experience has always been that owner operated banks of a specific size are the ones that really innovate.

Kamal: Yeah. And then a lot of politics comes into the bank itself. There are some people who want to support us, some people who have somebody else… You also want to make sure that you have your focus on what you want to do. You don't want to waste your time fighting other battles and the main battle is lost.

Samora: Yeah. And if experimentation is the key factor, then the size of the bank doesn't matter.

How to work with the bank you choose - Again, experimentation

It’s clear that you shouldn’t work with a bank that’s mired in politics. This was my experience at Sote as well. If you’re bringing in a new innovation, it’s important to work with a bank that’s willing to co-create.

Kamal: And actually that's what is happening. We have a customer who we are working with them to create some AI strategy, but still at a very infancy level because AI is, as much as everyone is talking about AI and say, "Oh my god, this is going to do wonders" as we move forward, but I think nobody has really created a core, both competency and the control centre for AI. The MD talks about AI, the CIO is talking about it, somebody else is talking about it, but they've not sat down together and said, "Let's have a clear strategy." It's a very vague strategy. We are now coming into the picture and saying, "Look, allow us to try and don't take this as it's going to start generating returns and profits from day one. Allow us to experiment. Allocate some budget, we try 10 things. They might look fancy. Maybe from 10, eight will fail, two will pass, but allow us to do that because if you will not do that, then it may become very difficult at some point when you want to launch. So, get into that day-to-day operation of using and experiencing the AI. So that’s where we are with Blue Beetle which has been formed by Craft Silicon specifically for AI experimentation.

Samora: Simply, what you're saying is that you're looking at the first step and saying, '”Guys, it may not make sense to have a hard-coded strategy right now. It's good to have a strategy, but it shouldn't be hard-coded. Rather, let's run a series of experiments. Let this team set up like some credit analysis, let this team do custom onboarding. let this team do an app that's just pure AI that is voice-based, and let's see what works, right?" 

Kamal: Yeah.

Samora: But that's not how banks traditionally operate. They operate on business cases, so, how are you navigating that?

Kamal: And so that's where players like us come into the picture, who have worked with these banks for a very long time, we need to convince them. So, as a new player, who is good at AI but doesn’t have relationships, it will be difficult. When we walk in, they have worked with us for several years. I think we have more convincing power in the banking industry. 

How to actually execute AI as a digital banking platform