Value shifts in Indian Financial Services through the lens of L* K* TFP
Cobb-Douglas function provides a useful way to frame the value shifts underway in Indian Financial Services — Banks, NBFCs, and FinTechs. By breaking it down very broadly into labor, capital and technology/total factor productivity — one can interpret what, why, how and what next.
This post is about technology (or in C-B language Total Factor Productivity) and it’s real implications on people (or in C-B language Labor).
One of the biggest shifts of the last decade in mainstream financial services has been the massive change in labor productivity by using technology / IP.
Why did the tech transformation start with labour? It was natural because employees typically comprise the single largest element (>50%) in the cost stack of typical financial institutions(*). Any improvements create tangible competitive advantage — ability to generate relatively higher returns sustainably.
When done thoughtfully the employee productivity has typically improved by 30–50% (depending on the baseline operating maturity). To be fair, so far, this shift has been seen mostly in customer facing operations and within those products-segments which are heavily dematerialized by nature. Prime / near-prime retail or commercial segments and non-collateralized products are predominantly dematerialized in terms of the data and asset/collateral or lack thereof. So they have seen the first wave (1).
An important aside: next wave of tech transformation is focusing on the collateralized or cashflow backed small to mid-ticket loans. Wholesale segments are ripe for disruption too. Important distinction — the disruption of larger ticket segments will be driven primarily for ensuring efficiency in capital allocation and portfolio management vs. labor productivity. More on that later.
At first look, this transformation seems primarily about modern loan origination and loan management systems, digital deviation workflows, UI/UX, data lakes, score cards/models, rule engines and API integrations.
However, the real magic happens at the intersection of technology and people. Technology intervention has to be accompanied by significant re-skilling and changes in ways-of-working. This to me is the biggest hidden mega shift. When done right, it leads to some combination of better risk decisions, capital efficiency, customer loyalty and employee morale. This shift has not fully played out because it impacts the entire organization. The board, serious investors and senior leadership need to have deep personal appreciation of this issue for the transformation to deliver value.
Organizations, while still hierarchical in a risk management sense, have to change from being command-and-control oriented to problem solving oriented. Command-and-control was a great strategy in the past to ensure process adherence across the value chain. Now the process is already getting hard wired in a tech workflow. While process deviations still need to be managed, the long-term challenge is not adherence. The long-term challenge is how to stay at the cutting edge of technology deployment in operations. That requires everyday tech enabled problem solving — top to bottom and left to right.
Employees who want to be problem solvers need to have very different mindset and skillset than those who want to operate in a command-and-control structures. The role of the employees is to understand technology, understand their business (within their role’s scope) and problem solve in a rigorous and continuous manner. Its needs the teams to be staffed differently. Most importantly, the people need to be trained to do everyday problem solving without directive supervision or upward delegation.
This extends to the leaders and managers too. Anyone who has attempted to change the approach for a proven leader who has achieved success in the command and control world knows that it is very hard — people become victims of their own success. For the managers and leaders this means two things — (a) becoming deeply knowledgeable about technology — its applications, benefits and risks and (b) getting comfortable with not giving directive instructions but instead actively focusing on prioritizing the team’s effort while managing risks to ensure outcomes.
All this takes time and effort. This needs to be a high priority agenda item for boards / senior business leaders / investors. Without solving for this issue — the tech benefits will decay or sustained adoption will suffer.
Finally, it can be an entirely uplifting and simultaneous very difficult experience for people as they migrate from being mere “Labor” in the C-B function to a much more value added role. As employees become stronger at technology and problem solving — the returns to labor will increase relative to returns to capital. In simple terms — this could translate into better compensation and hopefully more even allocation of returns. This is altogether a very good thing!
To conclude, if today I were…
an entry level employee → I would learn coding and math besides just operations; or ask myself who I am — an instruction taker or problem solver and seek employment accordingly
a CEO → I would build teams of problem solvers and change ways of working of my organization (and I would learn coding + math :-))
putting my capital at risk → I would deploy it in businesses that are bottom-up changing the operating models in large central revenue pools (and I would learn coding + math :-))
In subsequent posts I will discuss more thoughts on interplay between customer / capital / risk / technology…
(1) However, the post onboarding operations and servicing are generally speaking years behind and underinvested in.
All views are personal.