Synopsis: With lenders increasingly becoming reliant on tech systems to provide quick and seamless credit services to their clients, the accumulation of software entropy in their systems has become a cause for concern. In today’s blog, we will discuss how reducing software entropy can help improve the stability of their systems, unlocking the potential for exponential growth and success.
With digitalization becoming the new mainstay, the financial industry has continued to evolve exponentially. The ease and speed at which the information gets processed, in conjunction with an expansion in overall connectivity, have improved the service quality both at the customer end and backend offices.
While a plethora of financial institutions have leveraged this tech revolution to introduce new products, particularly in the digital lending space, this phenomenon of “anytime, anywhere” finance has come at a cost. Owing to the inherent nature of fintech, which involves a heavy reliance on software-led systems to provide reliable and faster services, it also suffers from its typical pitfalls — software entropy at the forefront of concerns.
So, what is software entropy, and why is it essential for lenders to reduce it?
The Problem with Tech-Based Lending
At its heart, fintech embraces the use of software and digital technology, including big data, cloud technology, artificial intelligence, and machine learning, for delivering financial services.
However, all innovative financial platforms must deal with the dilemma of choosing between quality, cost, and speed. For instance, when a lender wants to introduce a new credit product, their objective is to do so swiftly and at economical costs, without unduly compromising on quality.
But this isn’t possible for startups because of funding and time restraints. Consequently, the lenders’ dev team is forced to choose a coding solution that isn’t overly complicated and is quicker to release, making massive cost and time savings.
As a result, lenders end up launching a product that is originally safe for introduction but is harder to scale. This is where software entropy comes into the picture.
Understanding Software Entropy
It is no secret that tech processes undergo constant evolution; the development team must write and rewrite their codes, scan for bugs in the system, and add new features per the company’s requirements.
However, making these changes becomes increasingly complex with time, more so when the foundational code is sub-par.
So, the phenomenon that occurs when, in a closed system, it is no longer feasible to improve product quality is called software entropy. It means that as the lender modifies its processes, the “entropy,” or chaos, in the system escalates further.
Basically, software entropy is the state in which no matter how hard the developers try to improve their code, the software ends up deteriorating further; further modifications complicate the code with no corresponding product improvement. Subsequently, the developers are forced to write code afresh, resulting in substantial costs.
Additionally, software entropy can also accumulate involuntarily in a lender’s system because of changes in project requirements and system development; these changes are even harder to deal with because they haven’t come about through the conscious choice of prioritizing speedy delivery over code quality.
So, what are the consequences of software entropy building up in the lenders’ systems?
Why is Reducing Software Entropy Necessary?
As the software deteriorates over time, it begins to lose its usability. This could manifest in the form of lenders incurring high personnel and maintenance costs to maintain the system’s agility, increased security breaches, lower productivity, and higher system downtimes, which worsen the customer experience. Reducing software entropy is imperative for lenders to avoid the following negative consequences:
1. Reduced Software Agility: As software entropy results in system deterioration, it exponentially raises the instance of system errors, crashes, and downtime, which has severe repercussions for a lender’s reputation and service quality.
2. Slowdown in Growth and Innovation: Software entropy makes it challenging for lenders to scale their operations. This leads to higher lead times in building new apps, missing out on opportunities, and losing out on market share.
3. Increased Technical Debt: Technical debt is the cost of refactoring the code in order to keep up with the ever-changing customer requirements and transformations in the lending ecosystem. It significantly raises the cost of system maintenance.
4. Security and Compliance Risks: Software entropy complicates security by raising the risk of data breaches and fraud, which may further result in non-compliance with industry standards.
But not all lenders deal with the same intensity of software entropy — Protium, for one, has carefully designed a proprietary tech architecture that reduces software entropy, creating a sustainable yet flexible ecosystem that makes launching and shelving loan products a breeze.
How Does Protium’s Proprietary Tech Platform, Turiya, Deal with Software Entropy?
The inspiration behind the creation of Turiya was to build a platform that could serve as a multi-product, omnichannel LOS (loan origination system) to enable Protium to be a full-stack lender to MSMEs and consumers. Turiya is a new software and analytics development paradigm, where the amount of coding can be anywhere between 0% and 100% depending on the use case.
The platform’s primary contribution lies in its ability to create efficient and flexible engineering operations that can support multiple products, geographies, and channels. This versatility enables quick innovation and the rapid launch of new products, allowing for MSME lending through secured and unsecured loans, platform lending, and consumer lending with a short go-to-market time. For a young company, keeping the cost of innovation low is critical, and Turiya plays a crucial role in achieving this goal.
Traditional LOS systems have significant “Software Entropy,” which can lead to unexpected problems. A multi-product omnichannel platform requires an LOS that can be customized for risk, channel, and product with distinct user experiences and risk parameters. Turiya represents a step towards an anti-entropy state, enabling the platform to cater to distinct customer journeys while maintaining consistency, stability, and strength.
To put this into perspective, consider a scenario in which an enterprise named ABC Ltd. applies for a business loan of INR 1 crore, while an individual named “N” is seeking a personal loan of INR 10 lakh. Both customers have unique journeys based on their loan types, repayment timelines, and loan terms, which can complicate a software system. Additionally, if both customers come from different tier cities, the level of product customization required for non-metro customers can raise the complexity of the system’s configuration. However, Turiya has been designed to handle differentiated journeys while maintaining stability and consistency.
As ideas evolve and new features get added to a tech-based lending platform, it is bound to become more complex and eventually reach a stage of software entropy where running the current system becomes impracticable. However, lenders can curtail the growth of software entropy by optimizing their code and carefully designing their systems, as Protium has.