Senin, 05 November 2018

The A to D (asset to data) of new financing models

Data gets everywhere. Every time we send a message, search for something online, or interact with an app, we’re generating masses of information that businesses can make good use of to better tailor services and offers for us. It’s real-time, it’s personal, and it’s now expected. While retailers were the first to join the dots to capitalise on this treasure trove of data, digitisation has left nearly no industry untouched. As entire sector ecosystems evolve, business models are challenged and assumed economics and value chains are shaken. Partners and technology providers must rally around to support and enable, ensuring longstanding businesses are able to remain relevant and competitive. 

The world of asset finance doesn’t often see the light of day, but we’re seeing radical shifts in requirements here. Let’s take the auto sector as an example - big ticket headline trends such as Car-as-a-Service, Connected and Electric Vehicles reflect the changing way in which transport is delivered, managed, used, and therefore – paid for. 

Although we’re all used to dialling up a ZipCar for an emergency trip to the tip, or listing our own vehicle on a car sharing network such as hiyacar, this trend exposes automotive leasing businesses to a whole new layer of complexity. Conventional leasing models, whereby contract prices are determined by fixed parameters – i.e. mileage requirements, car choice, duration, post contract vehicle valuations – will no longer be applicable in a world where drivers become users of lots of vehicles rather than owners of their own.

Pricing electric vehicles

The plot thickens when we think about the trend towards electric vehicle ownership. This will have a major impact on traditional models for residual vehicle valuation. Due to a mix of governments’ evolving subsidy strategies, shifting demand patterns, and new technology developments, electric vehicle lease contracts will have to be priced differently to traditional vehicles. 

For example, conventional depreciation models used to calculate sales cost for combustion engine vehicles after lease expiry will not apply to electric vehicles as there are a number of unique additional considerations to bear in mind. This includes everything from wear and tear of the electric motor (which is very different to an internal combustion engine), to the amount of software updates made to an ECU. The latter will completely reverse traditional ‘depreciation theory’, and mess with assumed economies as software increases vehicle intelligence and performance. A standard car is valued as a whole ‘piece of metal’, unlike an EV which can be valued in components – the battery can make up 50% of the EV’s value.

This becomes even more complicated when we consider the connectivity of cars, with manufacturers and software providers beaming ‘over the air’ updates into vehicles, imbuing them with intelligence and functionality that will increase their value over time – contrary to what might be expected for a leased car.

This data surge brings a challenge, but also a considerable opportunity for asset finance firms that embrace the opportunity to do more with the information that is flowing through their systems. Think real-time, dynamic quotes, the ability to remotely monitor assets to ensure they are not being mis-used or breaking agreements, leasing contracts based on insight from past usership rather than factory-set guesstimates, and stronger customer relationships. Many asset lenders are playing catch up against retailers, hospitality providers, airlines and utility providers, but these businesses can’t shy away from the role of data in delivering the user experience we’ve all come to expect.   

Daniel Layne, CTO and Founder of Quotevine


November 05, 2018 at 05:30PM
Daniel Layne

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