Category: revenue accounting

The Payment Jungle

The Payment Jungle

Current situation

Even in normal times, the airline business is anything but easy. Competition, fuel costs, regulations and growing environmental awareness challenge the industry and make airline operations a demanding task. After the pandemic subsided, a certain recovery was felt, but the current rather difficult economic environment, the war in Ukraine and high energy costs bring new risks and challenges.

Not only the operational business faces challenges in this difficult environment, but also the back office of an airline. This is reason enough to take a closer look at the problems and developments in the area of payment handling for airlines. Specifically, we will take a closer look at service providers, markets and regulation.

Service Providers

Payment processing, credit card acquiring and controlling were carried out by the airlines themselves until the early 2000s. Growing regulation, new security standards in payment processing such as PCI and an increasing number of international and regional means of payment have led to more and more processes being outsourced to specialised and appropriately-certified service providers. In good economic times, the airlines were very attractive customers for these providers. This changed with the groundings of many airlines in the past decade, including some large and well-known carriers. For credit card acquirers in particular, aviation became a risky business as they were often the ones left out of pocket. Airline ticket sales are paid immediately but usually not used until weeks (or even months) after purchase. The total value of all tickets sold but not yet flown constitute the “unflown revenue”, and this quantifies the risk for the acquirer. In the event of a grounding, the acquirer is left with the ticket holder’s claims for reimbursement. More and more, airlines had to fulfil challenging conditions in order to get access to acquiring contracts at all, and the conclusion of such contracts is often linked to painful conditions for the airlines. These can mean providing security deposits such as rolling reserves (payments withheld by the acquirers), payment only when flown or the division of the business among several acquirers (risk splitting). For most airlines, credit cards are still the most widely-used means of payment, so these security deposits can have quite a painful impact on liquidity.

The number of external service and payment providers is also constantly increasing, which leads to higher processing costs as well. Payment service providers (PSPs), payment orchestrators, reconciliation services, fraud screeners and alternative payment methods charge fees for their services and thus make ticket sales more expensive.

Markets

Carriers operating worldwide usually have a very international clientele to which one must also adapt in the payment area. This means that the most relevant means of payment must be offered for each market. In addition, the credit card business can also be very different between individual markets due to legal regulations or regional standards. This not only generates more provider fees, but also increases the complexity of the processes. Airlines used to be able to map this complexity to their own system platforms, but today, this is no longer possible for the reasons already described. That is why PSPs were first forced to incorporate airline-specific features as “bespoke services”. Later, so-called “payment orchestrators” came onto the market, who inserted themselves as an additional application layer between the airlines and the PSPs, and from then on took over the control and routing of the payment processes.

Another topic is the change of customer needs. Payment should be secure, fast and simple all at the same time. It is possible to meet all requirements in this area of conflict, however the design of corresponding solutions is associated with great effort. Internationality and growing customer requirements create even more complexity, and this makes the development and operation of booking systems more expensive and slower.

Regulation

Dealing with customer requirements and external service providers is complex in itself, but national regulators, the EU and the card schemes add to this with their regulations. Especially in the areas of security and costs, merchants (including airlines themselves) and service providers are confronted with a growing number of regulations and restrictions.

With the Payment Services Directive (PSD) 2 regulation, the EU issues regulations on fees and security. Credit card fees, for example, may not exceed a certain amount (which for once is in favour of the airlines), but so-called “surcharging” (charging the payment fees to the end customer) is severely restricted. This is a painful cut, especially for the airlines. Furthermore, a two-factor authentication process is mandated for online payments.

The credit card schemes (Visa, Mastercard, American Express etc.) have reacted to this regulation with the security standard “3-D Secure 2”. Since the policy limits revenues by capping acquiring fees, the schemes are reacting with an almost unmanageable number of new fees.

With PCI DSS (Payment Card Industry Data Security Standards), the card schemes want to prevent the theft of credit card data. Since the complexity of the corresponding requirements makes it almost impossible for merchants and service providers to implement them on their own, a market for specialised service providers for tokenising credit card data has also established itself here. Of course, these providers do not work for free either, which leads to a further increase in the cost of payment processes.

Change as an opportunity

Many of the topics described above are given – especially when it comes to service providers and sales markets – and simply have to be implemented. Here, it is advisable to work with a specialised payment orchestration service.

When it comes to regulations, on the other hand, there are a number of exceptions and intelligent solutions with which negative effects can be neutralised. For example, there are simplified checkout procedures for registered customers, payment surcharges are still allowed under certain conditions, and the regulations concerning PCI DSS can be adhered to with little expense through the integration of tokenisation services. 

The facts described above could give the impression that service providers, customers and regulators have conspired together to make life difficult for the airlines. However, if you take a closer look at the new regulations and restrictions, you will discover advantages for all market participants. All the policies and regulations were not invented to make life difficult for the industry. By consistently adhering to the guidelines, companies can significantly reduce the risks of data theft, fraud and the resulting chargebacks. 

At its core, payment process design is about getting to grips with three factors: cost, risk and conversion. Despite all the issues described above, a well-balanced payment landscape can be customer-friendly, secure and comparatively cost effective. The basis for this is a good concept and, as so often in our industry, the choice of the right partners.

At Travel in Motion, we can help you finding your way in the jungle of customer needs, regulations, regional characteristics, cost pressures, scarce resources and security requirements. Both airlines and vendors can benefit from our expertise and experience.

This post has been published in collaboration with Terrapinn.

(Urs Kipfer, 8. June 2023)

 

 

June 8, 2023 Boris PadovanAggregation, AI, Airline Retailing, Airlines, Artificial Intelligence, Customer, Customer Service, Digital Transformation, forecast, forecasting, Homepage, NDC, NDC, ONE Order, OOMS, PSS, revenue, revenue accounting, Segmentation, Uncategorized

Untapped potentials of AI in the Airline Industry?

Untapped potentials of AI in the Airline Industry?

Inspired by a follow-up on my customer insights blog last December and an AI assignment for my Executive MBA studies, I wanted to share some learnings from that work. The aim was to look for an AI use case that can be implemented for an airline venturing onto the new distribution transformation path – something that many airlines are just starting to consider. There is a wealth of data to be tapped into, but what exactly might some of the possibilities be for using this data in a meaningful way? What does the new world allow an airline to do that it didn’t before? Will it deliver as promised, and how can this be measured?

  • While there is much talk about how AI can revolutionise pricing and revenue management, are there other potential uses of the data that can now give insights that an airline didn’t have before?
  • Much has been said about the ability to make more targeted offers and thereby increasing revenue per customer and flight, might there be other untapped golden nuggets to be derived from the offer data?

The airline industry is highly competitive, where customer satisfaction and operational efficiency are crucial to success. As airlines have access to vast amounts of data, it is no surprise that many are turning to artificial intelligence to help them gain a competitive advantage.

One of the most significant benefits of AI for the airline industry is its potential to improve customer experiences. Especially when looking at finding patterns and opportunities that might be undetected today, AI has the potential to process a huge amount of data with an efficiency that only a few solutions already do. Including more and different data sources than what is traditionally done can provide customer insights from a different angle. By analysing customer data, airlines can tailor their offers and services to meet their customers’ needs and preferences better.

A look at some use cases

Traditionally, airlines have pushed out the availability (or made it available in a “pull” fashion) and the prices, and only got to know about the customers when they purchased a flight. However, there is considerable knowledge about how customers behave before they buy – knowledge which airlines to date have never had access to. But my interest was piqued when thinking about what offers customers didn’t buy, since this says as much about their needs as what they finally purchased. Having a complete picture of who did not buy what can lead to new insight into what appeals to whom – in a different way than previously possible.

For example, AI can provide personalised recommendations for flights, hotels, and other travel-related services. AI can analyse a customer’s past purchases, preferences, and other data to deliver tailored recommendations more likely to meet their needs.

AI can also provide real-time information and support to customers during their journey. Chatbots, for example, can provide instant customer support, answering their questions and providing guidance throughout their journey. This can help to reduce customer frustration and improve their overall experience.

Airlines can increase operational efficiency by optimising their processes and reducing costs by using AI. For example, to optimise flight schedules, crew assignments, and other operational tasks.

AI can also improve maintenance operations, reducing downtime and increasing aircraft availability. By analysing data from sensors and other sources, AI can predict maintenance issues before they occur, allowing airlines to address them before they cause disruptions proactively.

Finally, AI can help airlines to boost their revenue by optimising pricing and increasing ancillary sales. AI can analyse customer data and market trends to predict demand and optimise pricing accordingly.

AI can also be used to increase ancillary sales by providing tailored recommendations for ancillary services, such as seat upgrades, baggage allowances, and lounge access. By tailoring these offers to each customer’s preferences and needs, airlines can increase their likelihood of purchasing.

The challenges

While the potential benefits of AI in the airline industry are significant, several challenges come with its implementation. These include the cost of implementation, the complexity of the technology, and the need for skilled personnel to manage and operate the systems.

To overcome these challenges, airlines need to take a phased approach to AI implementation, starting with small proof-of-concept projects to demonstrate the potential value of the technology.

Another challenge is data privacy and compliance. Airlines need to ensure that their use of AI complies with all relevant data privacy regulations and that customer data is adequately secured. This requires a strong governance framework and robust security measures to protect sensitive data.

Airlines need to ensure they have the right personnel to manage and operate AI systems. This requires a mix of technical skills, such as data engineering and data science, and soft skills, such as communication and stakeholder management. Airlines should invest in training and development programs to build these skills in-house and ensure their personnel are up-to-date with the latest AI technologies and best practices.

Potential – but only by doing it right

In conclusion, AI has enormous potential in the airline industry, providing airlines with tools to increase revenue, improve efficiency, and provide customers with personalised offers that cater to their needs. However, implementing AI solutions has challenges, and airlines must be aware of them and take steps to mitigate them. It’s essential to have a dedicated team with the necessary skills and expertise to manage the project and communicate the process and results effectively. With AI, the airline industry can move towards a more sustainable customer-centric business model, identifying new opportunities that emerge from the direct distribution model.

AI has the potential to transform the airline industry, and airlines that embrace it will have a competitive advantage over those that don’t. While the airline industry is still in its infancy in using AI, it’s clear that it is a technology that will play a significant role in shaping the airline industry’s future. It’s exciting to see what the future holds, and we can’t wait to see how AI will continue to transform the airline industry.

 

This post has been published in collaboration with Terrapinn.

(Mona Kristensen, 5. May 2023)

 

 

May 4, 2023 Boris PadovanAggregation, AI, Airline Retailing, Airlines, Artificial Intelligence, Customer, Customer Service, Digital Transformation, forecast, forecasting, Homepage, NDC, NDC, ONE Order, OOMS, PSS, revenue, revenue accounting, Segmentation, Uncategorized

What is the Future of Revenue Management?

What is the Future of Revenue Management?

Many years ago, I used to work as a TPF mainframe software developer, building applications for one of the leading global PSS providers at that time. Over the years I have had the privilege of working on some ground-breaking projects. When I first started in the mid-nineties, we were putting in place API layers for web services to power some of the first airline e-commerce platforms. In the early noughties, I was involved in the integration of one of the first origin and destination (O&D)-based revenue management systems, promising to deliver incremental revenue gains of 1-2% for airlines. This was, and still is, big money for any carrier.

Around 15 years after this project, in my role as solution architect I was responsible for integrating another airline with this same RM application. Not surprisingly, considering the pace at which the airline industry evolves, this integration was more or less identical to the initial implementation, although with a different PSS provider. Every night, a dump of booking, inventory and schedule data is pushed to the RM application which ingests this data along with numerous other files containing flown ticket data and who-knows-what else and begins running its nightly optimisation processes. Around eight hours later, new steering controls, bid prices and so on are pushed back into the reservation system and the process is complete for another day. Outside of this, ad-hoc changes may be triggered for a flight, either manually or automatically based on certain events. Essentially though, for almost all of an airline’s network, each flight goes through this process once a day.

Optimising the price of every seat on every O&D of an airline’s network is a very complex process, and back in the eighties when the first airline RM systems were implemented, this daily cycle was all that was technically possible. The enormous computing power needed was both expensive and scarce, and only available to airlines with deep pockets (we carry more computing power these days in our pockets!). Pretty much every airline RM system still works this way today: batch data is downloaded from booking systems (i.e., the PSS), optimisation processes run, and the output is uploaded into the airline’s pricing and inventory control systems (usually PSS). However, the (technology) world has moved on since then: computing power has become much more affordable, and the growth of cloud technology has made this available on demand and instantly scalable. At the same time, the volume of airline shopping transactions has increased exponentially in the last decade or two. Airline products have also become diversified and more complicated, with the advent of de-bundling components of the air ticket (seats, bags etc.). Markets have become more competitive, with demand exceeding supply in most cases. Considering all these factors, one must consider whether the RM approaches still used today are effective.

In one regard, the answer to this question is clearly yes: the RM methodologies themselves. Many clever people have dedicated their lives to perfecting the algorithms used to forecast demand based on all manner of data sources, statistical methods, and highly complex algorithms. These continue to adapt to the new ways in which airlines price and sell their products, although this is still predominantly limited to the air fare only. However, it could be argued that the manner in which these powerful algorithms and calculations are applied is somewhat outdated, considering the technological capabilities available today. Let’s consider an airline carrying 50 million passengers a year in a typical hub-and-spoke network. Using some schoolboy mathematics, this might give an average of around one booking created every second, give or take a few. For reference, Amazon gets something like 18 orders per second[1]. Assuming the airline is using O&D-based revenue management, this potentially means that the demand on a significant portion of the network has changed – and therefore of course the price. But these incredibly dynamic changes are not ingested by the forecast algorithms until the RM machines get their batch files to churn through and deliver new demand forecasts hours later. Of course, airline pricing is much more complicated than most products sold through online retailing, where prices are (relatively) static, but does that not mean that it is even more important that airlines stay on top of pricing and adapt in real time?

What is holding us back?

So why don’t airlines do this non-stop, 24x7x365? Well, the answer is the same as for many questions in the airline world: silos. Way back before many of you were born, there was just PSS – schedules, inventory, PNRs and tickets (eek!). The RM systems were bolted on using big interface files. But today’s computing world looks different – we have real-time integrations, artificial intelligence and machine learning engines that never sleep and enough computing power to run the numbers over and over again and get the results instantly. With the advent of offer and order management systems, we are also a goldmine of offer, pricing and conversion data that is just waiting to be tapped into. Sending a dump of booking data can tell you a lot about what was sold, but nothing about what was offered or who asked. Unlocking the value in this data and understanding what it tells you is the key airline retailing – offering the right products in the right channel at the right price.

Traditionally this data has been difficult to interpret – EDIFACT messages, tickets, fare base codes, RFISCs, RBDs all in cryptic formats. NDC and ONE Order bring some standardisation to these key sources of data, but we need to work harder to break down the silos and truly start working with offers and orders (instead of just bolting them onto our legacy systems).

Indeed, this issue is not only to be found within the RM domain. Many of the initiatives in the industry at present are reliant on removing these silos in the end-to-end chain of distribution. Instead of a set of standard integration points based on interfaces from the 1990s, a dynamic and real-time exchange of key data is needed to be able to make offers that are truly relevant, targeted, and likely to lead to conversion. The flow does not simply end with the completion of a booking. Real-time delivery of sales into financial accounting can simplify settlement and revenue recognition. Real-time operational data can drive automated, proactive service recovery in case of disruptions – a task today that often requires extensive manual intervention. For far too long, as an industry, we have looked at these barriers individually – and indeed, in the execution this is the way forward. However, we must also to step back and look at the flow in its entirety – offers, orders, service delivery, payments, financial accounting, RM, customer management and so on. This transformational journey will involve many steps along the way, but without seeing the big picture, the course cannot be plotted.

At Travel in Motion, we are passionate about driving this change forward – let us share our expertise with you and help guide you on your transformation to a world of offers, orders and airline retailing and unlocking the value in that vast amount of data.

[1] https://landingcube.com/amazon-statistics/

This post has been published in collaboration with Terrapinn.

(Nick Stott, 5. April 2023)

 

 

April 2, 2023 Boris PadovanAggregation, Airline Retailing, Airlines, Customer, Customer Service, Digital Transformation, forecast, forecasting, Homepage, NDC, NDC, ONE Order, OOMS, PSS, revenue, revenue accounting, Segmentation, Uncategorized