# How machine learning can improve pricing performance
Author:  Pal Sinha, Barnali 
Author URL: https://financedigest.com/author/pal-sinha-barnali
Published: 2019-01-29
Category: TECHNOLOGY
Category URL: https://financedigest.com/category/technology
Meta Title: Revolutionising Payment Pricing Strategies with AI
Meta Description: Discover how AI capabilities like machine learning can revolutionise payment providers' pricing strategies for complex products with insights from
URL: https://financedigest.com/machine-learning-can-improve-pricing-performancehtml

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**_Walter Rizzi_**, _Partner at_ [_McKinsey Marketing & Sales_](http://www.mckinsey.com/) _examines how adopting a variety of artificial intelligence capabilities, such as  machine learning or deep learning gives payment providers significant power to reshape their long-standing pricing strategies._

Obtaining fair compensation for complex payment products, such as corporate cards, merchant acquisitions, and treasury-management services, has long been a major challenge. This is primarily because these products tend to be intricate, offered in myriad forms, and implemented across diverse markets. Throughout the payment industry, these problems are further complicated by ever-changing payment methods and platforms created by the rapid evolution of payment technologies. And now, expectations of rising [interest rates](https://www.financedigest.com/london-stocks-slip-ahead-of-key-interest-rate-decisions.html "London stocks slip ahead of key interest rate decisions") are compounding the situation, increasing uncertainty in product-pricing performance for both the short and long terms.

However, there is good news on the [technology front](https://www.financedigest.com/distilled-advancements-on-the-technological-front-to-drive-the-fruit-infused-water-market.html "Distilled Advancements On The Technological Front To Drive The Fruit Infused Water Market"). Just as [technological advances](https://www.financedigest.com/cardiac-valvulotome-market-growth-latest-trends-top-players-competition-technological-advancements-outlook-and-forecast-2028-2.html "Cardiac Valvulotome Market Growth, Latest Trends, Top Players, Competition, Technological Advancements, Outlook and Forecast 2028") are reshaping the payment landscape, they are delivering powerful new analytical capabilities that have the potential to transform the way banks and other payment providers price products and services.

**Mining diverse data sets for deeper insight**

![Walter Rizzi](https://prod.superblogcdn.com/site_cuid_cm5qst7v3003gwirgwqtxn8i8/images/walter-450x600-1736839185626-compressed.jpg)

Walter Rizzi

The complex nature of financial services presents substantial hurdles to those charged with pricing strategically. Merchant acquisition, corporate cards, and treasury services, for example, often include hundreds of products, each with their own distinct fees. Service contracts also differ, and they might begin and end at different times. Moreover, prices tend to be set within the context of the respective client relationship, and transparency within the industry and individual institutions is frequently rare or non-existent.

In light of such complexities, most payment providers struggle to devise fair and effective [price strategies](https://www.financedigest.com/global-compressor-controllers-market-outlook-2021-pricing-strategy-industry-latest-news-research-report-analysis-and-share-by-forecast-2028.html "Global Compressor Controllers Market Outlook 2021, Pricing Strategy, Industry Latest News, Research Report Analysis And Share By Forecast 2028") systematically. For instance, a recent McKinsey study of treasury-management [services in North America](https://www.financedigest.com/industrial-cyber-security-solutions-and-services-strong-increase-in-user-base-pans-out-for-north-america-to-lead-market.html "Industrial Cyber Security Solutions and Services – Strong Increase in User Base Pans Out for North America to Lead Market") suggests that, over the long term, repricing services leads to value destruction about as frequently as it does to value creation. In the study, price increases resulted in revenue declines a [year later](https://www.financedigest.com/three-years-later-gdpr-is-all-talk-and-no-action.html "Three Years Later: GDPR is All Talk and No Action") at more than half of the subject institutions, suggesting the outcome of pricing adjustments is highly unpredictable.

New solutions to cope with pricing complexity are emerging. Developments in computational technology, data engineering, and [digitization of general processes can now transform how banks](https://www.financedigest.com/can-ai-supercharge-your-banks-digital-transformation-strategy.html "Can AI supercharge your bank’s digital transformation strategy?") and other payment providers create and implement pricing structures. Rapidly declining costs in high-performance computing and data storage, for example, are enabling them to use larger and more diverse data sets to build more sophisticated analytical [pricing models](https://www.financedigest.com/polypropylene-fibre-market-witness-a-spike-in-growth-pace-recent-improvements-in-pricing-models-fmi.html "Polypropylene Fibre Market Witness a Spike in Growth Pace Recent Improvements in Pricing Models: FMI"). Unsurprisingly, several [industry leaders are already capitalizing on the benefits of these developments](https://www.financedigest.com/bev-automotive-oil-filter-market-recent-industry-developments-and-growth-strategies-adopted-by-players.html "BEV Automotive Oil Filter Market: Recent Industry Developments and Growth Strategies Adopted by Players").

An especially useful new tool has been SparkBeyond. This application can automate feature engineering by creating a wide range of variable transformations. It is highly efficient in identifying the most effective machine-learning algorithms, such as random forest and XGBoost. The application also enables users to export selected algorithms and features for out-of-sample testing and other modelling needs in an external environment.

Banks that adopted advanced analytics early on have been building massive data sets that integrate customer and prospect details drawn from diverse internal and external data sources. The resulting content-rich data sets are yielding deeper customer and [market insights](https://www.financedigest.com/marine-big-data-market-to-expand-at-cagr-of-21-5-during-forecast-period-tmr-insights.html "Marine Big Data Market to Expand at CAGR of 21.5% During Forecast Period – TMR Insights") that are unobtainable using traditional data. For instance, government-published econometric [data can yield information on economic](https://www.financedigest.com/european-bourses-steady-as-focus-remains-on-key-economic-data.html "European bourses steady as focus remains on key economic data") well-being and thereby better guide a bank’s budgeting process. And adding commercial and benchmark [data can help banks more accurately determine their current business share](https://www.financedigest.com/asia-shares-edge-higher-wary-of-us-bank-data.html "Asia shares edge higher, wary of US bank data") in large corporate relationships.

To obtain richer and more actionable insight at a granular level, some institutions are adopting a variety of advanced technological capabilities, including [machine learning](https://www.financedigest.com/machine-learning-in-artificial-intelligence.html "Machine learning in artificial intelligence"), deep learning, and artificial intelligence more generally. [Artificial intelligence](https://www.financedigest.com/how-to-unlock-greater-value-from-artificial-intelligence.html "How to unlock greater value from artificial intelligence") uses algorithms that range from unsupervised (such as clustering and principal-component analysis) to supervised (such as random forest and neural networks) to reinforcement learning.

Some [payment](https://www.financedigest.com/why-anti-spoofing-fingerprint-technology-is-essential-for-the-continued-growth-of-digital-payments.html "Why anti-spoofing fingerprint technology is essential for the continued growth of digital payments") leaders are also venturing into interactive digital pricing by either subscribing to third-party services or building their own digital pricing tools. Using new data sources, technologies, and modelling techniques, these early adopters are providing front-end [staff with in-depth views of customers](https://www.financedigest.com/mcdonalds-makes-masks-mandatory-for-all-customers-staff.html "McDonald’s makes masks mandatory for all customers, staff") and prospects, including such information as their product-acceptance probabilities, price sensitivities, propensities to churn, and lifetime values. These new insights allow managers to identify micromarket segments and thus [target pricing](https://www.financedigest.com/hsbc-ups-price-targets-on-greek-banks-with-eurobank-piraeus-top-picks.html "HSBC ups price targets on Greek banks, with Eurobank, Piraeus top picks") more narrowly—down to the individual customer level, when data permits. Closely attuning pricing to customer and prospect needs maximizes price performance while minimising customer attrition and volume loss.

**Developing a holistic, multistep approach**

Although new tools and capabilities bring opportunities for payment providers to [enhance their pricing performance](https://www.financedigest.com/three-fundamental-tips-to-enhance-your-investment-portfolio-performance.html "Three fundamental tips to enhance your investment portfolio performance") significantly, real success will only come through systematic and comprehensive execution. Achieving maximum effectiveness [requires an enterprise-wide pricing transformation](https://www.financedigest.com/how-to-fulfil-the-digital-transformation-requirement-in-banking.html "How to fulfil the Digital Transformation Requirement in Banking").

One way to initiate a pricing [transformation is to develop incremental price changes with selected markets](https://www.financedigest.com/signal-transformer-market-one-the-most-booming-industry-in-upcoming-years-due-to-global-demand-in-industry-by-2027.html "Signal Transformer Market| One the Most Booming Industry in Upcoming Years Due to Global Demand in Industry by 2027") or segments using pilot programs that can be quickly learned and iterated before rolled out as a broad pricing program. Once the proof of concept is established, the full program can then be deployed through a three-step [approach that includes optional use of early revenue gains to fund](https://www.financedigest.com/private-equity-funds-approach-italys-serie-a-to-explore-media-rights-deal-sources.html "Private equity funds approach Italy’s Serie A to explore media rights deal -sources") subsequent steps:

1. For early transformation success, perform the following initiatives (in addition to other appropriate measures):
   - Use advanced-analytics technologies, such as machine learning, to establish pricing benchmarks at a granular level. For example, [banks can drill down from traditional](https://www.financedigest.com/fiat-republic-the-specialist-baas-platform-that-bridges-the-gap-between-web3-and-traditional-banks-announces-it-has-become-an-electronic-money-institution-emi-in-the-uk.html "Fiat Republic, the specialist BaaS platform that bridges the gap between web3 and traditional banks, announces it has become an Electronic Money Institution (EMI) in the UK.") segmentation levels (such as geography, industry, and deal size) to postal code or business unit and thus more quickly identify fee leakage at the level of individual customer pricing.
   - In parallel with establishing granular benchmarks, [develop interactive tools that enable field representatives to recognize pricing opportunities in client portfolios rapidly and simultaneously to leverage other opportunities to expand share of business](https://www.financedigest.com/dan-hodgson-joins-verasity-as-director-of-business-development.html "Dan Hodgson joins Verasity as Director of Business Development") with the customer.
   - Initiate price discussions throughout the organisation and redesign the pricing process so it can be implemented in carefully timed waves. A key component of this is building a disciplined exception-management process to strengthen pricing governance and to identify and remedy flaws in current processes and policies.

Initial programmes incorporating these three elements can yield revenue [lifts of about 15 percent within six to nine months yet incur only minimal client- and volume-attrition rates](https://www.financedigest.com/britain-lifts-rates-by-most-since-1995-latest-to-deliver-aggressive-hikes.html "Britain lifts rates by most since 1995, latest to deliver aggressive hikes"). And those who implement rigorous service-repricing programmes can apply early revenue gains to funding the overall journey.

2. Begin developing new organization-wide pricing skills and capabilities. While this often becomes a longer-term journey, it is one that needs to be initiated and proactively managed from an early stage. This step commonly includes the following actions:
   - improving and expanding skill sets throughout the pricing organization
   - significantly enhancing current [pricing data](https://www.financedigest.com/german-bond-yields-give-up-rise-after-u-s-price-data.html "German bond yields give up rise after U.S. price data") sets
   - building strong pricing-analytics capabilities
   - developing enterprise-grade tools to assist in such key areas as new-deal pricing, contract-renewal pricing, and ongoing revenue-portfolio management

Common related [investments include](https://www.financedigest.com/true-operational-resilience-must-include-investing-in-esg.html "True operational resilience must include investing in ESG") acquiring new technology capabilities, such as voice recognition and automation, to reduce manual processing, human-error rates, and technical leakage.

3. Equipped with powerful analytical tools, immense data sets, and newfound skills, continually enhance pricing strategies through ongoing monitoring and scaling of new pricing constructs.
   - Together, these actions are helping many institutions improve the ways they address current and prospective client needs in diverse [markets and segments](https://www.financedigest.com/chondroitin-market-overview-analysis-by-top-players-product-segments-market-size-and-leading-key-players-2022-2029.html "Chondroitin Market Overview & Analysis by Top Players, Product Segments, Market Size and Leading Key Players 2022- 2029"). Pricing tactics, for instance, can be finely tuned to reflect evolving customer and prospect needs by drawing on a variety of pricing approaches, including bundled pricing, subscription pricing for [small businesses](https://www.financedigest.com/foolproof-local-marketing-strategies-for-small-businesses.html "Foolproof Local Marketing Strategies for Small Businesses"), and unbundled granular pricing for corporate clients. Consequently, deeper understanding of ever-changing marketplace needs can provide a clear [competitive advantage](https://www.financedigest.com/ai-holds-the-key-for-both-competitive-advantage-and-risk-mitigation-in-2022.html "AI holds the key for both competitive advantage and risk mitigation in 2022").

**Leaping the hurdles of price transformation**

Adopting machine learning and advanced analytics generally gives payment providers significant [power to reshape their long-standing pricing](https://www.financedigest.com/eex-markets-to-remain-open-as-power-prices-soar-statement.html "EEX markets to remain open as power prices soar – statement") strategies. Yet transformation can also present unique challenges.

Advanced analytics presents a variety of sophisticated tools, but their effectiveness depends largely on how the insights are actually derived and subsequently used. For example, traditional approaches to [setting pricing](https://www.financedigest.com/oil-prices-set-for-weekly-fall-on-stockpile-releases.html "Oil prices set for weekly fall on stockpile releases") targets, such as scoring or ranking customers on price sensitivity, are less actionable than is employing a mathematical model that links offer-acceptance probability to historically accepted offer rates. Pricing models based solely on statistical performance can deliver suboptimal guidance; maximum performance, by contrast, also requires the application of sound business principles and disciplined practices.

Aside from aspects of data and analytics modelling, another common obstacle to achieving full effectiveness in the use of advanced analytics is a siloed organizational structure. [Organizational silos often lead](https://www.financedigest.com/how-to-lead-organizational-change.html "How to Lead Organizational Change") to departmental misalignments—for instance, among finance, marketing, and sales—when making strategic pricing decisions. In these situations, the best practice is usually to ensure from the outset that all stakeholders have integral roles in planning and implementing the pricing transformation and participate regularly in transformation-planning and progress-review meetings.

To generate positive results, even the best of strategies requires seamless execution. Real or perceived flaws during the rollout of a new pricing tactic can quickly incite rejection among relationship mangers—a problem that successful institutions are overcoming by showcasing success stories and prominently recognising champions of change within their organisations. Of course, it is also essential to realign performance incentives with new pricing approaches and goals promptly. Engaging relationship [managers in codeveloping pricing strategies is a highly effective way to generate positive change](https://www.financedigest.com/uk-at-forefront-of-fx-management-change.html "UK at Forefront of FX Management Change") attitudes. To instil manager confidence in a new pricing approach, one [European bank devised algorithms that can instantly](https://www.financedigest.com/more-banks-join-european-instant-payments-pilot-from-end-2023.html "More banks join European instant payments pilot from end 2023") show managers the bank’s pricing structure on comparable deals.

**Tomorrow’s industry leaders**

Advanced-analytics technologies are beginning to alter rapidly how businesses operate around the globe. Given the [central role of banks](https://www.financedigest.com/climate-change-fight-a-core-duty-for-central-banks-ecbs-villeroy.html "Climate change fight a ‘core duty’ for central banks – ECB’s Villeroy") and other payment-industry participants, these players are fast becoming subject to those same forces. To remain competitive, payment providers will therefore [need to embrace the technologies](https://www.financedigest.com/cfos-need-to-embrace-todays-technology-for-tomorrows-success.html "CFOs need to embrace today’s technology for tomorrow’s success ") on a timely basis. Many in the [payment industry](https://www.financedigest.com/end-of-year-overview-of-the-payments-industry.html "End of year overview of the payments industry") might be hesitant to change their long-standing approaches to pricing, but those willing to adopt a comprehensive pricing transformation built on deep market insights will clearly be among tomorrow’s industry leaders.

_\*The author would like to thank Maria Wang and Kuba Zielinskifrom McKinsey & Company for their contributions to this article_


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