人工智能驱动的定价：商业模式的转变

AI-driven Pricing: A Paradigm Shift for Business Benefits of Using AI Pricing Strategies AI-driven Pricing in Financial Institutions Krungsri Research view References Unlessexplicitlystatedotherwise,thispublicationandallmaterialthereinisunder the copyright ofKrungsriResearch. As such, the reuse, reproduction, oralteration of this text or any part thereof is absolutely prohibited without priorwrittenconsent.Thisreportdrawsonawiderangeofwell-establishedandtrustworthysources,butKrungsriResearchcanmakenoguaranteeoftheabsolute veracity of the material cited. Moreover,KrungsriResearch will not beheld responsible for any losses that may occur either directly or indirectly fromany use towhich this reportorthe datacontained therein maybe put.Theinformation,opinions,andjudgementsexpressedinthisreportarethoseofKrungsriResearch, but this publication does not necessarily reflect the opinionsof Bank ofAyudhyaPublic Company Limited or of any other companies withinthe same commercial group. This report is an accurate reflection of the thinkingand opinions ofKrungsriResearch as of the day of publication, but we reservethe right to change those opinions without prior notice. For research subscription, contactkrungsri.research@krungsri.com Introduction The saying ‘data is the new currency’ has become something of a commonplace in recent years, but thisreflects the core observation that within the modern business environment, data’s utility places it on a parwith currency in terms of its ability to facilitate decision-making, spur innovation and build competitiveadvantage. Companies across the economy are thus intensifying their efforts to source and utilize data,and in turn, this is driving the development of innovative data analytics strategies as companies look topreserve and extend their competitive edge. Artificial intelligence, or AI, is one area that is attractingconsiderable interest, and of particular note is the ability of AI systems to determine appropriate pricinglevels for goods and services. By integrating the analysis of historical data and current conditions, AIsystems can accurately and rapidly evaluate supply and demand, likely consumer behavior, overall marketconditions, and the factors likely to affect these. This then allows companies to set prices at their optimumlevel, achieve related business goals, and raise their overall levels of efficiency and productivity. Nathanon Ratanathamwat Dr. Pimnara Hirankasi Head of Research Division and Chief Economistpimnara.hirankasi@krungsri.com+662 296 6457 Senior Analystnathanon.ratanathamwat@krungsri.com+662 296 6389 Benefits of Using AI Pricing Strategies Artificial intelligence (AI) is an advanced technology that allows computer systems to learn fromhuge stores of data and to use this understanding to improve its own abilities in given areas. AI systemsare generally able to produce highly accurate outputs, and in some ways, these are analogous to humancognition in their ability to assimilate, analyze and exploit information from different sources.1/Given thepromise held out by AI, many companies are now using this technology to power their pricing strategies.This involves tasking AI systems with processing extensive historical datasets alongside currentinformation, such as the behavior of customers and trade partners, the extent of market competition andother relevant market factors. Additionally, it requires considering constraints due to the company'slimitations. The goal is to conduct a multidimensional analysis that integrates these diverse elements toderive actionable insights. This then allows for the generation of an optimal price given the company’sstated aims, whether that be expanding its customer base, gaining an advantage over the opposition,achieving revenue growth, or resolving issues within the company’s own supply chains. AI-driven pricing strategies are therefore emerging across the economy in areas as diverse ase-commerce, commercial air travel, hotels, and banking and insurance, especially in situations wherecompanies are selling to retail customers through the internet. Being able to simultaneously adjust pricesacross a huge range of products gives sellers the space to gain a competitive head start and to moresharply differentiate themselves from their competitors, and so when setting prices, retailers areincreasingly turning to the use of AI. Within this general field, one area that has found applications inprice-setting has been machine learning (ML),2/which allows retailers to better analyze and understandconsumer behavior, overall market conditions, and other factors affecting the business environment.However, research by Fisher et al. (2023)3/shows that analyzing historical data on only sales, prices, andproduct details results in an improvement in revenues or profits of at most 1%. In contrast, implementingdynamic price-response systems over a month-long testing period for 10,000 products resulted in a 15%increase in reven