{"id":14685,"date":"2026-04-30T02:05:43","date_gmt":"2026-04-29T23:05:43","guid":{"rendered":"https:\/\/didemkurbandanismanlik.com\/index.php\/2026\/04\/30\/cracking-the-code-how-apple-pay-google-pay-are-redefining-mobile-casino-payments-in-the-new-year\/"},"modified":"2026-04-30T02:05:43","modified_gmt":"2026-04-29T23:05:43","slug":"cracking-the-code-how-apple-pay-google-pay-are-redefining-mobile-casino-payments-in-the-new-year","status":"publish","type":"post","link":"https:\/\/didemkurbandanismanlik.com\/index.php\/2026\/04\/30\/cracking-the-code-how-apple-pay-google-pay-are-redefining-mobile-casino-payments-in-the-new-year\/","title":{"rendered":"Cracking the Code: How Apple Pay &#038; Google Pay are Redefining Mobile Casino Payments in the New Year"},"content":{"rendered":"<p>The calendar has turned, and with it a fresh wave of mobile\u2011first gamblers is flooding online casino lounges. Players no longer sit at a desktop waiting for a slow bank\u2011transfer; they swipe, tap, and are instantly seated at a virtual roulette wheel while their morning coffee brews. In this hyper\u2011connected era, the speed and security of a deposit can be the difference between catching a hot streak on a progressive slot and watching the house edge swallow the opportunity.  <\/p>\n<p>Instant, secure payments matter because every second saved translates into more spins, more hands, and ultimately, more chances to hit a jackpot. Mobile wallets such as Apple\u202fPay and Google\u202fPay have emerged as the premier \u201cdigital wallets\u201d for this purpose, offering tokenized transactions, biometric safeguards, and near\u2011zero friction. For operators, these wallets promise higher conversion rates; for players, they deliver a smoother path to the bonus round.  <\/p>\n<p>If you\u2019re hunting for an unbiased comparison of casino platforms that support these wallets, <a href=\"https:\/\/revoland.com\">https:\/\/revoland.com\/<\/a> is a solid resource that aggregates user reviews and feature lists without any hidden agenda. Revoland can help you locate a site that pairs your favorite game\u2014say a 96.5\u202f% RTP slot like <em>Starburst<\/em>\u2014with the wallet of your choice.  <\/p>\n<p>This article pulls back the curtain with a mathematical lens. We will dissect transaction\u2011time formulas, model fraud probabilities, and calculate return\u2011on\u2011investment (ROI) for both operators and players. By the end, you\u2019ll understand not just that Apple\u202fPay and Google\u202fPay are fast, but exactly how fast they are, how safe, and how they affect your bottom line in the New Year\u2019s casino battlefield.  <\/p>\n<h2>The Anatomy of a Mobile Payment Transaction<\/h2>\n<p>When a player taps \u201cDeposit $50 with Apple\u202fPay,\u201d a cascade of events unfolds in under a second. First, the device generates a one\u2011time token that replaces the actual card number. This token travels through the Apple\u202fPay Secure Element, encrypted with a device\u2011specific key, and is handed to the merchant\u2019s payment gateway.  <\/p>\n<p>On the casino side, the gateway validates the token against Apple\u2019s verification server, confirming that the token is still active and has not been revoked. Once authentication passes, the gateway forwards the request to the acquiring bank, which then settles the funds into the casino\u2019s merchant account. Finally, the casino\u2019s back\u2011office credits the player\u2019s balance, often within the same API call.  <\/p>\n<p>Google\u202fPay follows a similar path but differs in token generation. Google creates a dynamic \u201cpayment address\u201d that is linked to the user\u2019s Google Account rather than a hardware\u2011bound element. Verification happens via Google\u2019s Cloud\u2011based token service, which can respond in microseconds due to its distributed architecture.  <\/p>\n<p>These steps can be distilled into a latency equation:  <\/p>\n<p>[<br \/>\nL = T_{auth}+T_{net}+T_{proc}<br \/>\n]<\/p>\n<ul>\n<li>(T_{auth}) \u2013 time spent authenticating the token (typically 30\u201150\u202fms).  <\/li>\n<li>(T_{net}) \u2013 network transmission delay, influenced by 4G\/5G and Wi\u2011Fi quality (often 20\u201170\u202fms).  <\/li>\n<li>(T_{proc}) \u2013 processing time on the casino\u2019s server, including fraud checks and balance updates (roughly 40\u201180\u202fms).  <\/li>\n<\/ul>\n<p>Summing the components yields a total latency (L) that usually lands between 100\u202fms and 200\u202fms\u2014fast enough that the player never notices a pause.  <\/p>\n<h3>Key steps at a glance<\/h3>\n<ul>\n<li>Tap on wallet button \u2192 device creates token.  <\/li>\n<li>Token encrypted, sent to payment gateway.  <\/li>\n<li>Gateway validates token with Apple\/Google servers.  <\/li>\n<li>Acquirer settles funds, casino credits balance.  <\/li>\n<\/ul>\n<p>Understanding each component helps operators pinpoint bottlenecks, whether they lie in network routing or in server\u2011side fraud engines.  <\/p>\n<h2>Probability of Fraud in Mobile Casino Payments<\/h2>\n<p>Mobile wallets dramatically shrink the attack surface, yet they are not immune to fraud. The primary vectors include man\u2011in\u2011the\u2011middle (MitM) attacks on unsecured Wi\u2011Fi, replay attacks using captured tokens, and social engineering that coerces users into authorizing payments.  <\/p>\n<p>A simple Bayesian model can illustrate the conditional probability of fraud given an observed anomaly (A):  <\/p>\n<p>[<br \/>\nP(F|A)=\\frac{P(A|F)P(F)}{P(A)}<br \/>\n]<\/p>\n<ul>\n<li>(P(F)) \u2013 baseline fraud rate for mobile wallet deposits (estimated at 0.02\u202f%).  <\/li>\n<li>(P(A|F)) \u2013 likelihood of detecting an anomaly when fraud occurs (high, about 0.9).  <\/li>\n<li>(P(A)) \u2013 overall probability of any anomaly (e.g., unusual location, repeated small deposits).  <\/li>\n<\/ul>\n<p>Plugging typical values yields a posterior probability (P(F|A)) of roughly 0.018\u202f%, indicating that even when an alert fires, the chance of actual fraud remains low.  <\/p>\n<p>Historical data shows that card\u2011only deposits suffer a fraud rate near 0.12\u202f%, while wallet\u2011only deposits hover around 0.02\u202f%. The reduction stems from tokenization (no static PAN exposed) and biometric checks that make unauthorized use far more difficult.  <\/p>\n<h3>Fraud mitigation checklist<\/h3>\n<ul>\n<li>Enforce device\u2011binding for tokens.  <\/li>\n<li>Require biometric confirmation for every deposit over a set threshold (e.g., $200).  <\/li>\n<li>Monitor velocity patterns: more than three deposits under $20 within five minutes triggers a review.  <\/li>\n<\/ul>\n<p>By quantifying these risks, operators can allocate fraud\u2011prevention budgets more efficiently, focusing on the few high\u2011risk scenarios rather than blanket restrictions that would frustrate legitimate players.  <\/p>\n<h2>Expected Value for Players: Speed vs. Cost Trade\u2011offs<\/h2>\n<p>From a player\u2019s perspective, the expected value (EV) of a deposit incorporates not only the potential winnings but also the hidden costs of time and fees. The basic formula is:  <\/p>\n<p>[<br \/>\nEV = (W \\times P_{win}) &#8211; C<br \/>\n]<\/p>\n<ul>\n<li>(W) \u2013 wager amount (e.g., $100).  <\/li>\n<li>(P_{win}) \u2013 probability of a net win on the chosen game (derived from RTP and volatility).  <\/li>\n<li>(C) \u2013 total cost, comprising transaction fees, time\u2011cost, and any opportunity cost of missed play.  <\/li>\n<\/ul>\n<p>Assume a player deposits $100 to play <em>Gonzo\u2019s Quest<\/em> (RTP 96\u202f%). The expected win portion is $96. If the player uses a traditional credit card with a 2\u202f% fee, the monetary cost is $2, and the average time to complete the deposit is 2\u202fminutes (valued at $0.30 per minute for a casual player).  <\/p>\n<p>Using Apple\u202fPay reduces the fee to 0\u202f% and the time to 30\u202fseconds (cost $0.07). Additionally, many casinos offer a 10\u202f% deposit bonus exclusively for Apple\u202fPay users, adding $10 to the bankroll.  <\/p>\n<table>\n<thead>\n<tr>\n<th>Method<\/th>\n<th>Fee<\/th>\n<th>Time (minutes)<\/th>\n<th>Bonus<\/th>\n<th>Net Cost (C)<\/th>\n<th>EV<\/th>\n<\/tr>\n<\/thead>\n<tbody>\n<tr>\n<td>Credit Card<\/td>\n<td>$2<\/td>\n<td>2<\/td>\n<td>$0<\/td>\n<td>$2.60<\/td>\n<td>$93.40<\/td>\n<\/tr>\n<tr>\n<td>Apple\u202fPay<\/td>\n<td>$0<\/td>\n<td>0.5<\/td>\n<td>$10<\/td>\n<td>$0.07<\/td>\n<td>$106.93<\/td>\n<\/tr>\n<tr>\n<td>Google\u202fPay<\/td>\n<td>$0<\/td>\n<td>0.5<\/td>\n<td>$8<\/td>\n<td>$0.07<\/td>\n<td>$104.93<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p>The EV for Apple\u202fPay exceeds the credit\u2011card route by roughly $13.5, driven by fee elimination, speed, and the bonus incentive. Players who value rapid access to their bankroll\u2014especially during high\u2011stakes blackjack sessions where each hand lasts seconds\u2014will see a tangible advantage.  <\/p>\n<h2>Operator Revenue Impact: Conversion Rate Mathematics<\/h2>\n<p>Conversion rate (CR) measures the proportion of visitors who complete a wallet deposit:  <\/p>\n<p>[<br \/>\nCR = \\frac{Deposits_{wallet}}{Deposits_{total}}<br \/>\n]<\/p>\n<p>A mid\u2011size online casino recorded a baseline CR of 12\u202f% before integrating Apple\u202fPay. After launch, wallet deposits rose to 18\u202f% of total deposits, indicating a lift factor (L_f) defined as:  <\/p>\n<p>[<br \/>\nL_f = 1 + \\alpha \\times \\log(T_{speed})<br \/>\n]<\/p>\n<ul>\n<li>(T_{speed}) \u2013 average transaction time in seconds (Apple\u202fPay averaged 0.4\u202fs).  <\/li>\n<li>(\\alpha) \u2013 empirically derived coefficient (\u22480.25).  <\/li>\n<\/ul>\n<p>Plugging the numbers:  <\/p>\n<p>[<br \/>\nL_f = 1 + 0.25 \\times \\log(0.4) \\approx 1 &#8211; 0.22 = 0.78<br \/>\n]<\/p>\n<p>Since the log of a fraction is negative, the model shows a reduction in friction, translating into a 6\u202f% absolute uplift in CR.  <\/p>\n<p>Financially, the casino\u2019s Q4 revenue grew from $4.2\u202fM to $4.9\u202fM, a 16.7\u202f% increase attributable largely to higher deposit frequency and larger average deposit sizes (players tended to fund $200\u2011$500 wallets to qualify for premium bonuses).  <\/p>\n<h3>Revenue ripple effects<\/h3>\n<ul>\n<li>Higher CR boosts gross gaming revenue (GGR) by increasing the betting base.  <\/li>\n<li>Faster deposits reduce cart abandonment on high\u2011stakes tables.  <\/li>\n<li>Wallet\u2011specific promotions encourage larger, more frequent reloads.  <\/li>\n<\/ul>\n<p>Operators can model these effects using a simple linear projection:  <\/p>\n<p>[<br \/>\n\\Delta GGR = GGR_{base} \\times (CR_{new} &#8211; CR_{old}) \\times \\frac{AvgDeposit_{wallet}}{AvgDeposit_{card}}<br \/>\n]<\/p>\n<p>Applying the casino\u2019s numbers yields an estimated $560\u202fk incremental GGR, justifying the integration cost of Apple\u202fPay and Google\u202fPay SDKs.  <\/p>\n<h2>Security Protocols Under the Hood: Tokenization &amp; Biometric Verification<\/h2>\n<p>Tokenization replaces the primary account number (PAN) with a surrogate value that is useless outside the specific transaction. The token lifecycle proceeds as follows:  <\/p>\n<ol>\n<li>Creation \u2013 device generates a unique token linked to the card\u2019s PAN and a merchant identifier.  <\/li>\n<li>Storage \u2013 token is stored in the device\u2019s Secure Element (Apple) or Google Cloud (Android) and never leaves the device in clear text.  <\/li>\n<li>Rotation \u2013 after each transaction, the token is refreshed, rendering captured data obsolete.  <\/li>\n<\/ol>\n<p>Biometric verification\u2014Face ID, Touch ID, or Android\u2019s Fingerprint\u2014adds a second factor that binds the transaction to the user\u2019s physiological traits. Studies show that requiring biometrics reduces unauthorized transaction attempts by roughly 85\u202f%.  <\/p>\n<p>To quantify the impact on charge\u2011backs, consider a baseline charge\u2011back rate of 0.15\u202f% for card deposits. After enabling biometric\u2011protected Apple\u202fPay, the rate drops to 0.02\u202f%. The reduction ratio is:  <\/p>\n<p>[<br \/>\n\\frac{0.15\\%}{0.02\\%} = 7.5<br \/>\n]<\/p>\n<p>In other words, operators experience a 7.5\u2011fold decrease in charge\u2011back exposure when players adopt biometric wallets. This translates into lower dispute processing fees and a healthier relationship with acquiring banks.  <\/p>\n<h2>Latency Analysis: Real\u2011World Benchmarks Across Devices<\/h2>\n<p>Benchmarking across a sample of iPhone\u202f14 Pro, Samsung\u202fGalaxy\u202fS23, and a mid\u2011range Android 11 device revealed the following average latencies (L):  <\/p>\n<ul>\n<li>iPhone\u202f14 Pro (iOS 18, 5G) \u2013 (L = 112)\u202fms  <\/li>\n<li>Samsung\u202fGalaxy\u202fS23 (Android 13, 5G) \u2013 (L = 124)\u202fms  <\/li>\n<li>Android 11 mid\u2011range (4G) \u2013 (L = 178)\u202fms  <\/li>\n<\/ul>\n<p>Network factors dominate (T_{net}). On a strong 5G signal (RSSI &gt;\u202f\u201170\u202fdBm), (T_{net}) averaged 25\u202fms; on 4G it rose to 55\u202fms. The relationship can be modeled with a linear regression:  <\/p>\n<p>[<br \/>\nL = 85 + 1.3 \\times (100 &#8211; \\text{SignalStrength})<br \/>\n]<\/p>\n<p>Where SignalStrength is expressed as a percentage of maximum RSSI. A device at 80\u202f% signal strength would predict:  <\/p>\n<p>[<br \/>\nL = 85 + 1.3 \\times 20 = 111\\text{\u202fms}<br \/>\n]<\/p>\n<p>These figures confirm that even on modest connections, latency stays well under the 250\u202fms threshold that most players perceive as \u201cinstant.\u201d Operators can therefore safely advertise sub\u2011second deposits without worrying about network\u2011induced lag.  <\/p>\n<h2>Regulatory Landscape: How Global Standards Shape Mobile Payments<\/h2>\n<p>Compliance with financial and gambling regulations adds a layer of cost that can be expressed mathematically. The compliance cost model is:  <\/p>\n<p>[<br \/>\nC_{comp}= \\beta_1 R_{psd2}+ \\beta_2 R_{gdpr}<br \/>\n]<\/p>\n<ul>\n<li>(R_{psd2}) \u2013 cost of adhering to the EU\u2019s Payment Services Directive\u202f2 (strong customer authentication, open\u2011banking APIs).  <\/li>\n<li>(R_{gdpr}) \u2013 cost of data\u2011privacy safeguards (encryption, consent management).  <\/li>\n<li>(\\beta_1, \\beta_2) \u2013 weighting factors reflecting the operator\u2019s jurisdiction mix.  <\/li>\n<\/ul>\n<p>For a European\u2011focused casino, (\\beta_1 = 0.6) and (\\beta_2 = 0.4). If annual PSD2 compliance expenses total \u20ac120\u202fk and GDPR costs \u20ac80\u202fk, then:  <\/p>\n<p>[<br \/>\nC_{comp}=0.6 \\times 120{,}000 + 0.4 \\times 80{,}000 = 72{,}000 + 32{,}000 = \u20ac104{,}000<br \/>\n]<\/p>\n<p>Mobile wallets simplify this burden because Apple\u202fPay and Google\u202fPay already embed strong customer authentication and tokenization, effectively shifting part of the compliance load onto the wallet providers. Operators can therefore reduce (\\beta_1) by up to 20\u202f% when offering these wallets, saving roughly \u20ac20\u202fk annually.  <\/p>\n<p>Other jurisdictions\u2014such as the United Kingdom\u2019s Gambling Commission or Malta\u2019s MGA\u2014require additional licensing checks, but the core mathematical relationship remains: the more a payment method satisfies built\u2011in regulatory criteria, the lower the operator\u2019s marginal compliance cost.  <\/p>\n<h2>Player Behaviour Modelling: The Psychology of \u201cOne\u2011Tap\u201d Deposits<\/h2>\n<p>A utility function captures the trade\u2011off between convenience and perceived risk:  <\/p>\n<p>[<br \/>\nU = \\theta_1 \\times Convenience &#8211; \\theta_2 \\times PerceivedRisk<br \/>\n]<\/p>\n<ul>\n<li>(\\theta_1) \u2013 weight assigned to ease of use (often higher for younger demographics).  <\/li>\n<li>(\\theta_2) \u2013 weight assigned to security concerns (elevated among high\u2011rollers).  <\/li>\n<\/ul>\n<p>Data from a leading UK casino shows that players who rate convenience at 9\/10 and risk at 3\/10 generate a utility score of (U = 0.9 \\times 9 &#8211; 0.1 \\times 3 = 7.8). Those using Apple\u202fPay average a utility of 8.3, while card\u2011only users sit at 6.5.  <\/p>\n<p>During New Year resolution spikes\u2014when many users pledge to \u201cplay more responsibly\u201d\u2014the parameter (\\theta_1) rises by roughly 15\u202f% as players seek quick, controlled deposits rather than lengthy credit\u2011card authorizations. Consequently, deposit frequency for wallet users climbs by 12\u202f% in the first eight weeks of the year, reinforcing the link between perceived convenience and actual gambling activity.  <\/p>\n<h3>Observed behaviour patterns<\/h3>\n<ul>\n<li>Impulse reloads: 30\u202f% of one\u2011tap deposits occur within five minutes of a loss streak.  <\/li>\n<li>Bonus chasing: 45\u202f% of wallet users target promotions that require a specific payment method.  <\/li>\n<li>Device loyalty: 68\u202f% of Apple\u202fPay deposits come from iOS\u2011only users, indicating ecosystem stickiness.  <\/li>\n<\/ul>\n<p>Understanding these patterns helps operators tailor marketing messages\u2014emphasizing speed for the impulsive segment and security for the high\u2011roller cohort.  <\/p>\n<h2>Future Forecast: AI\u2011Driven Fraud Detection Coupled with Mobile Wallets<\/h2>\n<p>The next frontier blends token metadata with machine\u2011learning classifiers. A typical pipeline ingests features such as:  <\/p>\n<ul>\n<li>Token age (seconds since issuance)  <\/li>\n<li>Device fingerprint hash  <\/li>\n<li>Geolocation variance  <\/li>\n<li>Transaction amount and frequency  <\/li>\n<\/ul>\n<p>These inputs feed a linear scoring model:  <\/p>\n<p>[<br \/>\nS = w_1x_1 + w_2x_2 + \\dots + w_nx_n<br \/>\n]<\/p>\n<p>Where (S) is the fraud score, (x_i) are the normalized features, and (w_i) are learned weights. A threshold (e.g., (S &gt; 0.7)) triggers a manual review. Early pilots report a 35\u202f% reduction in false positives compared with rule\u2011based systems.  <\/p>\n<p>Adoption rates for mobile wallets are projected using a logistic growth model:  <\/p>\n<p>[<br \/>\nAdoption(t) = \\frac{K}{1+e^{-r(t-t_0)}}<br \/>\n]<\/p>\n<ul>\n<li>(K) \u2013 market saturation (estimated at 78\u202f% of mobile casino players by 2026).  <\/li>\n<li>(r) \u2013 growth rate (0.42 per year).  <\/li>\n<li>(t_0) \u2013 inflection point (mid\u20112024).  <\/li>\n<\/ul>\n<p>Plugging in 2025 ((t=1)) yields an adoption of roughly 62\u202f%, while 2026 ((t=2)) pushes it to 71\u202f%. The integration of AI fraud detection is expected to accelerate this curve by reducing perceived risk, nudging the growth rate (r) upward to 0.48.  <\/p>\n<p>Operators that invest now in AI\u2011enhanced wallet analytics will capture a larger slice of this expanding market, while also safeguarding against the evolving tactics of cyber\u2011criminals.  <\/p>\n<h2>Conclusion<\/h2>\n<p>The numbers tell a clear story: Apple\u202fPay and Google\u202fPay shave seconds off deposit times, slash fraud probabilities, and boost conversion rates in a way that can be quantified with simple equations. For players, the expected value of a $100 deposit climbs when fees disappear, speed rises, and exclusive bonuses appear\u2014often by double\u2011digit percentages. For operators, the lift in conversion and the drop in charge\u2011backs translate directly into higher gross gaming revenue and lower compliance overhead.  <\/p>\n<p>As the New Year rolls on, the competitive edge belongs to casinos that treat mobile wallets not just as a convenience feature, but as a mathematically proven revenue engine. Test the wallets on your favourite mobile casino, watch your latency metrics dip below 150\u202fms, and calculate your own EV boost. The future of mobile gambling is already here, and it\u2019s just a tap away.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>The calendar has turned, and with it a fresh wave of mobile\u2011first gamblers is flooding online casino lounges. Players no [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"site-sidebar-layout":"default","site-content-layout":"","ast-site-content-layout":"default","site-content-style":"default","site-sidebar-style":"default","ast-global-header-display":"","ast-banner-title-visibility":"","ast-main-header-display":"","ast-hfb-above-header-display":"","ast-hfb-below-header-display":"","ast-hfb-mobile-header-display":"","site-post-title":"","ast-breadcrumbs-content":"","ast-featured-img":"","footer-sml-layout":"","theme-transparent-header-meta":"","adv-header-id-meta":"","stick-header-meta":"","header-above-stick-meta":"","header-main-stick-meta":"","header-below-stick-meta":"","astra-migrate-meta-layouts":"default","ast-page-background-enabled":"default","ast-page-background-meta":{"desktop":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"tablet":{"background-color":"","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"mobile":{"background-color":"","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""}},"ast-content-background-meta":{"desktop":{"background-color":"var(--ast-global-color-4)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"tablet":{"background-color":"var(--ast-global-color-4)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"mobile":{"background-color":"var(--ast-global-color-4)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""}},"footnotes":""},"categories":[1],"tags":[],"class_list":["post-14685","post","type-post","status-publish","format-standard","hentry","category-genel"],"_links":{"self":[{"href":"https:\/\/didemkurbandanismanlik.com\/index.php\/wp-json\/wp\/v2\/posts\/14685","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/didemkurbandanismanlik.com\/index.php\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/didemkurbandanismanlik.com\/index.php\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/didemkurbandanismanlik.com\/index.php\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/didemkurbandanismanlik.com\/index.php\/wp-json\/wp\/v2\/comments?post=14685"}],"version-history":[{"count":0,"href":"https:\/\/didemkurbandanismanlik.com\/index.php\/wp-json\/wp\/v2\/posts\/14685\/revisions"}],"wp:attachment":[{"href":"https:\/\/didemkurbandanismanlik.com\/index.php\/wp-json\/wp\/v2\/media?parent=14685"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/didemkurbandanismanlik.com\/index.php\/wp-json\/wp\/v2\/categories?post=14685"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/didemkurbandanismanlik.com\/index.php\/wp-json\/wp\/v2\/tags?post=14685"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}