<img src="https://m2p-website-file.s3.ap-south-1.amazonaws.com/marketing-cms/m2p-blog/2026/10/blog_banner_2000x1000.webp" alt="What Apple Pay’s arrival means for card issuers in the Philippines" title="" id="a2koktuvq" width="100%" height="347"> Digital payments keep climbing in the Philippines. The latest full-year data shows they made up <a class="link" href="https://tribune.net.ph/2026/08/19/bsp-digital-payments-account-for-nearly-two-thirds-of-retail-volume">64.7% of retail payment volume, up from 57.4% a year earlier</a>. Customers are paying digitally <a class="link" href="https://www.sunstar.com.ph/cebu/ph-hits-digital-payments-target">more often, at more merchants and through more channels</a>. Apple Pay’s arrival is a natural next step, and for card issuers it raises a practical question: is your card ready to be part of that everyday habit? The first weeks of the rollout show where the real work lies.<h3 class="heading-node" id="2te3uyrq2">Digital payments are already the norm</h3>Digital payments now sit inside the national <a class="link" href="https://tribune.net.ph/2026/08/19/bsp-digital-payments-account-for-nearly-two-thirds-of-retail-volume" target="_blank">60% to 70%</a> target range, supported by a <a class="link" href="https://www.sunstar.com.ph/cebu/ph-hits-digital-payments-target" target="_blank">69.4% rise in digital payment accounts</a> and a 36.3% rise in merchant locations that accept them. Growth has come from several channels. QR Ph alone processed <a class="link" href="https://www.sunstar.com.ph/cebu/ph-hits-digital-payments-target" target="_blank">2.47 billion transactions worth ₱1.16 trillion</a> over the latest full year and, for the first time, exceeded debit and credit card transactions, reflecting a growing preference for interoperable, account-based payments.Our reading: customers now have more digital ways to pay than ever. For issuers, that makes presence a priority. Cards need to be available in the places customers already pay, and for many customers that place is the phone.<h3 class="heading-node" id="kvn5zq9ru">So how did the Apple Pay launch go?</h3>Apple Pay went live on August 4, 2026 with four Philippine banks, covering eligible Visa and Mastercard cards. Customers keep earning the same rewards, and select banks let customers get an instant virtual card and add it to Apple Pay straight away. Retailers, restaurants and online platforms were live from day one, and a leading payment processor is enabling Apple Pay for more than 5,000 online merchants.Google Pay launched in November 2025 with nine banks and financial institutions, so several issuers that were live on Google Pay were not among Apple Pay’s four launch banks.<h3 class="heading-node" id="9woc7yrya">Launching is the easy part</h3>Regulators have classified Apple Pay as a technology service provider rather than a payment system operator, so the regulatory path is clear. What remains is technical: local issuers must upgrade core systems to support card tokenization, which replaces card numbers with encrypted, device-specific tokens.That upgrade is one layer of many. A single tap depends on <a class="link" href="https://m2pfintech.com/blog/apple-pay-is-live-in-the-philippines-heres-what-issuers-need-to-do-next/">ten layers</a>, from card and BIN eligibility through issuer processing, tokenization and provisioning to fraud operations and launch testing. When different teams own different layers, the result is rework, unclear ownership and a customer experience that feels disjointed. Even at launch, Apple limits support to eligible cards, so coverage differs by bank and by card product.Here’s how those ten layers look when they’re scattered versus connected:<img src="https://m2p-website-file.s3.ap-south-1.amazonaws.com/marketing-cms/m2p-blog/2026/10/apple-pay.webp" alt="Side-by-side comparison of ten Apple Pay enablement layers, scattered across vendors versus connected on one M2P platform." title="" id="ozdp0cm5h" width="100%" height="703"><h3 class="heading-node" id="dijaxnnhx">What makes people use it every day?</h3>Adding a card to Apple Wallet is a one-time event. Everyday use comes from habit: in-store taps, app checkouts and online purchases without retyping card details. Apple says card numbers are not stored on the device or on its servers, and that transactions stay between the customer, the merchant and their bank or card issuer, which matters for customer trust.For issuers, the opportunity is to be the card customers choose at the top of the wallet, not one they added once and forgot. That depends on smooth provisioning, tokens that stay in sync when cards are renewed, replaced or suspended, and fraud controls that recognize tokenized transactions.<h3 class="heading-node" id="m71xtnaxi">What can issuers do right now?</h3><ol class="list-node" id="6in81czmc"><li>Choose the portfolio sequence - Decide which debit, credit and prepaid products and BINs go first, based on customer demand, network readiness and complexity.</li><li>Make the issuer processor token-aware - Authorization, decline logic and lifecycle events (renewal, replacement, suspension, closure) all need to recognize tokens.</li><li>Offer push provisioning in your own app - Letting an authenticated customer add a card directly keeps the bank at the center of the experience and <a class="link" href="https://m2pfintech.com/blog/apple-pay-is-live-in-the-philippines-heres-what-issuers-need-to-do-next/">typically improves conversion compared with wallet-led provisioning alone</a>.</li></ol>Our <a class="link" href="https://m2pfintech.com/blog/apple-pay-is-live-in-the-philippines-heres-what-issuers-need-to-do-next/">earlier guide</a> walks through the full seven-step framework.<h3 class="heading-node" id="stt66h9fq">Where M2P Fintech fits in</h3>M2P brings card management, issuer processing, network <a class="link" href="https://m2pfintech.com/blog/cracking-tokenization-for-bnpl-player-tabby/" target="_blank">tokenization</a> and wallet enablement together on one platform, and <a class="link" href="https://m2pfintech.com/blog/apple-pay-is-live-in-the-philippines-heres-what-issuers-need-to-do-next/">already powers Apple Pay for card issuers across the Middle East in live portfolios</a>. From card eligibility to launch testing, M2P supports each of the ten layers, so issuers can treat tokenization, processing and provisioning as one connected build rather than three separate projects.Planning your Apple Pay rollout, or looking to expand eligible cards? <a class="link" href="https://m2pfintech.com/contact-us/?activeKey=1" target="_blank">Talk to our team today!</a><h2 class="heading-node" id="kylriuxpm">Frequently Asked Questions</h2><ul class="list-node" id="bnyj2gpez"><li>How do banks enable Apple Pay in the Philippines? An issuer needs eligible BINs, a token-aware issuer processor, connectivity to the Visa and Mastercard token services, provisioning journeys (wallet-led and in-app), fraud and risk controls, and end-to-end testing. <a class="link" href="https://m2pfintech.com/blog/apple-pay-is-live-in-the-philippines-heres-what-issuers-need-to-do-next/">These layers work best when run as one connected programme</a> rather than separate projects.</li><li>What is push provisioning, and why does it matter? Push provisioning lets an authenticated customer add a card to a wallet directly from the bank’s own mobile app, instead of starting in the wallet. It keeps the bank at the center of the experience and typically improves the share of customers who complete setup.</li><li>Why does Apple Pay matter when digital payments are already growing? <a class="link" href="https://tribune.net.ph/2026/08/19/bsp-digital-payments-account-for-nearly-two-thirds-of-retail-volume">Digital payments made up 64.7% of retail payment volume in the latest full year</a>, across several channels. Apple Pay lets a bank’s cards, with their rewards, sit in the phone for tap, in-app and online payments, so issuers stay part of that everyday habit.</li></ul>

Digital Payments Are Rising in the Philippines. Why Apple Pay Matters for Issuers

Build vs. Buy for KYC: When In-House Identity Verification Stops Making Sense

Use Cases of Merchant Acquiring: QR, POS, SoftPOS, BNPL and More

In September 2026, the Unified Payments Interface (UPI) crossed <a class="link" href="https://www.npci.org.in/product/upi/product-statistics" target="_blank">24 billion transactions in a single month</a>, according to National Payments Corporation of India (NPCI) data. Each transaction must be matched across banks, switches, aggregators, and ledgers, often inside a daily settlement window.Volume is only part of the problem. New rails such as the Digital Rupee, richer ISO 20022 message data, and cross-border linkages add formats, currencies, and time zones that payment reconciliation software built for fewer rails was not designed to absorb.Regulation adds pressure on where this work runs. Since 2018, the Reserve Bank of India (RBI) has required payment system data to be stored only in India, which shapes how reconciliation platforms are hosted.For banks, this creates a widening gap between how fast payments change and how fast reconciliation can adapt. This guide covers eight shifts behind that gap, what each means for reconciliation, and the capabilities a future-ready platform needs.<h2 class="heading-node" id="61iq7us5u">1. UPI's Next Phase, UPI Lite, and International UPI: More Variables to Reconcile</h2>UPI is the foundation of digital payments in India, and its feature set keeps growing. Recent and proposed enhancements, such as overdraft-linked accounts, invoice verification, and signed intent, introduce new data points that reconciliation teams must track and match.UPI Lite's offline mode and NPCI's push to expand international merchant acceptance add more data sources and more reconciliation endpoints to an already high-volume rail.What this means for reconciliation: Platforms must connect to multiple UPI application programming interfaces (APIs), process settlement updates in near real time, and reconcile multi-currency transactions as cross-border UPI use grows.<h2 class="heading-node" id="zw9309opr">2. CBDC (Digital Rupee): Reconciling Against a Central Ledger</h2>The RBI's Central Bank Digital Currency (CBDC) pilot covers both retail and wholesale use. CBDC transactions differ from conventional bank transfers, and settlements may need verification against a ledger that the central bank maintains.What this means for reconciliation: Platforms will need ledger verification steps in their workflows. They must also reconcile CBDC settlements alongside traditional rails without duplicating records or losing data.<h2 class="heading-node" id="y8zccgg0c">3. Open Banking and the Account Aggregator Framework</h2>Under RBI regulation, the Account Aggregator (AA) framework lets regulated institutions share financial data securely, based on customer consent. For reconciliation, this could support transaction matching across institutions and products. A single view could bring together loan disbursements, card payments, and mutual fund redemptions across banks and fintechs.What this means for reconciliation: Engines must ingest standardized data formats, such as Non-Banking Financial Company–Account Aggregator (NBFC-AA) specifications, and operate across product lines and regulatory requirements.<h2 class="heading-node" id="o3rwfft3d">4. FASTag and Transit Payments: The Rise of Micro-Transactions</h2>FASTag use is extending beyond highway tolls into areas such as parking and urban transit. These high-volume, low-value payments often need aggregation before settlement.What this means for reconciliation: Systems must process large volumes of low-value transactions efficiently, so merchant settlements are not delayed.<h2 class="heading-node" id="ld4trxf5y">5. Tightening Compliance and Settlement Expectations</h2>Regulatory expectations for fraud monitoring, suspicious transaction reporting, and settlement timelines continue to tighten. Payment aggregators, for example, operate under RBI-defined settlement timelines for merchants.What this means for reconciliation: Reconciliation should shift from end-of-day batch processing toward continuous matching. Teams can then meet compliance thresholds as transactions occur, not only report on them afterward.<h2 class="heading-node" id="mlxf5jdrp">6. ISO 20022 Migration: Richer Data, More Complex Structures</h2>The RBI has indicated plans to adopt ISO 20022 for payment messaging systems such as Real Time Gross Settlement (RTGS) and National Electronic Funds Transfer (NEFT). The standard carries richer transaction metadata, which can improve matching accuracy. It also introduces more complex data structures.What this means for reconciliation: Platforms should be ISO 20022-ready, able to parse, match, and analyze the additional fields while maintaining processing performance.<h2 class="heading-node" id="20ngkvg62">7. Cross-Border Payment Integration</h2>India is connecting its payment systems with international partners, including Singapore through the PayNow–UPI linkage and the United Arab Emirates (UAE). These linkages bring more currencies, time zones, and regulatory regimes into everyday transaction flows.What this means for reconciliation: Systems must manage foreign exchange (FX) conversions, normalize time zones, and support compliance reporting across jurisdictions.<h2 class="heading-node" id="u6myblg3y">8. Data Localization and Security</h2>RBI guidelines require payment system data for Indian transactions to be stored only in India. Reconciliation platforms therefore need an architecture built for local data storage, while still integrating with global systems.India's Digital Personal Data Protection Act adds a broader data protection layer on top of these requirements. Our guide to the <a class="link" href="https://m2pfintech.com/blog/dpdp-act-data-residency-cloud-reconciliation-platforms/" target="_blank">DPDP Act and data residency for cloud-hosted reconciliation</a> platforms covers this in detail.What this means for reconciliation: Cloud-native solutions must run on India-based data centers and adapt as data privacy requirements evolve.<h2 class="heading-node" id="ars5y6yzw">What a Future-Ready Reconciliation Architecture Looks Like</h2>A future-ready reconciliation platform delivers six core capabilities:<ul class="list-node" id="2e9fn16g9"><li>API-first, modular design: Easy integration with new payment rails, fintech platforms, and regulatory APIs</li><li>Multi-rail, multi-currency support: Dynamic matching logic that adapts to UPI, NEFT, Immediate Payment Service (IMPS), FASTag, CBDC, and future payment types through configuration rather than major code rewrites</li><li>Predictive exception handling: <a class="link" href="https://m2pfintech.com/blog/ai-powered-payment-reconciliation-software/" target="">AI-driven</a> detection of patterns likely to cause mismatches, such as recurring delays from specific payment service providers</li><li>Continuous reconciliation: Streaming data processing in place of batch cycles</li><li>Compliance-by-design: Automated record retention, regulatory reporting, and audit trail creation</li><li>Cloud-native, geo-compliant infrastructure: Scalability that satisfies RBI data localization requirements</li></ul><h2 class="heading-node" id="chd91xdvo">How Recon360 Supports Future-Ready Reconciliation</h2>Recon360, M2P Fintech's reconciliation and settlement automation platform, is designed around these principles. It helps banks, fintechs, and payment businesses automate reconciliation across rails, products, and partners from a single platform.<table class="border-collapse border border-gray-300" style="min-width: 50px;"><colgroup><col style="min-width: 25px;"><col style="min-width: 25px;"></colgroup><tbody><tr class="border border-gray-300"><th class="border border-gray-300 bg-gray-100" colspan="1" rowspan="1">Capability</th><th class="border border-gray-300 bg-gray-100" colspan="1" rowspan="1">How Recon360 Supports It</th></tr><tr class="border border-gray-300"><td class="border border-gray-300 p-2" colspan="1" rowspan="1">Multi-rail, multi-source reconciliation</td><td class="border border-gray-300 p-2" colspan="1" rowspan="1">Reconciles payment, settlement, and General Ledger (GL) data across sources, entities, and currencies in one workflow</td></tr><tr class="border border-gray-300"><td class="border border-gray-300 p-2" colspan="1" rowspan="1">AI-driven matching and <a class="link" href="https://m2pfintech.com/blog/exception-management-reconciliation-best-practices/" target="_blank">exception handling</a></td><td class="border border-gray-300 p-2" colspan="1" rowspan="1">Applies AI-driven matching and configurable rules, and routes breaks to assigned owners with context attached</td></tr><tr class="border border-gray-300"><td class="border border-gray-300 p-2" colspan="1" rowspan="1">Continuous monitoring</td><td class="border border-gray-300 p-2" colspan="1" rowspan="1">Supports near-real-time transaction monitoring alongside scheduled reconciliation cycles</td></tr><tr class="border border-gray-300"><td class="border border-gray-300 p-2" colspan="1" rowspan="1">Configurable workflows</td><td class="border border-gray-300 p-2" colspan="1" rowspan="1">Lets teams adapt rules and workflows as new payment methods and data formats arrive</td></tr><tr class="border border-gray-300"><td class="border border-gray-300 p-2" colspan="1" rowspan="1">Audit readiness</td><td class="border border-gray-300 p-2" colspan="1" rowspan="1">Maintains a timestamped audit trail for every match, exception, and action</td></tr><tr class="border border-gray-300"><td class="border border-gray-300 p-2" colspan="1" rowspan="1">Deployment flexibility</td><td class="border border-gray-300 p-2" colspan="1" rowspan="1">Supports cloud and on-premise deployment, so institutions can align hosting with data residency requirements</td></tr></tbody></table>Because these capabilities sit on one platform, a bank adding a new rail can extend existing workflows instead of building a separate reconciliation process for each one. Teams also see exceptions, settlements, and ledger positions in the same place, which shortens the path from a mismatch to its cause.<h2 class="heading-node" id="laguux0j6">Why Strategic Adoption Matters Now</h2>Indian financial institutions face a twofold challenge: payment innovation cycles are shortening while compliance expectations tighten. The gap between what is possible and what is mandated keeps narrowing.Intelligent reconciliation helps institutions respond to both. It supports onboarding new payment methods in a structured way and meeting compliance requirements with less manual effort.Institutions that delay modernizing reconciliation face growing exception backlogs, settlement delays, and audit exposure as rails multiply. Customer expectations are also rising for faster refunds, real-time account visibility, and proactive fraud prevention.In a market where speed, accuracy, and trust shape outcomes, future-ready reconciliation is a strategic capability, not only an operational upgrade.To see how <a class="link" href="https://m2pfintech.com/recon360/" target="">Recon360</a> supports reconciliation across rails, products, and partners, connect with <a class="link" href="https://m2pfintech.com/contact-us/?utm_source=Blog&amp;utm_medium=Recon360&amp;utm_campaign=future_ready_reconciliation" target="">our team</a>.<h2 class="heading-node" id="k2108hyss">Frequently Asked Questions</h2>What is future-ready reconciliation? It is a reconciliation approach built to adapt to new payment rails, data standards, and regulations. It relies on API-first design, continuous matching, AI-driven exception handling, and built-in compliance.How do newer UPI features affect bank reconciliation? Features such as overdraft-linked accounts, invoice verification, and signed intent add new variables. Banks must integrate multiple UPI APIs and handle near-real-time settlements and multi-currency flows.Why does ISO 20022 matter for reconciliation? ISO 20022 carries richer transaction metadata, which can improve matching accuracy. Platforms must be able to parse these more complex structures without slowing down.How do RBI data localization rules affect reconciliation platforms? Payment system data for Indian transactions must be stored in India. Reconciliation platforms need India-based data centers while still integrating with global systems.How does Recon360 support future-ready reconciliation? Recon360 reconciles payment, settlement, and GL data across rails, entities, and currencies on one platform. It combines AI-driven matching, configurable exception workflows, audit trails, and cloud or on-premise deployment options.

Future-Ready Reconciliation: How Banks Can Keep Pace With India's Payment Shifts

Kenya and Nigeria are two of Africa's busiest digital lending markets. The Central Bank of Kenya reports that licensed digital lenders had disbursed KSh 150.56 billion across more than 8.37 million loans by May 2026. As volumes grew, both countries tightened the rules on two fronts. They brought digital lenders under formal licensing, and they passed data-protection laws that limit how far an algorithm can decide a loan without a person involved.For a lender using AI in underwriting, that creates a clear test. A human must remain accountable for material decisions. The lender must be able to explain each outcome. And a record must exist that a regulator or borrower can ask to see. This post covers what each market requires and how an origination platform can be built to meet it.<h3 class="heading-node" id="cg6lyyahg">Kenya: licensed lenders, limited automation</h3>Kenya's Central Bank (Digital Credit Providers) Regulations, 2022 put digital lenders under CBK licensing. The CBK assesses each applicant's business model, consumer-protection practices, and the suitability of its owners and managers. By mid-2026 it had licensed over 250 providers from more than 800 applications. The regime targets expensive borrowing, abusive collection practices, and misuse of borrowers' personal data.The Data Protection Act 2019, enforced by the Office of the Data Protection Commissioner (ODPC), adds two provisions that matter for AI-led credit:<ul class="list-node" id="q6ooi81op"><li>Section 35: People have the right not to be subjected to a decision based solely on automated processing, including profiling, when it significantly affects them. A loan approved or declined with no human involvement falls squarely within this.</li><li>Section 31: A data protection impact assessment is required before high-risk processing. ODPC regulations treat automated decision-making that determines access to services as high-risk.</li></ul>Enforcement is real. The ODPC has issued 184 compensation orders, 134 enforcement notices, and 20 penalty notices since the Act came into force. Digital lenders have been penalised over consent and personal-data handling.<h3 class="heading-node" id="0i4e44s2b">Nigeria: a conduct crackdown and a data law with teeth</h3>Nigeria divides oversight between two regulators.On conduct, the Federal Competition and Consumer Protection Commission (FCCPC) issued its Digital, Electronic, Online or Non-Traditional Consumer Lending Regulations in 2025. They took effect on 21 July 2025, with a compliance deadline of 5 January 2026. Any lender operating through an app, website, or other non-traditional channel must register with the FCCPC. The rules target abusive recovery, unauthorised access to borrower data, and predatory pricing. The Federal High Court in Lagos upheld them in July 2026 after a trade body challenged the FCCPC's authority.On data, the Nigeria Data Protection Act 2023 created the Nigeria Data Protection Commission (NDPC). Section 37 gives individuals the right not to be subject to a solely automated decision with legal or similarly significant effects, plus the right to human intervention and to contest the outcome. The Act also expects lenders to tell borrowers when automated decision-making or profiling is used. A DPIA is mandatory before high-risk processing.The NDPC enforces actively. It fined Fidelity Bank ₦555.8 million in August 2024 for processing customer data without valid consent. In June 2026 it announced a review of the Act focused on AI, robotics, and big data.<h3 class="heading-node" id="iw6ledkkd">Four expectations that apply in both markets</h3>The regulators and statutes differ, but their expectations of AI in credit are very similar.<ol class="list-node" id="mxf1h2obn"><li>A person stays accountable. A credit approval or rejection is the clearest example of a decision that significantly affects someone. Human oversight is how lenders stay on the right side of both laws.</li><li>Decisions are explainable. If a borrower can contest an automated outcome, the lender must show what drove it.</li><li>High-risk processing is assessed and documented. A DPIA presumes the lender can describe how its system uses data and reaches a result.</li><li>The evidence exists. Enforcement in both markets turns on consent records, processing records, and audit trails. A lender that can't produce them can't prove compliance, however good its model is.</li></ol><h3 class="heading-node" id="0mnw3lqxr">How M2P's Loan Origination System supports these expectations</h3>M2P's AI-orchestrated Loan Origination System runs digital, branch, embedded, and partner-led origination on one platform. Its configurable Business Rules Engine (BRE) handles credit decisioning, supported by AI agents for documents, fraud, financial analysis, scoring, and credit appraisal memos (CAMs). Here is how that design maps to the four expectations.<table class="border-collapse border border-gray-300" style="min-width: 50px;"><colgroup><col style="min-width: 25px;"><col style="min-width: 25px;"></colgroup><tbody><tr class="border border-gray-300"><th class="border border-gray-300 bg-gray-100" colspan="1" rowspan="1">What regulators expect</th><th class="border border-gray-300 bg-gray-100" colspan="1" rowspan="1">How the M2P LOS supports it</th></tr><tr class="border border-gray-300"><td class="border border-gray-300 p-2" colspan="1" rowspan="1">A human stays accountable</td><td class="border border-gray-300 p-2" colspan="1" rowspan="1">AI agents cut manual effort and turnaround across documents, fraud checks, financial analysis, and CAM generation, while approvals, policies, and accountability stay with the business. Straight-through workflows carry multi-level approvals and deviation management, and the Case Manager routes exceptions to people.</td></tr><tr class="border border-gray-300"><td class="border border-gray-300 p-2" colspan="1" rowspan="1">Explainable decisions</td><td class="border border-gray-300 p-2" colspan="1" rowspan="1">The BRE produces explainable decision outputs, with risk-based pricing and custom scorecards. The Credit Scoring Agent uses explainable AI, and the Policy Compliance Agent validates cases against internal credit policy and flags deviations with auditable outcomes.</td></tr><tr class="border border-gray-300"><td class="border border-gray-300 p-2" colspan="1" rowspan="1">Documented high-risk processing</td><td class="border border-gray-300 p-2" colspan="1" rowspan="1">Rules, scorecards, and pricing logic are configured explicitly, and the BRE supports back-testing against historical portfolio data. Lenders can describe and test how decisions are made before go-live, which is the groundwork a DPIA needs.</td></tr><tr class="border border-gray-300"><td class="border border-gray-300 p-2" colspan="1" rowspan="1">An audit trail that holds up</td><td class="border border-gray-300 p-2" colspan="1" rowspan="1">The BRE supports versioning and auditability for controlled policy enforcement. Case Manager keeps full audit trails with SLA and turnaround monitoring, and role-based dashboards and 100+ configurable MIS reports show decisions, deviations, and policy performance.</td></tr><tr class="border border-gray-300"><td class="border border-gray-300 p-2" colspan="1" rowspan="1">Controlled data handling</td><td class="border border-gray-300 p-2" colspan="1" rowspan="1">75+ pre-integrated APIs cover KYC, banking, bureau, documents, payments, and fraud services. M2P holds ISO 27001, ISO 22301, and PCI DSS certifications. [Product team to confirm deployment and data-residency options for Kenya and Nigeria.]</td></tr></tbody></table>The design principle is that AI supports the decision and the business owns it. The Document Intelligence, Bank Statement Analyser, Financial Analysis, and Fraud Detection agents do the preparatory work, such as classifying documents, parsing statements, and flagging tampering and velocity anomalies. Credit and risk teams then decide within policy. That division is what the automated-decision rules in both countries push lenders toward.The record matters most when a regulator or borrower asks for it. Because decisions run through a governed rules engine and exceptions pass through a managed case workflow, the evidence is created as the loan moves through origination. It doesn't have to be rebuilt afterwards.<h3 class="heading-node" id="z0w5dd8mc">Preparing for a Kenya or Nigeria launch</h3>A few questions are worth settling early:<ul class="list-node" id="k0vrzomv2"><li>Local data sources: Identity documents, credit bureaus, and bank or mobile-money statements differ by market. Plan the integration layer first, since this is where most localisation effort goes.</li><li>Human review points: Decide which decisions (declines, high-value loans, borderline scores) must go to a person, and configure them as explicit rules.</li><li>DPIA readiness: Document data inputs, scoring logic, and exception handling before launch, not after the first regulatory query.</li><li>Cross-border data flows: Both countries attach conditions to moving personal data abroad. Lenders using externally hosted AI models should confirm where borrower data goes and on what basis.</li><li>Consent and notice: Make sure borrowers are told when automated processing or profiling is involved, and that consent records are retrievable.</li></ul><h3 class="heading-node" id="s97y51d7y">Where the rules are heading</h3>Neither regulator has finished. Nigeria has said it will update its data law to address AI directly, and Kenya's ODPC has signalled closer scrutiny of automated decision-making. The rules on how machines may decide loans are becoming more explicit, and enforcement is already live.For lenders, the safest path is governed, explainable decisioning that keeps people in control. That meets today's rules and leaves room for what both regulators are drafting next.Planning to lend in Kenya or Nigeria? Talk to M2P about how our Loan Origination System can bring explainable, auditable credit decisioning to your lending operations. <a class="link" href="https://m2pfintech.com/contact-us/">Get in touch →</a>

Nigeria NDPA & Automated Loan Decisions: What Lenders Need

M2P has been recognized in the Chartis Research RiskTech100® 2027, securing the 75th position globally, placing us among the world’s leading providers of risk and compliance technology.&nbsp;The RiskTech100® is an independent evaluation of the world’s top 100 risk technology providers. It assesses companies across strategic vision, market impact, innovation, customer success, and execution, making it one of the industry’s most respected benchmarks for risk technology leadership.&nbsp;&nbsp;For M2P, this recognition reflects the strength of our Enterprise Fraud &amp; Risk Management platform and our ability to help financial institutions manage fraud across increasingly complex, real-time digital ecosystems.&nbsp;<h2 class="heading-node" id="oha41xh1o" style="text-align: left;">Built for the New Reality of Financial Fraud&nbsp;</h2>Fraud no longer happens within a single channel or at a single point in the customer journey. It moves across onboarding, login, cards, wallets, payments, transfers, BNPL, digital banking, and account servicing.&nbsp;Static rules and fragmented systems cannot keep pace with this complexity.&nbsp;M2P’s Enterprise Fraud &amp; Risk Management platform brings together real-time decisioning, AI and ML-driven risk models, explainable intelligence, behavioral profiling, device intelligence, and enterprise-grade case management in one integrated environment.&nbsp;This enables banks, fintechs, and financial institutions to detect emerging threats earlier, make faster risk decisions, and strengthen fraud operations without adding unnecessary friction to legitimate customer journeys.&nbsp;As Sid Dash, Chief Researcher at Chartis, noted: "M2P Fintech's innovations in fraud risk management provide integrated decisioning across channels, allowing the unification of data silos at scale and the detection of anomalies in real time. This and their high performance and the low latency/real-time nature of its solution is the principal driver for their debut appearance in our RiskTech100® 2027."&nbsp;<h2 class="heading-node" id="ctjbch9vx" style="text-align: left;">Intelligence That Goes Beyond Rules&nbsp;</h2>M2P’s EFRM platform is designed to continuously assess risk using multiple signals across transactions, customers, devices, channels, and behaviors.&nbsp;Its capabilities include:&nbsp;<ul class="list-node" id="g5y5kuwva"><li>Real-time fraud detection and prevention across financial products and channels&nbsp;</li></ul><ul class="list-node" id="4u80kk4zb"><li>Configurable rules and decision engines that allow institutions to adapt strategies as threats evolve&nbsp;</li></ul><ul class="list-node" id="w50h39ymp"><li>AI and ML-driven risk models for more accurate and dynamic fraud detection&nbsp;</li></ul><ul class="list-node" id="fqvg5we0n"><li>Explainable AI that gives risk teams greater visibility into model-led decisions&nbsp;</li></ul><ul class="list-node" id="omhep96tr"><li>Behavioral profiling and biometrics to identify unusual customer activity&nbsp;</li></ul><ul class="list-node" id="7jurjsyh3"><li>Device and contextual intelligence, including device fingerprinting, rooted or jailbroken device detection, IP intelligence, VPN and proxy detection, and location-based risk analysis&nbsp;</li></ul><ul class="list-node" id="951i7hu4f"><li>Listening mode, allowing institutions to validate models before full deployment and optimize performance while reducing false positives&nbsp;</li></ul>Together, these capabilities help institutions move from reactive fraud monitoring to adaptive, intelligence-led risk management.&nbsp;<h2 class="heading-node" id="vn0e3qjxp" style="text-align: left;">From Detection to Resolution&nbsp;</h2>Effective fraud management does not stop at generating an alert.&nbsp;M2P supports the complete fraud operations lifecycle through enterprise-grade case management. The platform enables automated case creation, intelligent prioritization, configurable analyst workflows, automated investigation support, and customer validation across SMS, IVR, and in-app channels.&nbsp;Detailed dashboards and reporting provide risk teams with the visibility needed to monitor patterns, accelerate investigations, maintain auditability, and respond more effectively to changing threats.&nbsp;The result is a more connected operating model that helps institutions detect, investigate, and resolve fraud faster.&nbsp;<h2 class="heading-node" id="a5c0l29f8" style="text-align: left;">Proven at Enterprise Scale&nbsp;</h2>M2P’s fraud and risk capabilities support banking and fintech environments spanning card programs, digital banking, customer onboarding, BNPL, wallets, and real-time payments. Our platform is designed for complex enterprise deployments and can be implemented across cloud and on-premises environments.&nbsp;With a presence across 30+ markets and engagements with 200+ banks, 300+ lenders, and 800+ fintechs, M2P combines global infrastructure scale with a deep understanding of how financial products, payment journeys, and risk operations work together.&nbsp;<h2 class="heading-node" id="utfd2byzf" style="text-align: left;">Recognition That Strengthens Our Ambition&nbsp;</h2>Being named in the Chartis RiskTech100® 2027 is more than an industry accolade. It validates our direction: building intelligent, scalable, and adaptive risk technology for the next generation of financial services.&nbsp;As AI, real-time payments, and digital financial journeys create new opportunities, they also create new risk vectors. M2P remains focused on helping institutions innovate confidently, combining speed and customer experience with the intelligence, control, and resilience required to operate securely.&nbsp;We are proud to be recognized among the world’s leading risk technology providers and even more determined to keep advancing what modern fraud prevention and risk intelligence can deliver.&nbsp; Explore: <a class="link Hyperlink SCXW154504172 BCX0" href="https://www.chartis-research.com/market-analysis/7947547/risktech100r-2027-ranking-and-award-winners" target="_blank" rel="noreferrer noopener">Chartis RiskTech100® 2027 rankings and award winners</a>.

M2P Named Among the World’s Leading Risk Technology Providers in Chartis RiskTech100® 2027

KYC for Microfinance: Biometric eKYC in Low-Connectivity, Field-Led Onboarding

<img src="https://m2p-website-file.s3.ap-south-1.amazonaws.com/marketing-cms/m2p-blog/2026/10/baas-cover-fraud-loss-ownership_2x1.webp" alt="In a BaaS Stack, Whose Fraud Loss Is It, Really?" title="" id="x6grswgvy" width="100%" height="60">A customer gets defrauded on a neobank app. The app was built by a fintech. The fintech doesn't hold a banking license — it operates under a sponsor bank. The sponsor bank doesn't run the technology stack — that's handled by a Banking-as-a-Service (BaaS) platform sitting in between. The card that was compromised was issued through a program manager. The transaction that moved the money ran over a card network and a processor neither the customer nor, often, the fintech's own support team has direct visibility into.Now ask the obvious question: whose fraud loss is this?In a traditional bank, the answer is uncomfortable but at least clear — it's the bank's, full stop, because the bank is the only regulated entity in the relationship and the customer's contract is with no one else. In a BaaS stack, the honest answer is: it depends on the contract, it depends on which party had operational control at the moment of failure, and in a meaningful share of cases, it depends on who blinks first in the dispute. That's not a regulatory framework. That's a negotiation.This is one of the more uncomfortable open questions in modern financial infrastructure, and it's worth examining directly, because every month that it stays unanswered, more transaction volume flows through stacks where the question hasn't been settled.<h2 class="heading-node" id="7lr4v0tra">The Stack: More Parties Than the Customer Ever Sees</h2>A typical BaaS arrangement for a consumer neobank or embedded finance product involves, at minimum:<ul class="list-node" id="qyifg25jq"><li>The sponsor bank — the regulated, licensed entity whose charter underpins the whole arrangement, legally the entity "providing" the financial service</li><li>The BaaS/infrastructure platform — the technology layer that provides APIs, core banking rails, card issuing processing, ledgering, and often the actual fraud and risk tooling</li><li>The program manager or fintech — the brand the customer actually sees and trusts, who designed the product experience and owns the customer relationship</li><li>The card network — Visa, Mastercard, RuPay, or equivalent, which has its own rulebook on chargeback liability</li><li>The processor — handling authorization and settlement, sometimes a separate entity from the BaaS platform</li><li>Downstream service providers — KYC/identity verification vendors, fraud scoring vendors, dispute management vendors — each potentially a different company again</li></ul>A customer onboarding into this product has a relationship with the fintech brand. Legally, their account is with the sponsor bank. Operationally, their transaction data, fraud scoring, and dispute workflows run through the BaaS platform. None of these three — brand, license holder, and infrastructure operator — necessarily has full visibility into what the other two are doing at the moment a fraud event occurs.This isn't a hypothetical structure drawn up for the sake of argument. It's the default architecture of embedded finance today, in India under the NBFC-fintech co-lending and PPI issuance models, in the US under the sponsor-bank model that's powered most neobanks and embedded finance launches of the last decade, and increasingly across Southeast Asia, the GCC, and Africa as digital-first banking licenses proliferate. The question of who owns fraud risk isn't a corner case. It's the central unresolved question of the entire BaaS category.<h2 class="heading-node" id="jr3nukzcb">Why "The Contract Decides" Isn't a Satisfying Answer</h2>The reflexive answer from most legal and commercial teams is that the contracts between these parties allocate liability, and in a narrow sense, that's true — most BaaS and program agreements do contain indemnification clauses, loss-sharing formulas, and service-level commitments that assign financial responsibility for different fraud scenarios.But this answer breaks down in practice for three reasons.First, contracts are written before the fraud happens, and fraud typologies evolve faster than contract renegotiation cycles. A loss-sharing clause drafted around card-not-present fraud risk in 2022 may say nothing coherent about a 2026 scam where the customer is socially engineered into authorizing their own transaction, moved through a mule account the sponsor bank's own compliance team should arguably have flagged, using a device fingerprint the BaaS platform's fraud engine scored as "unusual" but didn't block. Which clause governs that? Often, none cleanly does — and the parties end up negotiating the specific incident rather than applying a pre-agreed formula.Second, contractual liability and operational control frequently don't line up. The sponsor bank may be contractually on the hook for a category of loss, but the fraud model that failed to catch it was built, tuned, and operated entirely by the BaaS platform, with the bank having limited visibility into its thresholds or decisioning logic. Conversely, the fintech brand — the party the customer trusts and who designed the user experience that may have made the scam more or less likely to succeed — often carries little to no direct financial liability at all, because they're not a regulated entity and their contract with the sponsor bank was deliberately structured to limit their exposure. The party with the most contractual liability is not always the party with the most operational ability to have prevented the loss, and that mismatch is exactly why these disputes drag on.Third, regulators have not caught up to the structure. Most financial regulation — in the US, India, the EU, and most of APAC and MEA — was written with a bilateral mental model: one regulated institution, one customer, one relationship. Outsourcing and third-party risk guidelines (RBI's guidelines on outsourcing of financial services, the EBA's guidelines on outsourcing arrangements, the US OCC and FDIC's third-party risk management guidance) all gesture at the idea that the regulated entity remains accountable for outsourced functions — but "remains accountable" is a supervisory statement about who the regulator will come after, not an operational answer to who absorbs the loss, who built the control that failed, or how four or five companies should coordinate incident response in real time during an active fraud event. The regulatory answer and the commercial answer are different documents, written by different people, for different purposes, and they often don't reconcile cleanly.<h2 class="heading-node" id="xpjxeb4hj">A Concrete Scenario Worth Walking Through</h2>Consider a realistic case: a customer of a BaaS-powered neobank falls victim to a phishing scam and is tricked into authorizing a push payment to a mule account. The transaction passes SCA-equivalent authentication because the customer, under the scammer's instruction, approves it themselves. It passes the fraud model's real-time scoring because the device, location, and amount are all consistent with the customer's normal behavior — the only anomaly is the payee, which was flagged as "new" but not blocked, per the risk threshold the BaaS platform configured by default.Now trace the aftermath:<ul class="list-node" id="y0z893cgh"><li>The fintech brand fields the customer's complaint first, because that's the app the customer opened. It has no direct mechanism to reverse the transaction and limited visibility into the fraud model's decisioning.</li><li>The sponsor bank is the regulated entity responsible for the account and, in most jurisdictions, is the party a regulator or ombudsman will ultimately hold accountable for customer treatment — but it likely didn't configure the specific payee-risk threshold that let the transaction through.</li><li>The BaaS platform owns and operates the fraud model, and may have offered a stricter threshold as a configurable option — one the program never enabled, whether due to cost, conversion-rate concerns, or simply not being flagged as a priority during onboarding.</li><li>The card network or payment rail, if involved, has its own dispute rules, which may or may not cover authorized-but-coerced transactions at all — most do not, by design, since the customer genuinely authorized the payment.</li></ul>Every party in this chain has a partially valid claim that the loss isn't "theirs" alone, and every party also had some sliver of ability to have prevented it. This is precisely why these disputes are frequently resolved through negotiation, internal write-offs, or — worst of all — simply left unresolved, with the customer absorbing the loss because no single party accepts full ownership quickly enough to make them whole.<h2 class="heading-node" id="4cb6t7ab8">Three Structural Reasons This Keeps Happening</h2>1. BaaS is multi-party by design, and no single party owns the full transaction lifecycle. This isn't a bug to be patched — it's the entire value proposition of the model. A bank gets distribution without building consumer product. A fintech gets a banking license without becoming a bank. A BaaS platform monetizes infrastructure instead of owning customer relationships. That division of labor is exactly what makes embedded finance commercially viable — but it also means the full transaction lifecycle, end to end, isn't visible to or controlled by any single entity, which is precisely the condition that makes fraud liability so hard to assign cleanly.2. Regulatory frameworks still presume a bilateral relationship. Virtually every consumer protection and fraud liability regulation on the books — whether it's Regulation E in the US, RBI's customer liability circulars in India, or PSD2/PSD3's liability provisions in the EU — was drafted assuming the customer's financial institution is a single, identifiable, directly accountable entity. These frameworks are only slowly being updated to contemplate multi-party technology stacks, and in the meantime, the gap gets filled by private contracts that were never designed to do the job regulation is supposed to do.3. Commercial incentives push liability downstream rather than toward the party best positioned to prevent the loss. In commercial negotiations between banks, BaaS platforms, and fintechs, liability allocation is a point of leverage, not a principled design exercise. The party with the most negotiating power — frequently the sponsor bank, given its licensing position — tends to push liability toward the parties with less leverage, regardless of which party actually controls the systems that could have prevented the fraud. This produces contracts that are internally consistent and legally enforceable, but structurally disconnected from where operational risk actually sits.<h2 class="heading-node" id="v4aptyex9">What a More Defensible Model Looks Like</h2>None of this means the problem is unsolvable — it means it hasn't been treated as a design question with the seriousness it deserves. A few principles point toward a more defensible structure:Liability should be mapped to operational control, stage by stage. Rather than a single blanket liability clause, BaaS agreements need granular control-mapping: who configures authentication thresholds, who owns fraud model tuning, who monitors real-time alerts, who has authority to freeze a suspicious transaction before settlement. Liability for a given failure mode should sit primarily with whoever had the operational ability to prevent it — not whoever has the weakest negotiating position.Shared, real-time fraud visibility has to replace siloed dashboards. A meaningful share of these disputes exist because the bank, the fintech, and the BaaS platform are each looking at partial data after the fact. A fraud and risk management layer built for multi-party visibility — where the sponsor bank, the program manager, and the infrastructure platform see the same transaction-level risk signals in real time, not reconstructed after a complaint — removes much of the ambiguity about who knew what, when.Incident response needs a predefined, cross-party playbook, not an improvised negotiation. When a scam or account takeover is detected, the question of who freezes funds, who notifies the customer, and who initiates recovery shouldn't be settled contract-clause-by-contract-clause during the incident itself. The institutions handling this well have pre-agreed, tested incident response protocols that span all parties in the stack, triggered automatically by defined fraud signals.Regulators and industry bodies need to keep building multi-party liability guidance, not just bilateral frameworks. Some progress is visible — the UK's Confirmation of Payee and APP fraud reimbursement rules under the PSR, and evolving guidance from US regulators following several high-profile bank-fintech partnership failures, both represent early attempts to address multi-party accountability directly. APAC and MEA regulators drafting open banking and BaaS-specific frameworks have a real opportunity to build this in from the start rather than retrofitting it later.<h2 class="heading-node" id="3weu95n7b">The Bottom Line</h2>The honest answer to "who owns fraud risk in a shared BaaS stack" today is: it's split across several parties, unevenly, inconsistently, and in ways that frequently don't match who actually had the ability to prevent the loss. That's not a satisfying answer, but it's the accurate one, and pretending otherwise — treating a signed indemnification clause as if it resolves the operational question — is exactly how these disputes end up taking months to settle while customers wait for resolution.Getting this right isn't primarily a legal exercise. It's an infrastructure exercise. The institutions that will handle this well are the ones that build — or partner for — fraud and risk systems designed from the outset for multi-party visibility and clear, stage-by-stage control mapping, rather than treating shared liability as something to be resolved after the fact through negotiation.If you're a bank, fintech, or program manager operating in a BaaS stack and this question has come up in a real dispute rather than a hypothetical one, it's worth examining whether your fraud and risk infrastructure actually supports shared visibility and clear control attribution — or whether it's quietly assuming the bilateral model that regulation was built around. <a class="link" href="https://m2pfintech.com/frm-aml/?utm_source=blg&amp;utm_medium=frm&amp;utm_campaign=oct" target="_blank">M2P's FRM</a> system is built for exactly this multi-party reality, giving every party in a BaaS stack visibility into the same transaction-level risk signals rather than reconstructing them after a dispute. If this is a live question for your organization, <a class="link" href="https://m2pfintech.com/contact-us/?utm_source=blg&amp;utm_medium=frm&amp;utm_campaign=oct" target="_blank">reach out to M2P</a> to talk through what a clearer ownership model could look like for your stack.

Who Owns Fraud Risk in a Shared Banking-as-a-Service Stack — and Why Nobody's Really Answered This Yet

<img src="https://m2p-website-file.s3.ap-south-1.amazonaws.com/marketing-cms/m2p-blog/2026/09/paisaback_m2p_blog_v8_2000x1000.webp" alt="M2P Powers Federal Bank Paisaback Co-Branded Credit Card" title="" id="azfbg8gmd" width="100%" height="451"><a class="link" href="https://m2pfintech.com/" target="_blank">M2P Fintech</a> is powering Paisaback, the co-branded credit card launched by <a class="link" href="https://timesofindia.indiatimes.com/business/india-business/federal-bank-paisabazaar-launch-paisaback-credit-card-with-7-5-cashback-on-grocery-spends/articleshow/134061265.cms" target="_blank">Federal Bank in partnership with Paisabazaar</a>. The card runs on <a class="link" href="https://m2pfintech.com/credit-cards/" target="_blank">M2P's Credit Card Stack</a>, which handles everything from issuance and day-to-day card management to the cashback at the heart of the product.The idea behind <a class="link" href="https://www.paisabazaar.com/federal-bank/paisabazaar-paisaback-credit-card/" target="_blank">Paisaback</a> is simple. Most people want a credit card that pays them back on what they already spend, without having to learn a points system or wait on a redemption catalogue. Paisaback does exactly that, offering cashback across everyday spend categories, including a distinctive cashback on everyday transactions made using the credit card. With UPI now the way so many Indians pay, from the neighbourhood grocer to monthly bills, rewarding those payments makes the card useful in the moments that matter most.Getting a proposition like this to market quickly takes more than a good idea. It needs a card platform that adapts to the product, not the other way round. That is where <a class="link" href="https://m2pfintech.com/blog/why-switch-to-a-new-age-credit-card-system/" target="_blank">M2P's Credit Card Management System</a> comes in. It manages the full life of a card, from onboarding the customer and issuing the card to setting credit limits, authorising transactions, generating statements and processing repayments. Just as importantly, M2P's Credit Card Management System can be configured quickly to support differentiated product constructs like this one. That flexibility lets issuers design card propositions for different customer segments and interests, and bring them to market faster. For Paisaback, it meant a fast launch and a platform ready to grow with the program.<a class="link" href="https://m2pfintech.com/blog/6-reasons-cards-issuers-need-modern-api-based-platform/" target="_blank">APIs</a> sit at the heart of the stack, which lets it connect smoothly with a partner's digital journeys. Customers can discover the card, apply for it and manage it through channels they already know and trust, which is exactly what a digital-first co-branded card needs.The cashback itself is delivered through <a class="link" href="https://m2pfintech.com/rewards/" target="_blank">M2P's Rewards platform</a>, working hand in hand with the <a class="link" href="https://m2pfintech.com/blog/what-is-a-card-management-system-the-complete-guide-to-modern-card-issuance-2026/" target="_blank">Credit Card Management System</a>. The rules engine decides how cashback is earned, whether by spend category, merchant, payment type such as UPI, spend thresholds or monthly caps. As transactions come through, rewards are worked out accurately and credited transparently, so customers can clearly see the value they are getting. For the issuer, the same platform makes it easy to fine-tune the program over time, whether that means running a festive offer, adding a partner campaign or shifting focus to a new spend category, all without touching the core card platform. Behind every swipe, UPI payment and cashback credit sits a set of transactions that must be matched and settled accurately. This is where <a class="link" href="https://m2pfintech.com/recon360/" target="_blank">M2P's reconciliation</a> product completes the stack. It automates the back-office work of matching transaction records across networks, processors and the bank's ledgers, and flags exceptions early so they can be resolved quickly. For a program like Paisaback, that means fewer manual checks, cleaner books and greater confidence as transaction volumes grow.<a class="link" href="https://m2pfintech.com/blog/why-co-branded-credit-cards-are-the-next-frontier-for-banks/" target="_blank">Co-branded cards</a> work best when the value is easy for customers to understand and the technology behind them is easy for issuers to shape. Paisaback is a great example of that. Paisabazaar knows what today's credit customers are looking for, and our role has been to give that insight a platform that can launch quickly and scale with confidence. We're excited to be part of this journey.Paisaback brings together three strengths. <a class="link" href="https://www.federal.bank.in/" target="_blank">Federal Bank</a> contributes its banking franchise and credit card expertise, Paisabazaar brings its deep understanding of consumer credit needs and wide digital reach, and M2P provides the technology that ties it all together. The result is a card that is simple, rewarding and digital-first.M2P Fintech looks forward to supporting Federal Bank and Paisabazaar as Paisaback continues to grow, and to enabling more innovative credit experiences across the BFSI sector.

Product

About

Compliance

Resources