Personalized Lifestyle Marketplace

Enterprises face multiple challenges in driving customer engagement • Unable to identify merchants in transaction data Data • Unable to enrich transaction data with external data • Do not have a 360-degree view of a customer Head of • Unable to uncover customer’s lifestyle tastesPortfolio Algos • Unable to target customers with 1:1 recommendations • Unable to refine recommendations in real-time based on digital behavior (like/dislike) Experience • Experience spread across the multiple digital assets, no unified journey. Partnerships • Onboarding offer merchants is not digital and is time consuming • Existing merchant partners who provide offers see limited traction

Proposed Solution:

maya.ai can deliver a Personalized Lifestyle Marketplace to drive customer engagement • Unable to identify merchants in transaction data Ingests, cleans, enriches Enterprise • Unable to enrich transaction data with external Data as a Service data transaction data and creation a customer • Do not have a 360-degree view of a customer taste print • Unable to uncover customer’s lifestyle tastes • Unable to target customers with 1:1 Recommendation as a Generates 1:1 recommendations that match recommendations Service customers with lifestyle merchants, offers • Unable to refine recommendations in real-time based on digital behavior (like/dislike) • Onboarding offer merchants is not digital and is Marketplace Connects Enterprises to an ecosystem of time consuming as a Service merchants • Existing merchant partners who provide offers see limited traction Customer Experience Enables consumer engagement through • Experience spread across the multiple digital as a Service white-labeled apps, widgets and/or on assets, no unified journey. Enterprise digital assets

Web Experience

Mobile Experience

Illustration of Customer Journey

1 VIEW PERSONALIZED OFFERS

Sample customer journey Customer receives Clicks on notification. Views Wishlists notification for visiting Lands on personalized personalized offers Personalized Storefront storefront offers Claims Offers refreshed Likes / dislikes Searches for offers offer based on feedback offers using keyword

CX Journeys powered by maya.ai 1 View personalized offers 2 View wishlisted offers 3 Search offers by keyword 4 Claim online offers 5 Claim offline offers 6 View claimed offers

Homepageofstorefrontshowspersonalized offers View Wishlisted Offers Keyword Search Live campaigns Personalized User experience can be Hyperlocal Offers customized as per Bank’s brand guidelines and requirements Personalized Online Offers that are expiring soon

2 VIEW WISHLISTED OFFERS

Wishlisted offers page

3 SEARCH BY KEYWORD

“Search bar” where one can type keywords

“Search result page” showing offers based on keyword searched

4 CLAIM ONLINE OFFERS

5 CLAIM OFFLINE OFFERS

6 VIEW CLAIMED OFFERS

“Claimed offers page” showing list of offers claimed

COLD START PERSONALIZATION

In the absence of customer transaction data, maya.ai can also provide cold-start personalization Recommend popular, trending offers and improve recommendations based on customer’s interactions

Differentiation

The only full stack solution in the market; adds value across data, algos, apps, marketplace layers Clean transaction data + relevant external data (Taste Graph - data on 7.5Mn merchants) Patented AI/ML models to uncover customer’s lifestyle preferences APIs + White-labeled Apps, widgets to power experiences in real-time based on preferences and context Ecosystem of partners to serve customers across lifestyle categories (i.e. dining, retail, travel, apparel, etc..)

KPIs Impacted

maya.ai personalized lifestyle marketplace solution will impact the following metrics • More active customers • Incremental spends • Higher digital engagement • Reduced attrition • Reduced time to onboard merchant • More engaged merchants • NEW: Affiliate income from merchants

Solution components

maya.ai modules can enable Banks to deliver personalized lifestyle marketplaces maya.ai Customers visit the bank’s website/app, browse Data As a Service (DaaS) ingests Bank’s through the offers and redeems them transaction data and enriches it with external data to understand lifestyle preferences Bank shares required transaction data sets Marketplace as a Service (MaaS) provides supply of merchant and offer inventory - dining, apparel, travel, retail, etc.. Recommendation as a Service (RaaS) matches customer's preferences with lifestyle inventory and creates personalized offer recommendations for every customer Customer Experience As a Service (CXaaS) provides a front-end to show the recommendations which can Bank notifies customers be integrated on bank’s website/app about the marketplace on Email, SMS, Notifications

The solution covers the following components. Consumer App Merchant Studio Merchant Supply Shows personalized offers Enables Merchant & Offer onboarding Add relevant merchants to portfolio Page Features Page Features Category Merchants Offers Login Screen Personalized URL Login Screen Login in via OTP Retail 200 400 Guest Login Login with password Travel 1550 1650 Login by Phone Number Add Merchant Profile Home Page Personalized Campaigns Page Business Details Apparel 100 350 Hyper-Location Offer Recommendations Product Catalogue Dining (F & B) 300 400 Keyword Based Search Settings Entertainment 200 250 Recommendations based on preferences Privacy Policy Merchant Page Merchant Description & Logo Terms & Conditions Merchant Affinity Score Add Offer Page Offer Description & creative Reasoning for Recommendations Channels – Online, Offline, Both Offer Description & Logo Payment –Regular, EMI Offer Terms & Conditions Redemption Options Offer Redemption Target Categories Category Page Recommendations offers in category based Custom Rules on preferences Terms & Conditions Search Results Page Recommendations matching search criteria View Offers Page Offer ID, Description Wishlist Page View Wishlisted offers Status Accounts Page View Claimed Offers State Date, End Date View Redemptions Channels Provide App Feedback FAQ Privacy Policy Terms & Conditions

Deployment Options Components Details Add-Ons Details Cloud AWS or Azure Card Network VISA + MASTERCARD offers for the Transaction Data Extraction from source systems Offers region Campaign APIs across Email, SMS, Push Financial APIs for integrating with existing notification Product Bank products which have digital Digital Asset APIs across Website, Mobile App fulfilment Loyalty APIs for integrating with existing Program Bank loyalty program *Any API integration will be charged separately

White labelling and customizations The Personalized Lifestyle Marketplace is available for white labelling and additional customizations • Branding and logos: Apply brand names, colours, and logos according to your style guide • UI: Choose from a set of standard layouts and cards, or customize your own • Typography: Font selection • Product writing: Category names, list names, and more • Privacy Policy and Terms & Conditions: Align with internal privacy policies and terms & conditions

Required Data

maya.ai needs the following data sets for delivering a Personalized Lifestyle Marketplace Customers Transactions Card Products Offers Digital Data customer_id (masked) tran_id customer_id (masked) offer_id user_IP mar_status tran_datetime card_id (masked) offer_name customer_id (masked) gender tran_amount cr_lim_group offer_start_date Session Date nationality tran_description card_product offer_end_date Session Start Time cr_lim card_type card_status merchant_name Session End Time email_flag issuer_type create_date dnd_flag merchant_code primary_secondary_flag Merchant_description CookieID sms_flag merchant_name product_name Product ID interacted with cc_type merchant_city offer_type Interaction Type salary_bin merchant_country Merchants offer_category customer_segment customer_id (masked) offer_redemptioncode customer_segment merchant_id offer_locations Campaigns age product_id merchant_name customer_from product_category merchant_category offer_link customer_id (masked) zipcode/City mcc_code address offer_t&Cs campaign date points_balance tran_terminal_id contact_no offer_img_urls campaign_id tran_geocode channel card_id (masked) zipcode deliver_date points_earned geocode open_date click_date points_used mcc_code view_date settlement_date tran_type merchant_tags tran_code tran_ecom_flag Mandatory Optional

Process flow – Data Transfer Mechanismswith Crayon Raw data transfer from Enterprise to Crayon Cloud Processed recommendation data transfer from Crayon Cloud to Enterprise SFTP • Enterprise can extract data from their DB and transfer via SFTP Email & SMS • Crayon can deliver batch files via SFTP • Crayon can help automate this Campaigns • Crayon can expose an API that the Enterprise can call from within their environment API • If Enterprise has built an API to transfer • Crayon can integrate with the Email and/or data, Crayon can call it SMS execution engine and pass the data directly to that system Engage App, • One time integration of Widget or API with Integration • Crayon can integrate with Enterprise’s data Widget & API Enterprise’s digital asset. to Data lake lake or extract from Azure blob link or S3 • Once this is done data exchange will be real- storage and pull the data. time and continuous i.e. no manual • Enterprise will need to give Crayon intervention needed after one-time permission to access the data and write the integration data extraction jobs

How Enterprises anonymize/mask data before sharing it with Crayon Transaction Data Customer ID Merchant Name Card Number Date Amount Enterprise has PII data in 171127 The Educated Pot 4850909284846029 25-03-2021 35.08 its data lake 171128 The Hidden Chariot 9840203948230982 25-03-2021 3.91 171126 The Thunder Plum 8347104982344983 25-03-2021 4.84 171125 The Smelly Growth 1458710875243090 25-03-2021 23.95 Customer Id Mapping Card Number Mapping Enterprise creates Customer ID Masked Customer ID Card Number Masked Card Number anonymized data using 171125 b09c16fcd90889cfdaa59ac9ac76894e 1458710875243090 75284494dd043356b727de882fea084a Hashing Algorithms 171126 bcb39d95c667faa134415186c0e8fbdf 8347104982344983 b4991fc9706f9a71dd40cd1856822b22 (For example, using MD5) 171127 8e69f6b56f0905a684f20c8ad4f2e702 4850909284846029 dc0a6d660cdd3216c546420095130ce7 171128 043f134b2b9469d5e08d8780047bab41 9840203948230982 a2d9dc79b1a280ee01e921af26b492be These mapping tables can be stored in the Enterprise’s data lake Masked Transaction Data Masked Customer ID Merchant Name Masked Card Number Date Amount Enterprise shares 8e69f6b56f0905a684f20c8ad4f2e702 The Educated Pot dc0a6d660cdd3216c546420095130ce7 25-03-2021 35.08 anonymized data (No PII) 043f134b2b9469d5e08d8780047bab41 The Hidden Chariot a2d9dc79b1a280ee01e921af26b492be 25-03-2021 3.91 with Crayon bcb39d95c667faa134415186c0e8fbdf The Thunder Plum b4991fc9706f9a71dd40cd1856822b22 25-03-2021 4.84 b09c16fcd90889cfdaa59ac9ac76894e The Smelly Growth 75284494dd043356b727de882fea084a 25-03-2021 23.95 Crayon can enable the Enterprise to mask the data

Technical Architecture

maya.ai automates multiple, complex, silo-ed manual enterprise processes needed to deliver engaging customer experiences 1 Share Data 2 Ingest Data 3 Clean Data 4 Enrich Data Enterprise Data Crayon Secure Merchant Data Cleaning Enrichment Crayon External data (Taste, (no PII) ISO27001 Cloud & de-duplication influence, context) + Supply Of Offers Enterprise transfers anonymized data via Team of 3-4 analysts Limited external data, if any. SFTP, APIs or Crayon writes data extraction working for weeks to Limited supply of merchants, jobs to pull the data clean 1mn rows offers. Procurement and internal approvals Enterprise Without maya.ai Recommendations shown on Enterprise’s Digital Assets or Crayon’s white labeled Limited iteration and self-learning Data scientists working with Business App/Widget capabilities. Refresh of models happens teams to develop models. infrequently Campaign planning ~5-10 days Email Widget SMS White Labeled Rank ordered Recommendations Algorithm, model self Modeling on internal API http:// App generated optimization Behavioral data 7 View recommendations on 6 Generate and refine the recommendations 5 Run Algos for different use digital channels cases

Technology stack that powers maya.ai’s capabilities Enterprise’s Cloud Azure Real Time Data Visualization Layer Data Sources Feed Daily Dashboard ü APIs/ Widget/ White-labelled Insights assets Azure Event ü Taste Graphs Offers Txn Tracking Custom Hub Connectors Taste AI Studio Engage Studio Data Ingestion Studio DWH CRM … Layer Data Query Layer Crayon Analytics Layer Enterprise Data Hadoop SQL DW Spark / Streaming Offers, curated content Partner data Data Processing Layer SFTP Access Control Meta Data Management Unstructured data, Blogs, Reviews Data Lake Internet data Daily Batch Feed Crayon Data AI/ML Driven Platform

maya.ai – solution architecture Open API. Easy Configuration. Plug n Play Customer Experience as a Service Retail Bazaar Trigger & Context based recos B2B predictive marketplace Consumer Merchant Enterprise Mobile lifestyle apps apps assets banking apps Category Experiences incl. Travel P2P & P2M payments Upsell/x-sell recommendations (web/mobile) Dashboards Wallets Custom apps Use cases & Territory Management Customer loyalty management +++ Interfaces experiences Cognitive BIM API Partner Vendor Inventory Agent Taste API Engage Results Lists API Payments Merchant Cashback API API API API API API API s API API APIs +++ Territory Search Product Destinatio Insights Genome Interactio User API Itinerary Affiliate Offers API Fulfilment API API API n API API API n API API API API Data as a Service Recommendation as a Service Marketplace as a Service API extraction User-centric data lake to power automation experience-oriented solutions Patented TasteGraph Patented Choice AI Global Products Global Enterprise Algorithms algorithms Repository Repository Entity standardization & disambiguation Operations & business-centric Distributed data data lake to deliver 50+ SOTA & out-of-box algorithms Global Merchant movement optimization-oriented solutions Repository rd rd Enterprise Transaction CRM 3 Party 3 Party System Merchant Data Data Partner Enrichment Integrations data Systems Systems Integrations Data Offer Merchant Core Repository Details Communication E-Wallet Identity rd Systems +++ 3 party APIs +++ banking platform verification system Infrastructure & Integrations

Solution deployment on AWS

Solution deployment on Azure

Security

Deployment ensures maximum security for enterprise data Crayon follows Defense in Depth approach which includes ü Compliant to regulatory standards - CIS, SOC TSP, PCI DSS (Azure) and ISO 27001 (Crayon). ü Components hosted in private zone behind Azure Firewall. ü Encryption of Data at Rest & Transit across components. ü Web Application Firewall (WAF) with OWASP Standard protection for externally exposed endpoints. ü Protection against malwares by enterprise standard Trend Micro Deep Security Tool. ü RegularVulnerability Scanning by third party auditors (Qualys) ü Penetration Testing of external endpoints at regular intervals. ü Real time monitoring and Incident Alerting mechanism

Support Needed

Enterprise to provide minimal support to aid deployment Category Collaborative Support • Share anonymized transaction data (No PII) of complete credit card customer base Data with 12 months transaction history • Setup regular data refresh cadence (daily/weekly/monthly) People • Dedicated single point of contact for successful project execution • Applicable approvals/sign offs to be provided in the agreed timelines in order to Approvals proceed with every phase of the project Campaigns • Timely launch of campaigns for driving traffic to marketplace

Commercial Model

Commercial Model Module Base Annual Fee* AnnualSubscription** Professional Services*** Data as a Service $ A N/A At actuals for any custom requirements (DaaS) Customer Experience as a $ B N/A At actuals for custom requirements (country Service specific requirements, integrations to 3rd party (CXaaS) platforms, Data enrichment, UX modifications etc) Marketplace as a service $ C Tiered Pricing based on merchants onboarded (MaaS) on the platforms Recommendation as a Service $ D Tiered Pricing based on customer base (RaaS) onboarded on the platforms Affiliate Revenue Split Between To Be Agreed Enterprise and Crayon Data *Base Annual Fee • will be the minimum annual price for the modules that are part of the proposal. • This caters or allows Enterprise to onboard up to 100K customers. • This is applicable to every new instance of the platform that will be set up for Enterprise. ** Yearly Subscription • Based on tiered pricing and will be in effect once Enterprise onboards more than 100K customers. *** Professional Services • Will be estimated based on scope of work and charged at actuals for all custom services requested including but not limited to rd integrations to 3 party platforms, country specific requirements, compliance related requirements etc.