United States Securities and Exchange Commission Washington, D.C. 20549 FORM 6-K REPORT OF FOREIGN PRIVATE ISSUER PURSUANT TO RULE 13a-16 OR 15d-16 UNDER THE SECURITIES EXCHANGE ACT OF 1934 For the month of May 2024 Commission File Number 132-02847 INTER & Co, INC. (Exact name of registrant as specified in its charter) N/A (Translation of Registrant’s executive offices) Av Barbacena, 1.219, 22nd Floor Belo Horizonte, Brazil, ZIP Code 30 190-131 Telephone: +55 (31) 2138-7978 (Address of principal executive office) Indicate by check mark whether the registrant files or will file annual reports under cover of Form 20-F or Form 40-F. Form 20-F ☒ Form 40-F ☐ Indicate by check mark if the registrant is submitting the Form 6-K in paper as permitted by Regulation S-T Rule 101(b)(1): Yes ☐ No ☒ Indicate by check mark if the registrant is submitting the Form 6-K in paper as permitted by Regulation S-T Rule 101(b)(7): Yes ☐ No ☒
1 TechDay
E A R N I N G S P R E S E N T A T I O N | 1 Q 2 4 Disclaimer This report may contain forward-looking statements regarding Inter, anticipated synergies, growth plans, projected results and future strategies. While these forward-looking statements reflect our Management’s good faith beliefs, they involve known and unknown risks and uncertainties that could cause the company’s results or accrued results to differ materially from those anticipated and discussed herein. These statements are not guarantees of future performance. These risks and uncertainties include, but are not limited to, our ability to realize the amount of projected synergies and the projected schedule, in addition to economic, competitive, governmental and technological factors affecting Inter, the markets, products and prices and other factors. In addition, this presentation contains managerial numbers that may differ from those presented in our financial statements. The calculation methodology for these managerial numbers is presented in Inter’s quarterly earnings release. Statements contained in this report that are not facts or historical information may be forward-looking statements under the terms of the Private Securities Litigation Reform Act of 1995. These forward-looking statements may, among other things, beliefs related to the creation of value and any other statements regarding Inter. In some cases, terms such as “estimate”, “project”, “predict”, “plan”, “believe”, “can”, “expectation”, “anticipate”, “intend”, “aimed”, “potential”, “may”, “will/shall” and similar terms, or the negative of these expressions, may identify forward looking statements. These forward-looking statements are based on Inter's expectations and beliefs about future events and involve risks and uncertainties that could cause actual results to differ materially from current ones. Any forward-looking statement made by us in this document is based only on information currently available to us and speaks only as of the date on which it is made. We undertake no obligation to publicly update any forward-looking statement, whether written or oral, that may be made from time to time, whether as a result of new information, future developments or otherwise. For additional information that about factors that may lead to results that are different from our estimates, please refer to sections “Cautionary Statement Concerning Forward- Looking Statements” and “Risk Factors” of Inter&Co Annual Report on Form 20-F. The numbers for our key metrics (Unit Economics), which include active users, as average revenue per active client (ARPAC), cost to serve (CTS), are calculated using Inter’s internal data. Although we believe these metrics are based on reasonable estimates, but there are challenges inherent in measuring the use of our business. In addition, we continually seek to improve our estimates, which may change due to improvements or changes in methodology, in processes for calculating these metrics and, from time to time, we may discover inaccuracies and make adjustments to improve accuracy, including adjustments that may result in recalculating our historical metrics. About Non-IFRS Financial Measures To supplement the financial measures presented in this press release and related conference call, presentation, or webcast in accordance with IFRS, Inter&Co also presents non-IFRS measures of financial performance, as highlighted throughout the documents. The non-IFRS Financial Measures include, among others: Adjusted Net Income, Cost to Serve, Cost of Funding, Efficiency Ratio, Underwriting, NPL > 90 days, NPL 15 to 90 days, NPL and Stage 3 Formation, Cost of Risk, Coverage Ratio, Funding, All-in Cost of Funding, Gross Merchandise Volume (GMV), Premiuns, Net Inflows, Global Services Deposits and Investments, Fee Income Ratio, Client Acquisition Cost, Cards+PIX TPV, Gross ARPAC, Net ARPAC, Marginal NIM 1.0, Marginal NIM 2.0, Net Interest Margin IEP + Non-int. CC Receivables (1.0), Net Interest Margin IEP (2.0), Cost-to-Serve, Risk-Adjusted Net Interest Margin IEP + Non-int. CC Receivables (1.0), Risk Adjusted Net Interest Margin IEP (2.0), Risk Adjusted Efficiency Ratio. A “non-IFRS financial measure” refers to a numerical measure of Inter&Co’s historical or financial position that either excludes or includes amounts that are not normally excluded or included in the most directly comparable measure calculated and presented in accordance with IFRS in Inter&Co’s financial statements. Inter&Co provides certain non-IFRS measures as additional information relating to its operating results as a complement to results provided in accordance with IFRS. The non-IFRS financial information presented herein should be considered together with, and not as a substitute for or superior to, the financial information presented in accordance with IFRS. There are significant limitations associated with the use of non-IFRS financial measures. Further, these measures may differ from the non-IFRS information, even where similarly titled, used by other companies and therefore should not be used to compare Inter&Co’s performance to that of other companies. 2
3 TechDay Agenda Vision CEO overview with João Vitor Foundation Our technology with Guilherme Ximenes Innovation Business cases with Alexandre Riccio Monetization Financial impacts with Santiago Stel Firechat Cocktail
4 The Vision João Vitor Menin | Inter&Co CEO
5 • What we built • Technology as the bedrock The vision
6 The vision Data centers Monolithic systems IT servers Wired connections Branches From
7 Cloud-based Digital Microservices Single App Simple To The vision
8 Cloud-based Digital Microservices Single App Simple To The vision What we built so far Through Technology Creativity People Innovation Data
9
10 What we built so far 124 app versions since 2015 +160x more data processing capability than 2015 2024 32MM clients 7 verticals
11 Enabling our operations to exceed expectations through 3 pillars: Technology as the bedrock of everything we do Scalability Acceleration Focus Combining Growth And Profitability Driven By Cost Efficiency Data-Based Business Model Providing Deeper and Faster Insights Highly Scalable and Extensible Deployment across Markets & Products
12 Technology as the bedrock of everything we do These foundations allowed us to be the 1st mover in several markets & Retail digital banking & Digital underwriting & Integrated Investments Platform & Integrated Insurance Platform & Integrated Marketplace & Integrated Global Account & Integrated Loyalty
13 Which product exemplifies the power our technology stack?
14 DEPOSITS Which product exemplifies the power our technology stack?
15 Which product exemplifies the power our technology stack? DEPOSITS
16 191’000 cash-in transactions1 per hour DEPOSITSWhich product exemplifies the power our technology stack? Note 1: Incoming resource transactions into Inter account, such as PIX, transfers, deposits and others.
17 17 Foundation Guilherme Ximenes | Inter&Co CTO
18 18 Strategic Use of Technology • Digital Transformation • Financial Super App • Proprietary Technologies • Data Platform + AI • Scaling Beyond Brazil • Gen AI Cases • Beyond The Horizon Foundation
19 Laying out the foundations Until 2018 Less scalable Slower process High dependency Computing restraints Legacy systems Rigid structure Cloud based infrastructure 2018 & beyond Automated process Scalable computing Time to market 1st bank in Latin America to operate 100% in the cloud1 DevOps Microservices+ +Data center On premisesWaterfall Monolithic+ +
20 Financial Super App: the visionary approach The Super App Launch Everything integrated in a Single App
21 100,000 requests per minute1 3rd party API Gateway 1 bottleneck Scaling from 1 million clients 4 million clients The problem and the opportunity to Note 1: Considering peak periods, such as the Inter Day campaign (07/07/2020).
22 Inter API Gateway The solution
23 ~6 months market median vs. ~15 days to create new features4 -95% Easy to EvolveRamp-up Speed Inter Gateway cost2 vs. 3rd Party Gateway cost2 Efficiency 1/10 of the cost USD 120’000 Inter Cost Inter API Gateway Performance 0.1 2 3rd Party Inter Inter Gateway’s capacity to process requests per minute1 In million 20x From 15 minutes to 1 second3 Time N um be r o f m ac hi ne s Designing the solution for the future Note 1: The performance index was calculated using current data from Inter Gateway and third party estimates from July 2020. Note 2: The third party cost was calculated considering the current licensing contract until 2023 and the improvements implemented between 2020 and 2022. The cost of Inter Gateway only includes computational power consumption. Values expressed in US dollars. Note 3: The availability time for receiving requests does not take into account the time required for infrastructure provisioning. Note 4: The calculation was based on the average number of requests received per day during the period.
24 Inter API Gateway Designing the solution for the future 0 1 Linear Exponential
25 Tailor-Made Super Fast to evolve Ultra-High Performance Cost Efficiency Unleashing an immense potential Inter Shop APIs Strong Authentication DevOps Pipe Digital Banking Core Pix Inter Freedom & speed to create and customize
26 15 million logins per day1 + 3,500 micro services2 Hundreds of Millions of interactions+ Note 1: The login volume used in this calculation is based on the average between May 5th, 2024 to May 10th, 2024. Note 2: The microservices used in this calculation are from the production environment of January 2024. Variety Volume Velocity Data becomes solid gold The 3V’s Everything, everywhere, all at once
27 Volume of data increased significantly Note 1: Stored data in AWS servers. 2020 +25 PB 2019 20232021 2022 0,1PB Data in our Data Lake In Petabytes Various types of storageExponencial growth 2024 Version 1 Version 2 Version 3
28 Dashboard Live moment
29 Time-to-insight2 Time taken to deploy a model AI: Empowering the existing data & creating more insights 68 day s 36 day s Quality + +Scale Flexibility Note 1: Internal models used across Inter&Co’s teams and processes. Note 2: Interviews were conducted with data scientists in July 2023, November 2023, and April 2024. These interviews covered steps such as setting up the environment, data cleaning and preparation, experiments, model development, deployment to production environment, and monitoring configuration. AI use cases across all business verticals Card Processing Comms Channels Next best offer Shopping Investment Clustering Favorite channel Churn avoidance ~80 AI models at scale now1 Credit risk Provision Income inference Pricing Anti Fraud AML Collection Credit card limits Offensive AI Defensive AI Baseline Today Future
30 ~30 AI touch points1 Geo Location4 Transaction Speed3 -68% -52%Face Recognition2 loss and theft claims6 (mar/23 - mar/24) financial fraud losses5 (2022 vs. 2023) Fraud Prevention AI: Empowering the existing data & creating value Note 1: 30 microservices that support the current AI models. Note 2: Implementation of selfie similarity validation and screen detection features to prevent account breaches. Note 3: Creation of unique behavioral models for each client aimed at detecting unusual movements. Note 4: Determination of secure transaction zones. Note 5: The decrease in book value between 2Q/23 and 1Q/24 represents fraud losses.
31 Scalable beyond Brazil New frontiers Same components Cloud Infrastructure Backend Systems User Experience Developers Team Highly scalable bussines model, from products to countries
32 Live logins Worldwide Live moment
33Note 1: Data points gathered in an unified internal data basis, which has client’s credentials and app usage. Cr os s & u p se lli ng ca pa bi lit y Data gathering+ Data gathering+ Data gathering+ Data gathering+ Data gathering+ Data gathering+Data gathering+ Open Account Geolocation Day to day banking usage Clicks and access behavior Time spent in a product or vertical Investments profile Client engagement Cards on and off Inter A unique and personalized version tailor-made for each client based on data +500 Data points gather per client in on average1 Insurance products Impressive capability for deep customer insights
34 Previous models Win OneBlack Digital 4 clusters Constant improvements in the journey 2018
35 Previous models Win One Black Digital Constant improvements in the journey Demographic Data 2020 To more than 80
36 Constant improvements in the journey Per cluster Per client Per context / client 2022 To Thousands From 80
37 From thousands to 1 personalized app tailor made for each customer Constant improvements in the journey Beyond
38 We are now unleashing the power of Gen AI AI Machine Learning Deep Learning Gen AI Again, being one of the early users of a new solution
39 Note 1: The implementation of Chat GPT by Open IA occurred in November 2022, while Inter GPT was implemented on March 10, 2024. Note 2: Interactions refer to each message responded by Inter GPT. 3 months1 For all Inter’s employees after Open Al launch Enhancing the power of our platform with Gen AI InterGPT was launched in Images generator Code Quality Ask HR CS Assistant Gen AI App Generator Legal Assistant New Gen AI tools 2024 Quantity of interactions2 with InterGPT +5x March 2023 25,000 August 2023 80,000 March 142,000 2024 +
40 Note 1: Gen AI assistant test made by a portion of the contact center team in October 2023. Note 2: Increase noticed at the same time as the Gen AI assistant was being tested in October. Contact center Summarizing 2,500 articles into a chat conversation From 18minutes To 14minutes1 using Gen AI Assistant ↑ 15% Customer Satisfaction3 Enhancing the power of our platform with Gen AI Average call time ↓-21%
41 Inter Gen AI at Scale Orchestration Layer Gen AI platform Prompt Eng. Services Client issues the command Optimizes the best models for the best outcomes Memory Services Data Lake Integration New Gen AI solution Propriatery Model Recover previous conversation Enriches responses from LLM Models with CUSTOMER DATA Context and guardrails to the conversation
42 Modern Apps Intelligent Apps Natural language interaction with GenAi Driven by data + Personalized experiences Next Chapter… Looking ahead Modern app development principles Rapid innovation with CI/CD Microservices-based architecture Pa ra di gm Sh ift
43 Exploring new opportunities to push the frontier, again Voice command Next chapter… Or the future could be…
44 Exploring new opportunities to push the frontier, again No need of smartphone Next chapter… Or the future could be…
45 Exploring new opportunities to push the frontier, again Predictive solutions? Next chapter… Or the future could be…
46 Exploring new opportunities to push the frontier, again Imagine everything together
47 We are looking beyond the horizon
48 Innovation Alexandre Riccio | SVP – Banking Rodrigo Gouveia | Inter Shop CEO
49 1 2 3 Credit Underwriting PIX Global Account Shopping 4 Business and IT together delivering results: 4 cases of success at Inter
50
51 Prioritizing the bestUX& products
52 Launching unsecured products BNPL Overdraft Withdrawal financing Bill pay financing PIX financing Launching Cashback CC Processor Launch 0.8 1.9 4.8 6.9 9.5 10.1 Gross Credit Card Portfolio In R$ Billion Scaling unsecured products Repricing the Portfolio Scaling CDB+Limite Offering Credit card on onboarding 2019 2020 2021 2022 2023 1Q24 +10X since 2020 Credit Underwriting: 0 to 1 approach to product development
53 1. Income Estimator 2. Onboarding Scoring 3. Behavior Scoring 4. Credit Limit Maintanance 5. Credit Collection Scoring 1. Income Estimator 2. Onboarding Scoring 3. Behavior Scoring 4. Credit Limit Maintenance 5. Credit Collection Scoring InterLake Data Marts Other S3 Bucket EC2 Instance Data + IT infrastructure AI Modeling Framework Credit Underwriting: mature set of models for consistent growth
54 8% PIX Market Share PIX: eliminating cash and revolutionizing payments
55 163 177 198 230 234 541 647 761 889 928 1 0 1 50 2 0 0 2 50 3 0 0 3 50 4 0 0 1Q23 2Q23 3Q23 4Q23 1Q24 Clients using PIX per day2 in Millions Number and Volume of PIX Transactions In million & in R$ billion R$ 6.7 bn Cash-In Balance1 3.1 4.9 April, 2023 April, 2024 487 PIX transactions per second April 5th, 2024 # of transactions (In MM, Monthly) TPV (In R$ Bn, monthly) Note 1: Difference between cash-in and cash-out transacted volume in 1Q24. Note 2: Unique clients. +44% YoY +72% YoY Record +37% YoY PIX: transactional banking at a scale never seen before
56 Service Quality Index (IQS)1 Monthly stability of PIX Peer 1 Peer 2 Peer 3 Peer 4 Peer 5 Peer 6 Months2 at Grade A 23 23 22 19 11 12 25 How? Most stable PIX in Brazil IQS Methodology Service Quality Index Complaints Availability Timeouts + + PIX: Inter establishing the industry benchmark
57 Cloud-Based Continuous Monitoring Independent Architecture Our Own Code and Solutions Preventive Routines Adaptive Architecture How? Most stable PIX in Brazil Faster and Independent Quick Reactive Responses Scalable and Stable PIX: capitalizing on experience to find the best solution
58 First ever e-commerce platform integrated into a bank in the Americas Banking Shopping Global Investments Loyalty Insurance Credit Inter Shop
59 Shopping Loyalty Travel Shell Box Connectivity Credit Digital Account Gift Card Insurance End to End Affiliates Integration is the key for the Shop success Inter Shop: integration unlocking value across the Financial Super App
60 Close Loop “On-Us” Processing = On-Us payments + Frictionless experience + Upsell options Banking Global Investments Insurance Credit Shopping Loyalty Inter Shop: integration driving efficiency
61 Debit Loop points Credit BNPL Flexible installments options Faster approval Higher control of payment flow On-Us Payments 37% 83% 63% 17% 2Q20 1Q24 On-us Off-us GMV1 In % Note 1: Gross merchandise value, or GMV, for a given period as the total value of all sales made or initiated through our Inter Shop platform managed by Inter Shop. On-us transactions defined as the “end-to-end” model. Inter Shop: integration generating revenue
62 Targeting better clients Customer Potential new customer Probability of buying Pr ob ab ili ty o f S pe nd in g H ig h 12 4 3 Lo w HighLow +40% average ticket1 AI Predictive Models Leads to Better Targeting & Omnichannel Leads to Better Communication = More Sales & Higher Revenue Using of AI propensity models Client 1 Client 2 ˜2x conversion rate2 Note 1: AI predictive models allow us to better target customers leading to a 40% increase on the average ticket. Note 2: AI predictive models allow us to better target customers leading to a 100% increase on the conversion rate. Inter Shop: AI models boosting better targeting and hyper personalization
63 Gen AI SHOP CONCIERGE Note 1: AI predictive models allow us to better target customers leading to a 40% increase on the average ticket. Note 2: AI predictive models allow us to better target customers leading to a 100% increase on the conversion rate. Inter Shop: Gen AI unlocking new possibilities
64 to Replication ˜3.0 3x million clients more product adoption Modularity Time-to-market Lower costs 0 to 5 verticals in less than 2 years Global Account: addressing market demand with a unique UX
65 One password. One Financial Super App. All solutions you need. Live moment
66 Monetization Santiago Stel | SVP - CFO
67 7 0 10 0 13 0 16 0 19 0 4Q21 1Q22 2Q22 3Q22 4Q22 1Q23 2Q23 3Q23 4Q23 1Q24 Net revenue1 Adm. & Personnel Expenses 114 119 115 137 140 158 172 179 193 100 89 89 95 108 96 91 98 100 101 7 0 10 0 13 0 16 0 19 0 4Q21 1Q22 2Q22 3Q22 4Q22 1Q23 2Q23 3Q23 4Q23 1Q24 1.9X Tech and innovation driving operational leverage Note 1: Net revenue = total net revenue - tax expenses. Validation of digital bank model Revenue vs. Expenses In %, index in a 100 basis
68 914 - 500 1,000 1,500 2,000 2,500 3,000 2020 1,702 2021 2,392 2022 2,413 2023 628 628 4Q23 1Q24 Expenses remaining flat since 2022 Optimizing our cost structure by embracing technology Boosting efficiency Note 1: SG&A Expenses consider personnel expenses, administrative expenses and depreciation and amortization. SG&A Expenses1 In R$ Million
69 25%, 229 26%, 443 31% 734 33% 791 75% 685 74% 1,258 69% 1,658 67% 1,622 914 1,702 2,392 2,413 2020 2021 2022 2023 Personnel Expenses Optimizing our spending in personnel expenses SG&A Expenses1 In R$ Million Note 1: SG&A Expenses consider personnel expenses, administrative expenses and depreciation and amortization.
70 +3X YoY And resulting in more productivity
71 Net Revenue per Employee1 In R$ Thousand Active Clients per Employee 1 Employee = 1Q24 ˜5.2 Thousand active clients + 1.5X YoY 475 532 812 1,334 - 200 400 600 800 1,000 1,200 1,400 2020 2021 2022 2023 And resulting in more productivity Note 1: Net revenue = total net revenue - tax expenses. +3X YoY
72 30% 37% 40% 40% 44% 28% 30% 32% 34% 36% 38% 40% 42% 44% 2020 2021 2022 2023 Apr-24 Tech Employees as % of Headcount1 In % Inspiring innovative thinking Headcount increasingly more tech-based Note 1: Tech employees include IT employees and employees with technology background. Scaling up tech workforce
73 861 546 373 315 1,521 1,563 1,400 1,420 1,440 1,460 1,480 1,500 1,520 1,540 1,560 1,580 Operations Client Services Technology Headcount Breakdown In number of employees Technology 44% of HC Client Services 15% of HC Operations 9% of HC 2021 Apr/24 Re-allocating resources to ensure continued innovation
74 25% 229 26% 443 31% 734 33% 791 75% 685 74% 1,258 69% 1,658 67% 1,622 914 1,702 2,392 2,413 2020 2021 2022 2023 Administrative Expenses Optimizing our spending in administrative expenses SG&A Expenses1 In R$ Million Note 1: SG&A Expenses consider personnel expenses, administrative expenses and depreciation and amortization.
75 25% 229 26% 443 31% 734 33% 791 26% 175 42% 532 38% 637 40% 650 914 1,702 2,392 2,413 2020 2021 2022 2023 Top 6 Providers Optimizing our spending in administrative expenses SG&A Expenses1 In R$ Million Note 1: SG&A Expenses consider personnel expenses, administrative expenses and depreciation and amortization.
76 -16% -40% -23% -75%+58%-52% Optimizing our cost structure across vendors 1 2 3 4 5 6 MasterCard Expense per Cards TPV In R$ AWS Expense per Active Client In R$ ATM Expense per Active Client In R$ Contact Center Expense per Active Client In R$ Printing & Shipping per Cards Active Client In R$ Google & Facebook Expense per Active Client In R$
77 2021 2022 2023 13.2 7.9 -40% 2021 2023 0.0029 0.0024 -16% 8.7 6.7 4.2 2021 2022 2023 -52% 11.7 7.9 2.9 2021 2022 2023 -75% 2021 2022 20236.6 7.8 8.6 -23% 6.9 10.9 10.8 2021 2022 2023 +58% 1 2 3 4 5 6 MasterCard Expense per Cards TPV In R$ AWS Expense per Active Client In R$ ATM Expense per Active Client In R$ Contact Center Expense per Active Client In R$ Printing & Shipping per Cards Active Client In R$ Google & Facebook Expense per Active Client In R$ Optimizing our cost structure across vendors
78 Revenue In R$ Billion Increasing revenues at a fast pace 71%, 0.7 72%, 1.6 66%, 2.3 68%, 3.2 29%, 0.3 28%, 0.6 34%, 1.2 32%, 1.5 1.0 2.2 3.6 4.8 1.3 3.1 6.0 8.1 2020 2021 2022 2023 Net Revenue Net Fee Revenue NII Gross Revenue +135% +120% +92% +60% +35% +33%
79 2023 Interest Income Breakdown In R$ Million & in % 926 15% 1,117 18% 522 9%1,246 21% 738 12% 1,546 25% 2023 Gross Fee Revenue Breakdown In R$ Million & in % 1,040 52% 341 17% 121 6% 170 9% 89 5% 222 11% R$1,983R$6,096 Real Estate Personal SMB Securities & Derivatives Anticipation of Credit Card Receivables Credit Card Banking1 Shop Other Insurance Invest Exchange Note 1: Includes interchange revenue. Increasing revenues at a fast pace
80 2023 Interest Income Breakdown In R$ Million & in % 926 15% 1,117 18% 522 9%1,246 21% 738 12% 1,546 25% 2023 Gross Fee Revenue Breakdown In R$ Million & in % 1,040 52% 341 17% 121 6% 170 9% 89 5% 222 11% R$1,983R$6,096 Real Estate Personal SMB Securities & Derivatives Anticipation of Credit Card Receivables Credit Card Banking1 Shop Other Insurance Invest Exchange 1 2 4 3 5 6 Note 1: Includes interchange revenue. Increasing revenues at a fast pace
81 Credit Card Revenue per Credit Card Active Client In R$ FGTS ROE In % Home Equity ROE In % Banking Revenue per Cards Active Client In R$ Shop Revenue per Inter Shop Active Client In R$ Insurance Revenue per Insurance Active Client In R$ +4x +33 p.p. +8 p.p. +62%+89%+8% Boosting operational leverage Note 1: Includes interchange revenue. 1 2 3 4 5 6
82 Insurance Revenue per Insurance Active Client In R$ 0% 15% 48% 2022 2023 318 89 202 2021 2022 2023 +33 p.p.+4x +89% +62% +8 p.p. +8% 107 110 115 2021 2022 2023 57 30 2021 2022 20232021 100 62 2023 2021 23% 15% Banking Revenue per Cards Active Client In R$ Shop Revenue per Inter Shop Active Client In R$ Boosting operational leverage Note 1: Includes interchange revenue. Credit Card Revenue per Credit Card Active Client In R$ FGTS ROE In % Home Equity ROE In % 1 2 3 4 5 6 2021
83 Total Clients Efficiency Ratio Return on Equity What we achieved so far Our 5-year north star By 2027 ~60 MM ~30 % ~30 % Where we started 3Q22 Year 0 Year 5 23MM 75% (2%) G ro w th O pe ra tio na l Le ve ra ge Pr of ita bi lit y Year 1 4Q23 Year 2 4Q24 Year 3 4Q25 Year 4 4Q26 Year 1 4Q23 Year 2 4Q24 Year 3 4Q25 Year 4 4Q26 Year 5 4Q27 Year 0 3Q22 Year 0 3Q22 Year 5 4Q27 32MM 1Q24 48% 10% 36% Year 3 4Q25 Year 4 4Q26 Year 0 3Q22 Year 5 4Q27 Year 2 4Q24 Year 1 4Q23 24% 60% In the end, it all comes down to the 60-30-30 plan
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Non-IFRS measures and KPIs Activation Rate: Number of active clients at the end of the quarter Total number of clients at the end of the quarter Active clients: We define an active client as a customer at any given date that was the source of any amount of revenue for us in the preceding three months, or/and a customer that used products in the preceding three months. For Inter insurance, we calculate the number of active clients for our insurance brokerage vertical as the number of beneficiaries of insurance policies effective as of a particular date. For Inter Invest, we calculate the number of active clients as the number of individual accounts that have invested on our platform over the applicable period. Active clients per employee: Number of active clients at the end of the quarter Total number of employees at the end of the quarter, including interns Administrative efficiency ratio: Administrative expenses + Depreciation and amortization Net Interest Income + Net result from services and comissions + Other revenue − Tax expense Annualized interest rates: Yearly rate calculated by multiplying the quarterly interest by four, over the average portfolio of the last two quarters. All-in loans rate considers Real Estate, Personnal +FGTS, SMBs, Credit Card, excluding non-interest earnings credit card receivables, and Anticipation of Credit Card Receivables. Anticipation of credit card receivables: Disclosed in note 9.a of the Financial Statements, line " "Loans to financial institutions”. ARPAC gross of interest expenses: (Interest income + (Revenue from services and comissions − Cashback − Inter rewards) + Income from securities and derivarives + Other revenue) ÷ 3 Average of the last 2 quarters Active Clients ARPAC net of interest expenses: (Revenue − Interest expenses) ÷ 3 Average of the last 2 quarters Active Clients ARPAC per quarterly cohort: Total Gross revenue net of interest expenses in a given cohort divided by the average number of active clients in the current and previous periods1. Cohort is defined as the period in which the client started his relationship with Inter. 1 - Average number of active clients in the current and previous periods: For the first period, is used the total number of active clients in the end of the period. Assets under custody (AuC): We calculate assets under custody, or AUC, at a given date as the market value of all retail clients’ assets invested through our investment platform as of that same date. We believe that AUC, as it reflects the total volume of assets invested in our investment platform without accounting for our operational efficiency, provides us useful insight on the appeal of our platform. We use this metric to monitor the size of our investment platform. Card fee revenue: It is part of the “Revenue from services and commission” and “Other revenue” on IFRS Income Statement. Client acquisition cost (CAC): The average cost to add a client to the platform, considering operating expenses for opening an account, such as onboarding personnel, embossing and sending cards and digital marketing expenses with a focus on client acquisition, divided by the number of accounts opened in the quarter. 85
Card+PIX TPV: PIX, debit and credit cards and withdrawal transacted volumes of a given period. PIX is a Central Bank of Brazil solution to bring instant payments among banks and financial institutions in Brazil. Card+PIX TPV per active client: Card+PIX TPV for a given period divided by the number of active clients as of the last day of the period. Cost of funding: Interest expenses × 4 Average of last 2 quarters Interest bearing liabilities (demand deposits, time deposits, savings deposits, creditors by resources to release, securities issued, securities sold under agreements to repurchase, interbank deposits and others) Cost of risk: Impairment losses on Linancial assets × 4 Average of last 2 quarters of Loans and advances to customers Cost of risk excluding anticipation of credit card receivables: Impairment losses on Linancial assets × 4 Average of last 2 quarters of Loans and advances to customers excluding anticipation of credit card receivables Cost of risk excluding credit card: Impairment losses on Linancial assets × 4 Average of last 2 quarters of Loans and advances to customers excluding credit card Cost-to-serve (CTS): Personnel Expense + Administrative Expenses − Total CAC ÷ 3 Average of the last 2 quarters Active Clients Coverage ratio: Provision for expected credit loss Overdue higher than 90 days Earning portfolio (IEP): Earnings Portfolio includes “Amounts due from financial institutions” + “Loans and advances to customers” + “Securities” + “Derivatives” from the IFRS Balance Sheet Efficiency ratio: Personnel expense + Administrative expenses + Depreciation and amortization Net Interest Income + Net result from services and comissions + Other revenue − Tax expense Fee revenue ratio: Net result from services and commissions + Other revenue Net Interest Income + Net result from services and comissions + Other revenue − Tax expense Funding: Demand Deposits + Time Deposits + Securities Issued + Savings Deposits + Creditors by Resources to Release + Securities sold under agreements to repurchase + Interbank deposits + Borrowing and onlending Global Services Clients: Includes Brazilian Global Account clients, US clients and international investors. Non-IFRS measures and KPIs 86
Gross loan portfolio: Loans and Advance to Customers + Loans to financial institutions Gross merchandise volume (GMV): Gross merchandise value, or GMV, for a given period as the total value of all sales made or initiated through our Inter Shop & Commerce Plus platform managed by Inter Shop & Commerce Plus. Gross take rate: Inter Shop gross revenue GMV Margin per active client gross of interest expenses: ARPAC gross of interest expenses – Cost to Serve Margin per active client net of interest expenses: ARPAC net of interest expenses – Cost to Serve Net fee income: Net result from services and commissions + Other Revenue Net interest income: Interest Income + Interest Expenses + Income from securities and derivatives Net revenue: Net interest income + Net result from services and commissions + Other revenue Net take rate: Inter Shop net revenue GMV NIM 1.0 – IEP – Credit Card Transactional Portfolio: Net interest income x 4 Average of 2 Last Quarters Earning Portfolio (Loans to Linancial institutions + Securities + Derivatives + Net loans and advances to customers) – Credit card transactor portfolio NIM 2.0 – IEP Only: Net interest income x 4 Average of 2 Last Quarters Earning Portfolio (Loans to Linancial institutions + Securities + Derivatives + Net loans and advances to customers) NPL 15 to 90 days: Overdue 15 to 90 days Loans and Advance to Costumers + Loans to Linancial institutions NPL > 90 days: Overdue higher than 90 days Loans and Advance to Costumers + Loans to Linancial institutions NPL formation: Overdue balance higher than 90 days in the current quarter –Overdue balance higher than 90 days inthe previous quarter +Write − off change in the current quarter Total loans and advance to customers in the previous quarter Non-IFRS measures and KPIs 87
Risk-Adjusted NIM 2.0: Net interest income − Impairment losses on Linancial assets x 4 Average of 2 Last Quarters Earning Portfolio (Loans to Linancial institutions + Securities + Derivatives + Net loans and advances to customers) SG&A: Administrative Expenses + Personnel Expenses + Depreciation and Amortization Stage 3 formation: Stage 3 balance in the current quarter – Stage 3 balance in the previous quarter +Write − off change in the current quarter Total loans and advance to customers in the previous quarter Tier I ratio: Tier I referential equity Risk weighted assets Total gross revenue: Interest income + Revenue from services and commissions − Cashback expenses − Inter rewards + Income from securities and derivatives + Other revenue Non-IFRS measures and KPIs Personal efficiency ratio: Personnel expense Net Interest Income + Net result from services and comissions + Other revenue − Tax expense Primary Banking Relationship: A client who has 50% or more of their income after tax for that period flowing to their bank account with us during the month. Return on average equity (ROE): (ProLit / (loss) for the quarter)× 4 Average of last 2 quarters of total shareholder`s equity Risk-adjusted efficiency ratio: Personnel expense + Administrative expenses + Depreciation and amortization Net Interest Income + Net result from services and comissions + Other revenue − Tax expense − Impairment losses on Linancial assets Risk-adjusted NIM 1.0 Net interest income − Impairment losses on Linancial assets x 4 Average of 2 Last Quarters Earning Portfolio (Loans to Linancial institutions + Securities + Derivatives + Net loans and advances to customers) – Credit card transactor portfolio 88
SIGNATURE Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned, thereunto duly authorized. INTER & Co, INC. By: /s/ Santiago Horacio Stel Name: Santiago Horacio Stel Title: Senior Vice President of Finance and Risks Date: May 13, 2024
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