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• Assembling frames into a video in Node.js using fluent-ffmpeg [closed]

  14 novembre 2024, par Andrei

  I have the original video and it's modified frames in a folder. Now I want to assemble the modified frames into a new video. I also want to take the audio from the original video and add it to the new video.

  


  My latest code is this using fluent-ffmpeg. But it's not working.

  


  await new Promise((resolve, reject) => {
  ffmpeg(path.join(processedFramesDir, "frame-%d.png"))
    .inputOptions(["-framerate 30", "-start_number 1"])
    .input(videoPath)
    .outputOptions([
      "-c:v",
      "libx264",
      "-c:a",
      "copy",
      "-shortest",
      "-r",
      "30",
      "-pix_fmt",
      "yuv420p",
    ])
    .outputOptions(["-map 0:v:0", "-map 1:a:0"])
    .save(outputVideoPath)
    .on("start", (commandLine) => {
      console.log("FFmpeg command: " + commandLine);
    })
    .on("stderr", (stderrLine) => {
      console.log("FFmpeg stderr: " + stderrLine);
    })
    .on("end", resolve)
    .on("error", (err, stdout, stderr) => {
      console.error("Error assembling video:", err);
      console.error("FFmpeg stderr:", stderr);
      reject(err);
    });
});


  


  I get this error even though the frames exist and they are valid pngs :
FFmpeg command: ffmpeg -framerate 30 -start_number 1 -i /tmp/video-processing-CyULOE/processedFrames/frame-%05d.png -i /tmp/video-processing-CyULOE/input.mp4 -y -c:v libx264 -c:a copy -shortest -r 30 -pix_fmt yuv420p -map 0:v:0 -map 1:a:0 /tmp/video-processing-CyULOE/output.mp4 2024-11-13 23:40:27 FFmpeg stderr: ffmpeg version 4.1.11-0&#x2B;deb10u1 Copyright (c) 2000-2023 the FFmpeg developers 2024-11-13 23:40:27 FFmpeg stderr:   built with gcc 8 (Debian 8.3.0-6) 2024-11-13 23:40:27 FFmpeg stderr:   configuration: --prefix=/usr --extra-version=0&#x2B;deb10u1 --toolchain=hardened --libdir=/usr/lib/x86_64-linux-gnu --incdir=/usr/include/x86_64-linux-gnu --arch=amd64 --enable-gpl --disable-stripping --enable-avresample --disable-filter=resample --enable-avisynth --enable-gnutls --enable-ladspa --enable-libaom --enable-libass --enable-libbluray --enable-libbs2b --enable-libcaca --enable-libcdio --enable-libcodec2 --enable-libflite --enable-libfontconfig --enable-libfreetype --enable-libfribidi --enable-libgme --enable-libgsm --enable-libjack --enable-libmp3lame --enable-libmysofa --enable-libopenjpeg --enable-libopenmpt --enable-libopus --enable-libpulse --enable-librsvg --enable-librubberband --enable-libshine --enable-libsnappy --enable-libsoxr --enable-libspeex --enable-libssh --enable-libtheora --enable-libtwolame --enable-libvidstab --enable-libvorbis --enable-libvpx --enable-libwavpack --enable-libwebp --enable-libx265 --enable-libxml2 --enable-libxvid --enable-libzmq --enable-libzvbi --enable-lv2 --enable-omx --enable-openal --enable-opengl --enable-sdl2 --enable-libdc1394 --enable-libdrm --enable-libiec61883 --enable-chromaprint --enable-frei0r --enable-libx264 --enable-shared 2024-11-13 23:40:27 FFmpeg stderr:   libavutil      56. 22.100 / 56. 22.100 2024-11-13 23:40:27 FFmpeg stderr:   libavcodec     58. 35.100 / 58. 35.100 2024-11-13 23:40:27 FFmpeg stderr:   libavformat    58. 20.100 / 58. 20.100 2024-11-13 23:40:27 FFmpeg stderr:   libavdevice    58.  5.100 / 58.  5.100 2024-11-13 23:40:27 FFmpeg stderr:   libavfilter     7. 40.101 /  7. 40.101 2024-11-13 23:40:27 FFmpeg stderr:   libavresample   4.  0.  0 /  4.  0.  0 2024-11-13 23:40:27 FFmpeg stderr:   libswscale      5.  3.100 /  5.  3.100 2024-11-13 23:40:27 FFmpeg stderr:   libswresample   3.  3.100 /  3.  3.100 2024-11-13 23:40:27 FFmpeg stderr:   libpostproc    55.  3.100 / 55.  3.100 2024-11-13 23:40:27 FFmpeg stderr: [png @ 0x5630fb89a880] Invalid PNG signature 0x52494646F8A20000. 2024-11-13 23:40:27 FFmpeg stderr: [png @ 0x5630fb89a880] Invalid PNG signature 0x52494646C89F0000. 2024-11-13 23:40:27 FFmpeg stderr: [png @ 0x5630fb89a880] Invalid PNG signature 0x524946464EA10000. 2024-11-13 23:40:27 FFmpeg stderr: [png @ 0x5630fb89a880] Invalid PNG signature 0x5249464628A40000. 2024-11-13 23:40:27 FFmpeg stderr: [png @ 0x5630fb89a880] Invalid PNG signature 0x52494646AAA30000. 2024-11-13 23:40:27 FFmpeg stderr: [png @ 0x5630fb89a880] Invalid PNG signature 0x524946467CA10000. 2024-11-13 23:40:27 FFmpeg stderr: [png @ 0x5630fb89a880] Invalid PNG signature 0x52494646AAA30000. 2024-11-13 23:40:27 FFmpeg stderr: [png @ 0x5630fb89a880] Invalid PNG signature 0x52494646BAA10000. 2024-11-13 23:40:27 FFmpeg stderr: [png @ 0x5630fb89a880] Invalid PNG signature 0x52494646ACA30000. 2024-11-13 23:40:27 FFmpeg stderr: [png @ 0x5630fb89a880] Invalid PNG signature 0x5249464670A80000. 2024-11-13 23:40:27 FFmpeg stderr: [png @ 0x5630fb89a880] Invalid PNG signature 0x52494646E8A60000. 2024-11-13 23:40:27 FFmpeg stderr: [png @ 0x5630fb89a880] Invalid PNG signature 0x524946469AA60000. 2024-11-13 23:40:27 FFmpeg stderr: [png @ 0x5630fb89a880] Invalid PNG signature 0x5249464672A90000. 2024-11-13 23:40:27 FFmpeg stderr: [png @ 0x5630fb89a880] Invalid PNG signature 0x52494646B8A50000. 2024-11-13 23:40:27 FFmpeg stderr: [png @ 0x5630fb89a880] Invalid PNG signature 0x52494646AAA80000. 2024-11-13 23:40:27 FFmpeg stderr: [png @ 0x5630fb89a880] Invalid PNG signature 0x52494646A0A70000. 2024-11-13 23:40:27 FFmpeg stderr:     Last message repeated 1 times 2024-11-13 23:40:27 FFmpeg stderr: [png @ 0x5630fb89a880] Invalid PNG signature 0x5249464646A80000. 2024-11-13 23:40:27 FFmpeg stderr: [image2 @ 0x5630fb898a40] decoding for stream 0 failed 2024-11-13 23:40:27 FFmpeg stderr: [image2 @ 0x5630fb898a40] Could not find codec parameters for stream 0 (Video: png, none(pc)): unspecified size 2024-11-13 23:40:27 FFmpeg stderr: Consider increasing the value for the &#x27;analyzeduration&#x27; and &#x27;probesize&#x27; options 2024-11-13 23:40:27 FFmpeg stderr: Input #0, image2, from &#x27;/tmp/video-processing-CyULOE/processedFrames/frame-%05d.png&#x27;: 2024-11-13 23:40:27 FFmpeg stderr:   Duration: 00:00:00.60, start: 0.000000, bitrate: N/A 2024-11-13 23:40:27 FFmpeg stderr:     Stream #0:0: Video: png, none(pc), 30 fps, 30 tbr, 30 tbn, 30 tbc 2024-11-13 23:40:28 FFmpeg stderr: Input #1, mov,mp4,m4a,3gp,3g2,mj2, from &#x27;/tmp/video-processing-CyULOE/input.mp4&#x27;: 2024-11-13 23:40:28 FFmpeg stderr:   Metadata: 2024-11-13 23:40:28 FFmpeg stderr:     major_brand     : isom 2024-11-13 23:40:28 FFmpeg stderr:     minor_version   : 512 2024-11-13 23:40:28 FFmpeg stderr:     compatible_brands: isomiso2avc1mp41 2024-11-13 23:40:28 FFmpeg stderr:     encoder         : Lavf60.16.100 2024-11-13 23:40:28 FFmpeg stderr:   Duration: 00:00:00.62, start: 0.000000, bitrate: 4289 kb/s 2024-11-13 23:40:28 FFmpeg stderr:     Stream #1:0(und): Video: h264 (High) (avc1 / 0x31637661), yuv420p(tv, bt709), 1920x1080 [SAR 1:1 DAR 16:9], 4395 kb/s, 30 fps, 30 tbr, 15360 tbn, 60 tbc (default) 2024-11-13 23:40:28 FFmpeg stderr:     Metadata: 2024-11-13 23:40:28 FFmpeg stderr:       handler_name    : VideoHandler 2024-11-13 23:40:28 FFmpeg stderr:     Stream #1:1(und): Audio: aac (LC) (mp4a / 0x6134706D), 48000 Hz, stereo, fltp, 2 kb/s (default) 2024-11-13 23:40:28 FFmpeg stderr:     Metadata: 2024-11-13 23:40:28 FFmpeg stderr:       handler_name    : SoundHandler 2024-11-13 23:40:28 FFmpeg stderr: Stream mapping: 2024-11-13 23:40:28 FFmpeg stderr:   Stream #0:0 -> #0:0 (png (native) -> h264 (libx264)) 2024-11-13 23:40:28 FFmpeg stderr:   Stream #1:1 -> #0:1 (copy) 2024-11-13 23:40:28 FFmpeg stderr: Press [q] to stop, [?] for help 2024-11-13 23:40:28 FFmpeg stderr: [image2 @ 0x5630fb898a40] Thread message queue blocking; consider raising the thread_queue_size option (current value: 8) 2024-11-13 23:40:28 FFmpeg stderr: [png @ 0x5630fb9b7700] Invalid PNG signature 0x52494646F8A20000. 2024-11-13 23:40:28 FFmpeg stderr: [png @ 0x5630fb988dc0] Invalid PNG signature 0x52494646C89F0000. 2024-11-13 23:40:28 FFmpeg stderr: [png @ 0x5630fba3edc0] Invalid PNG signature 0x524946464EA10000. 2024-11-13 23:40:28 FFmpeg stderr: [png @ 0x5630fba40600] Invalid PNG signature 0x5249464628A40000. 2024-11-13 23:40:28 FFmpeg stderr: Error while decoding stream #0:0: Invalid data found when processing input 2024-11-13 23:40:28 FFmpeg stderr: [png @ 0x5630fb8c7900] Invalid PNG signature 0x52494646AAA30000. 2024-11-13 23:40:28 FFmpeg stderr: Error while decoding stream #0:0: Invalid data found when processing input 2024-11-13 23:40:28 FFmpeg stderr: [png @ 0x5630fb9b7700] Invalid PNG signature 0x524946467CA10000. 2024-11-13 23:40:28 FFmpeg stderr: Error while decoding stream #0:0: Invalid data found when processing input 2024-11-13 23:40:28 FFmpeg stderr: [png @ 0x5630fb988dc0] Invalid PNG signature 0x52494646AAA30000. 2024-11-13 23:40:28 FFmpeg stderr: Error while decoding stream #0:0: Invalid data found when processing input 2024-11-13 23:40:28 FFmpeg stderr: [png @ 0x5630fba3edc0] Invalid PNG signature 0x52494646BAA10000. 2024-11-13 23:40:28 FFmpeg stderr: [png @ 0x5630fba40600] Invalid PNG signature 0x52494646ACA30000. 2024-11-13 23:40:28 FFmpeg stderr: Error while decoding stream #0:0: Invalid data found when processing input 2024-11-13 23:40:28 FFmpeg stderr:     Last message repeated 1 times 2024-11-13 23:40:28 FFmpeg stderr: [png @ 0x5630fb8c7900] Invalid PNG signature 0x5249464670A80000. 2024-11-13 23:40:28 FFmpeg stderr: Error while decoding stream #0:0: Invalid data found when processing input 2024-11-13 23:40:28 FFmpeg stderr: [png @ 0x5630fb9b7700] Invalid PNG signature 0x52494646E8A60000. 2024-11-13 23:40:28 FFmpeg stderr: Error while decoding stream #0:0: Invalid data found when processing input 2024-11-13 23:40:28 FFmpeg stderr: [png @ 0x5630fb988dc0] Invalid PNG signature 0x524946469AA60000. 2024-11-13 23:40:28 FFmpeg stderr: Error while decoding stream #0:0: Invalid data found when processing input 2024-11-13 23:40:28 FFmpeg stderr: [png @ 0x5630fba3edc0] Invalid PNG signature 0x5249464672A90000. 2024-11-13 23:40:28 FFmpeg stderr: Error while decoding stream #0:0: Invalid data found when processing input 2024-11-13 23:40:28 FFmpeg stderr: [png @ 0x5630fba40600] Invalid PNG signature 0x52494646B8A50000. 2024-11-13 23:40:28 FFmpeg stderr: Error while decoding stream #0:0: Invalid data found when processing input 2024-11-13 23:40:28 FFmpeg stderr: [png @ 0x5630fb8c7900] Invalid PNG signature 0x52494646AAA80000. 2024-11-13 23:40:28 FFmpeg stderr: Error while decoding stream #0:0: Invalid data found when processing input 2024-11-13 23:40:28 FFmpeg stderr: [png @ 0x5630fb9b7700] Invalid PNG signature 0x52494646A0A70000. 2024-11-13 23:40:28 FFmpeg stderr: [png @ 0x5630fb988dc0] Invalid PNG signature 0x52494646A0A70000. 2024-11-13 23:40:28 FFmpeg stderr: Error while decoding stream #0:0: Invalid data found when processing input 2024-11-13 23:40:28 FFmpeg stderr: [png @ 0x5630fba3edc0] Invalid PNG signature 0x5249464646A80000. 2024-11-13 23:40:28 FFmpeg stderr: Error while decoding stream #0:0: Invalid data found when processing input 2024-11-13 23:40:28 FFmpeg stderr:     Last message repeated 4 times 2024-11-13 23:40:28 FFmpeg stderr: Cannot determine format of input stream 0:0 after EOF 2024-11-13 23:40:28 FFmpeg stderr: Error marking filters as finished 2024-11-13 23:40:28 FFmpeg stderr: Conversion failed! 2024-11-13 23:40:28 FFmpeg stderr:  2024-11-13 23:40:28 Error assembling video: Error: ffmpeg exited with code 1: Cannot determine format of input stream 0:0 after EOF 2024-11-13 23:40:28 Error marking filters as finished 2024-11-13 23:40:28 Conversion failed! 2024-11-13 23:40:28  2024-11-13 23:40:28     at ChildProcess.<anonymous> (/usr/src/app/node_modules/fluent-ffmpeg/lib/processor.js:180:22) 2024-11-13 23:40:28     at ChildProcess.emit (node:events:519:28) 2024-11-13 23:40:28     at ChildProcess._handle.onexit (node:internal/child_process:294:12)</anonymous>

  


  The code used to

  


  ffmpeg(videoPath) .screenshots({ folder: framesDir, filename: "frame-%i.png", size: "?x1080", count: 10, }) .on("end", resolve) .on("error", reject);


  


  The pngs are valid and displaying in windows photos viewer

  


• A Quick Start Guide to the Payment Services Directive (PSD2)

  22 novembre 2024, par Daniel Crough — Banking and Financial Services, Privacy

  In 2023, there were 266.2 billion real-time payments indicating that the demand for secure transactions has never been higher. As we move towards a more open banking system, there are a host of new payment solutions that offer convenience and efficiency, but they also present new risks.

  The Payment Services Directive 2 (PSD2) is one of many regulations established to address these concerns. PSD2 is a European Union (EU) business initiative to offer smooth payment experiences while helping customers feel safe from online threats. 

  In this post, learn what PSD2 includes, how it improves security for online payments, and how Matomo supports banks and financial institutions with PSD2 compliance.

  What is PSD2 ? 

  PSD2 is an EU directive that aims to improve the security of electronic payments across the EU. It enforces strong customer authentication and allows third-party access to consumer accounts with explicit consent. 

  Its main objectives are :

  • Strengthening security and data privacy measures around digital payments.
  • Encouraging innovation by allowing third-party providers access to banking data.
  • Improving transparency with clear communication regarding fees, terms and conditions associated with payment services.
  • Establishing a framework for sharing customer data securely through APIs for PSD2 open banking.

  Rationale behind PSD2 

  PSD2’s primary purpose is to engineer a more integrated and efficient European payment market without compromising the security of online transactions. 

  The original directive aimed to standardise payment services across EU member states, but as technology evolved, an updated version was needed.

  PSD2 is mandatory for various entities within the European Economic Area (EEA), like :

  • Banks and credit institutions
  • Electronic money institutions or digital banks like Revolut
  • Card issuing and acquiring institutions
  • Fintech companies
  • Multi-national organisations operating in the EU

  PSD2 implementation timeline

  With several important milestones, PSD2 has reshaped how payment services work in Europe. Here’s a closer look at the pivotal events that paved the way for its launch.

  • 2002 : The banking industry creates the European Payments Council (EC), which drives the Single Euro Payments Area (SEPA) initiative to include non-cash payment instruments across European regions. 
  • 2007 : PSD1 goes into effect.
  • 2013 : EC proposes PSD2 to include protocols for upcoming payment services.
  • 2015 : The Council of European Union passes PSD2 and gives member states two years to incorporate it.
  • 2018 : PSD2 goes into effect. 
  • 2019 : The final deadline for all companies within the EU to comply with PSD2’s regulations and rules for strong customer authentication. 

  PSD2 : Key components 

  PSD2 introduces several key components. Let’s take a look at each one.

  Strong Customer Authentication (SCA)

  The Regulatory Technical Standards (RTS) under PSD2 outline specific requirements for SCA. 

  SCA requires multi-factor authentication for online transactions. When customers make a payment online, they need to verify their identity using at least two of the three following elements :

  • Knowledge : Something they know (like a password, a code or a secret answer)
  • Possession : Something they have (like their phone or card)
  • Inherence : Something they are (like biometrics — fingerprints or facial features)

  

  Before SCA, banks verified an individual’s identity only using a password. This dual verification allows only authorised users to complete transactions. SCA implementation reduces fraud and increases the security of electronic payments.

  SCA implementation varies for different payment methods. Debit and credit cards use the 3D Secure (3DS) protocol. E-wallets and other local payment measures often have their own SCA-compliant steps. 

  3DS is an extra step to authenticate a customer’s identity. Most European debit and credit card companies implement it. Also, in case of fraudulent chargebacks, the issuing bank becomes liable due to 3DS, not the business. 

  However, in SCA, certain transactions are exempt : 

  • Low-risk transactions : A transaction by an issuer or an acquirer whose fraud level is below a specific threshold. If the acquirer feels that a transaction is low risk, they can request to skip SCA. 
  • Low-value transactions : Transactions under €30.
  • Trusted beneficiaries : Trusted merchants customers choose to safelist.
  • Recurring payments : Recurring transactions for a fixed amount are exempt from SCA after the first transaction.

  Third-party payment service providers (TPPs) framework

  TPPs are entities authorised to access customer banking data and initiate payments. There are three types of TPPs :

  Account Information Service Providers (AISPs)

  AISPs are services that can view customers’ account details, but only with their permission. For example, a budgeting app might use AISP services to gather transaction data from a user’s bank account, helping them monitor expenses and oversee finances. 

  Payment Initiation Service Providers (PISPs)

  PISPs enable clients to initiate payments directly from their bank accounts, bypassing the need for conventional payment options such as debit or credit cards. After the customer makes a payment, PISPs immediately contact the merchant to ensure the user can access the online services or products they bought. 

  Card-Based Payment Instruments (CBPII)

  CBPIIs refer to services that issue payment cards linked to customer accounts. 

  Requirements for TPPs

  To operate effectively under PSD2, TPPs must meet several requirements :

  Consumer consent : Customers must explicitly authorise TPPs to retrieve their financial data. This way, users can control who can view their information and for what purpose.

  Security compliance : TPPs must follow SCA and secure communication guidelines to protect users from fraud and unauthorised access.

  API availability : Banks must make their Application Programming Interfaces (APIs) accessible and allow TPPs to connect securely with the bank’s systems. This availability helps in easy integration and lets TPPs access essential data. 

  Consumer protection methods

  PSD2 implements various consumer protection measures to increase trust and transparency between consumers and financial institutions. Here’s a closer look at some of these key methods :

  • Prohibition of unjustified fees : PSD2 requires banks to clearly communicate any additional charges or fees for international transfers or account maintenance. This ensures consumers are fully aware of the actual costs and charges.
  • Timely complaint resolution : PSD2 mandates that payment service providers (PSPs) have a straightforward complaint procedure. If a customer faces any problems, the provider must respond within 15 business days. This requirement encourages consumers to engage more confidently with financial services.
  • Refund in case of unauthorised payment : Customers are entitled to a full refund for payments made without their consent.
  • Surcharge ban : Additional charges on credit and debit card payments aren’t allowed. Businesses can’t impose extra fees on these payment methods, which increases customers’ purchasing power.

  Benefits of PSD2 

  Businesses — particularly those in banking, fintech, finserv, etc. — stand to benefit from PSD2 in several ways.

  Access to customer data

  With customer consent, banks can analyse spending patterns to develop tailored financial products that match customer needs, from personalised savings accounts to more relevant loan offerings.

  Innovation and cost benefits 

  PSD2 opened payment processing up to more market competition. New payment companies bring fresh approaches to banking services, making daily transactions more efficient while driving down processing fees across the sector.

  Also, banks now work alongside payment technology providers, combining their strengths to create better services. This collaboration brings faster payment options to businesses, helping them stay competitive while reducing operational costs.

  Improved customer trust and experience

  Due to PSD2 guidelines, modern systems handle transactions quickly without compromising the safety of payment data, creating a balanced approach to digital banking.

  

  Banking customers now have more control over their financial information. Clear processes allow consumers to view and adjust their financial preferences as needed.

  Strong security standards form the foundation of these new payment systems. Payment provider platforms must adhere to strict regulations and implement additional protection measures.

  Challenges in PSD2 compliance 

  What challenges can banks and financial institutions face regarding PSD2 compliance ? Let’s examine them. 

  Resource requirements

  For many businesses, the new requirements come with a high price tag. PSD2 requires banks and fintechs to build and update their systems so that other providers can access customer data safely. For example, they must develop APIs to allow TPPs to acquire customer data. 

  Many banks still use older systems that can’t meet PSD2’s added requirements. In addition to the cost of upgrades, complying with PSD2 requires banks to devote resources to training staff and monitoring compliance.

  The significant costs required to update legacy systems and IT infrastructure while keeping services running remain challenging.

  Risks and penalties

  Organisations that fail to comply with PSD2 regulations can face significant penalties.

  Additionally, the overlapping requirements of PSD2 and other regulations, such as the General Data Protection Regulation (GDPR), can create confusion. 

  Banks need clear agreements with TPPs about who’s responsible when things go wrong. This includes handling data breaches, preventing data misuse and protecting customer information. 

  Increased competition 

  Introducing new players in the financial ecosystem, such as AISPs and PISPs, creates competition. Banks must adapt their services to stay competitive while managing compliance costs.

  PSD2 aims to protect customers but the stronger authentication requirements can make banking less convenient. Banks must balance security with user experience. Focused time, effort and continuous monitoring are needed for businesses to stay compliant and competitive.

  How Matomo can help 

  Matomo gives banks and financial institutions complete control over their data through privacy-focused web analytics, keeping collected information internal rather than being used for marketing or other purposes. 

  Its advanced security setup includes access controls, audit logs, SSL encryption, single sign-on and two-factor authentication. This creates a secure environment where sensitive data remains accessible only to authorised staff.

  While prioritizing privacy, Matomo provides tools to understand user flow and customer segments, such as session recordings, heatmaps and A/B testing.

  Financial institutions particularly benefit from several key features : 

  • Tools for obtaining explicit consent before processing personal data like this Do Not Track preference
  • Insights into how financial institutions integrate TPPs (including API usage, user engagement and potential authentication drop-off points)
  • Tracking of failed login attempts or unusual access patterns
  • IP anonymization to analyse traffic patterns and detect potential fraud

  

  PSD3 : The next step 

  In recent years, we have seen the rise of innovative payment companies and increasingly clever fraud schemes. This has prompted regulators to propose updates to payment rules.

  PSD3’s scope is to adapt to the evolving digital transformation and to better handle these fraud risks. The proposed measures : 

  • Encourage PSPs to share fraud-related information.
  • Make customers aware of the different types of fraud.
  • Strengthen customer authentication standards.
  • Provide non-bank PSPs restricted access to EU payment systems. 
  • Enact payment rules in a directly applicable regulation and harmonise and enforce the directive.

  Web analytics that respect user privacy 

  Achieving compliance with PSD2 may be a long road for some businesses. With Matomo, organisations can enjoy peace of mind knowing their data practices align with legal requirements.

  Ready to stop worrying over compliance with regulations like PSD2 and take control of your data ? Start your 21-day free trial with Matomo.

• Lean Analytics in a Privacy-First Environment – Bootcamp with Timo Dechau

  29 novembre 2024, par Daniel Crough — Banking and Financial Services, GDPR, Marketing, Privacy, Videos, Featured Banking Content

  In a recent bootcamp, Timo Dechau walked attendees through his approach to data and measurement in privacy-focused analytics environments. He demonstrates how to shift from a chaotic, ‘track-it-all’ mentality to a focused method that prioritizes quality over quantity. This post will summarize some of his key privacy-first analytics ideas, but be sure to check out the on-demand video for more detail.

  Watch the bootcamp on demand

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  Unrestrained data collection leads to data bloat

  Marketing and the business world are experiencing a data problem. Analysts and business intelligence teams grapple with large amounts of data that aren’t always useful and are often incomplete. The idea that “more data is better” became a guiding principle in the early 2000s, encouraging companies to gather everything possible using all available data collection methods. This unrestrained pursuit often led to an unexpected problem : data bloat. Too much data, too little clarity. Digital marketers, analysts, and business leaders now try to navigate vast amounts of information that create more confusion than insight, especially when the data is incomplete due to privacy regulations.

  

  Cutting through the noise, focusing on what matters

  The “more data is better” mindset emerged when digital marketers were beginning to understand data’s potential. It seemed logical : more data should mean more opportunities to optimise, personalise, and drive results. But in practice, gathering every possible piece of data often leads to a cluttered, confusing pile of metrics that can mislead more than guide.

  This approach carries hidden costs. Excessive data collection burns resources, increases privacy concerns, and leaves teams unfocused. It’s easy to get lost trying to make sense of endless dashboards, metrics, and reports. More data doesn’t necessarily lead to better decisions ; it often just leads to more noise, hindering effective data management.

  Rethinking data management : From data overload to data mindfulness

  Data management has often prioritised comprehensive data gathering without considering the specific value of each data point. This approach has created more information, but not necessarily better insights.

  Data mindfulness is about taking a deliberate, focused approach to data collection and analysis. Instead of trying to collect everything, it emphasises gathering only what truly adds value. It’s about ensuring the data you collect serves a purpose and directly contributes to better insights and data-driven decision-making.

  Think of it like applying a “lean” methodology to data—trimming away the unnecessary and keeping only what is essential. Or consider embracing data minimalism to declutter your data warehouse, keeping only what truly sparks insight.

  

  Mindful data is ethical data

  Adopting a mindful approach to data can pay off in several ways :

  • Reduces overwhelm : When you reduce the clutter, you’re left with fewer, clearer metrics that lead to stronger decisions and actionable data insights.

  • Mitigates compliance risks : By collecting less, companies align better with privacy regulations and build trust with their customers. Privacy-first analytics and privacy-compliant analytics practices mean there’s no need for invasive tracking if it doesn’t add value—and customers will appreciate that.

  • Enhances data ethics : Focusing on the quality rather than the quantity of data collected ensures ethical data collection and management. Companies use data responsibly, respect user privacy, and minimise unnecessary data handling, strengthening customer relationships and brand integrity.

  • Improves data efficiency : Focused analytics means better use of resources. You’re spending less time managing meaningless metrics and more time working on meaningful insights. Many companies have found success by switching to a leaner, quality-first data approach, reporting sharper, more impactful results.

  Shifting towards simplicity and lean analytics

  If data mindfulness sounds appealing, here’s how you can get started :

  1. Ask the right questions. Before collecting any data, ask yourself : Why are we collecting this ? How will it drive value ? If you can’t answer these questions clearly, that data probably isn’t worth collecting. This is a key step in smart data management.

  2. Simplify metrics. Focus on the KPIs that truly matter for your business. Choose a handful of key metrics that reflect your goals rather than a sprawling list of nice-to-haves. Embracing data simplicity helps in targeting data collection effectively.

  3. Audit your current data. Review your existing data collection processes. Which metrics are you actively using to make decisions ? Eliminate any redundant or low-value metrics that create noise. Use ethical data management practices to ensure data efficiency and compliance. Understanding what is data management in this context is crucial.

  4. Implement lean analytics practices. Shift towards lean analytics by cutting down on unnecessary tracking. This can involve reducing reliance on multiple tracking scripts, simplifying your reporting, and setting up a streamlined dashboard focused on key outcomes. Embrace data reduction strategies to eliminate waste and boost effectiveness.

  Who should watch this bootcamp

  This bootcamp is perfect for data analysts, product managers, digital marketers and business leaders who are seeking a more streamlined approach to data measurement. If you’re interested in moving away from a chaotic “track-it-all” mentality and towards a focused, lean, and privacy-first analytics strategy, this workshop is for you.

  What you’ll discover

  • Practical steps : Learn actionable strategies to reduce data bloat and implement lean, privacy-first analytics in your organisation.

  • Real-life examples : Explore case studies of companies that have successfully adopted focused and privacy-first analytics.

  • Deep insights : Gain a deeper understanding of how to prioritise quality over quantity without sacrificing valuable insights.

  Watch the bootcamp on-demand

  For a comprehensive dive into these topics, watch the full workshop video or download the detailed transcript. Equip yourself with the knowledge and tools to transform your data management approach today.

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