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Médias (1)
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Spitfire Parade - Crisis
15 mai 2011, par
Mis à jour : Septembre 2011
Langue : English
Type : Audio
Autres articles (72)
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Amélioration de la version de base
13 septembre 2013Jolie sélection multiple
Le plugin Chosen permet d’améliorer l’ergonomie des champs de sélection multiple. Voir les deux images suivantes pour comparer.
Il suffit pour cela d’activer le plugin Chosen (Configuration générale du site > Gestion des plugins), puis de configurer le plugin (Les squelettes > Chosen) en activant l’utilisation de Chosen dans le site public et en spécifiant les éléments de formulaires à améliorer, par exemple select[multiple] pour les listes à sélection multiple (...) -
Other interesting software
13 avril 2011, parWe don’t claim to be the only ones doing what we do ... and especially not to assert claims to be the best either ... What we do, we just try to do it well and getting better ...
The following list represents softwares that tend to be more or less as MediaSPIP or that MediaSPIP tries more or less to do the same, whatever ...
We don’t know them, we didn’t try them, but you can take a peek.
Videopress
Website : http://videopress.com/
License : GNU/GPL v2
Source code : (...) -
Emballe médias : à quoi cela sert ?
4 février 2011, parCe plugin vise à gérer des sites de mise en ligne de documents de tous types.
Il crée des "médias", à savoir : un "média" est un article au sens SPIP créé automatiquement lors du téléversement d’un document qu’il soit audio, vidéo, image ou textuel ; un seul document ne peut être lié à un article dit "média" ;
Sur d’autres sites (8230)
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Four Trends Shaping the Future of Analytics in Banking
27 novembre 2024, par Daniel Crough — Banking and Financial ServicesWhile retail banking revenues have been growing in recent years, trends like rising financial crimes and capital required for generative AI and ML tech pose significant risks and increase operating costs across the financial industry, according to McKinsey’s State of Retail Banking report.
Today’s financial institutions are focused on harnessing AI and advanced analytics to make their data work for them. To be up to the task, analytics solutions must allow banks to give consumers the convenient, personalised experiences they want while respecting their privacy.
In this article, we’ll explore some of the big trends shaping the future of analytics in banking and finance. We’ll also look at how banks use data and technology to cut costs and personalise customer experiences.
So, let’s get into it.
This doesn’t just represent a security risk, it also impacts the usability for both customers and employees. Does any of the following sound familiar ?
- Only specific senior employees know how to navigate the software to generate custom reports or use its more advanced features.
- Customer complaints about your site’s usability or online banking experience are routine.
- Onboarding employees takes much longer than necessary because of convoluted systems.
- Teams and departments experience ‘data siloing,’ meaning that not everyone can access the data they need.
These are warning signs that IT systems are ready for a review. Anyone thinking, “If it’s not broken, why fix it ?” should consider that legacy systems can also present data security risks. As more countries introduce regulations to protect customer privacy, staying ahead of the curve is increasingly important to avoid penalties and litigation.
And regulations aren’t the only trends impacting the future of financial institutions’ IT and analytics.
4 trends shaping the future of analytics in banking
New regulations and new technology have changed the landscape of analytics in banking.
New privacy regulations impact banks globally
The first major international example was the advent of GDPR, which went into effect in the EU in 2018. But a lot has happened since. New privacy regulations and restrictions around AI continue to roll out.
- The European Artificial Intelligence Act (EU AI Act), which was held up as the world’s first comprehensive legislation on AI, took effect on 31 July 2024.
- In Europe’s federated data initiative, Gaia-X’s planned cloud infrastructure will provide for more secure, transparent, and trustworthy data storage and processing.
- The revised Payment Services Directive (PSD2) makes payments more secure and strengthens protections for European businesses and consumers, aiming to create a more integrated and efficient payments market.
But even businesses that don’t have customers in Europe aren’t safe. Consumer privacy is a hot-button issue globally.
For example, the California Consumer Privacy Act (CCPA), which took effect in January, impacts the financial services industry more than any other. Case in point, 34% of CCPA-related cases filed in 2022 were related to the financial sector.
California’s privacy regulations were the first in the US, but other states are following closely behind. On 1 July 2024, new privacy laws went into effect in Florida, Oregon, and Texas, giving people more control over their data.
One typical issue for companies in the banking industry is that their privacy measures regarding user data collected from their website are much less lax than those in their online banking system.
It’s better to proactively invest in a privacy-centric analytics platform before you get tangled up in a lawsuit and have to pay a fine (and are forced to change your system anyway).
And regulatory compliance isn’t the only bonus of an ethical analytics solution. The right alternative can unlock key customer insights that can help you improve the user experience.
The demand for personalised banking services
At the same time, consumers are expecting a more and more streamlined personal experience from financial institutions. 86% of bank employees say personalisation is a clear priority for the company. But 63% described resources as limited or only available after demonstrating clear business cases.
McKinsey’s The data and analytics edge in corporate and commercial banking points out how advanced analytics are empowering frontline bank employees to give customers more personalised experiences at every stage :
- Pre-meeting/meeting prep : Using advanced analytics to assess customer potential, recommend products, and identify prospects who are most likely to convert
- Meetings/negotiation : Applying advanced models to support price negotiations, what-if scenarios and price multiple products simultaneously
- Post-meeting/tracking : Using advanced models to identify behaviours that lead to high performance and improve forecast accuracy and sales execution
Today’s banks must deliver the personalisation that drives customer satisfaction and engagement to outperform their competitors.
The rise of AI and its role in banking
With AI and machine learning technologies becoming more powerful and accessible, financial institutions around the world are already reaping the rewards.
McKinsey estimates that AI in banking could add $200 to 340 billion annually across the global banking sector through productivity gains.
- Credit card fraud prevention : Algorithms analyse usage to flag and block fraudulent transactions.
- More accurate forecasting : AI-based tools can analyse a broader spectrum of data points and forecast more accurately.
- Better risk assessment and modelling : More advanced analytics and predictive models help avoid extending credit to high-risk customers.
- Predictive analytics : Help spot clients most likely to churn
- Gen-AI assistants : Instantly analyse customer profiles and apply predictive models to suggest the next best actions.
Considering these market trends, let’s discuss how you can move your bank into the future.
Using analytics to minimise risk and establish a competitive edge
With the right approach, you can leverage analytics and AI to help future-proof your bank against changing customer expectations, increased fraud, and new regulations.
Use machine learning to prevent fraud
Every year, more consumers are victims of credit and debit card fraud. Debit card skimming cases nearly doubled in the US in 2023. The last thing you want as a bank is to put your customer in a situation where a criminal has spent their money.
This not only leads to a horrible customer experience but also creates a lot of internal work and additional costs.Thankfully, machine learning can help identify suspicious activity and stop transactions before they go through. For example, Mastercard’s fraud prevention model has improved fraud detection rates by 20–300%.
Implementing a solution like this (or partnering with credit card companies who use it) may be a way to reduce risk and improve customer trust.
Foresee and avoid future issues with AI-powered risk management
Regardless of what type of financial products organisations offer, AI can be an enormous tool. Here are just a few ways in which it can mitigate financial risk in the future :
- Predictive analytics can evaluate risk exposure and allow for more informed decisions about whether to approve commercial loan applications.
- With better credit risk modelling, banks can avoid extending personal loans to customers most likely to default.
- Investment banks (or individual traders or financial analysts) can use AI- and ML-based systems to monitor market and trading activity more effectively.
Those are just a few examples that barely scratch the surface. Many other AI-based applications and analytics use cases exist across all industries and market segments.
Protect customer privacy while still getting detailed analytics
New regulations and increasing consumer privacy concerns don’t mean banks and financial institutions should forego website analytics altogether. Its insights into performance and customer behaviour are simply too valuable. And without customer interaction data, you’ll only know something’s wrong if someone complains.
Fortunately, it doesn’t have to be one or the other. The right financial analytics solution can give you the data and insights needed without compromising privacy while complying with regulations like GDPR and CCPA.
That way, you can track usage patterns and improve site performance and content quality based on accurate data — without compromising privacy. Reliable, precise analytics are crucial for any bank that’s serious about user experience.
Use A/B testing and other tools to improve digital customer experiences
Personalised digital experiences can be key differentiators in banking and finance when done well. But there’s stiff competition. In 2023, 40% of bank customers rated their bank’s online and mobile experience as excellent.
Improving digital experiences for users while respecting their privacy means going above and beyond a basic web analytics tool like Google Analytics. Invest in a platform with features like A/B tests and user session analysis for deeper insights into user behaviour.
Behavioural analytics are crucial to understanding customer interactions. By identifying points of friction and drop-off points, you can make digital experiences smoother and more engaging.
Matomo offers all this and is a great GDPR-compliant alternative to Google Analytics for banks and financial institutions.
Of course, this can be challenging. This is why taking an ethical and privacy-centric approach to analytics can be a key competitive edge for banks. Prioritising data security and privacy will attract other like-minded, ethically conscious consumers and boost customer loyalty.
Get privacy-friendly web analytics suitable for banking & finance with Matomo
Improving digital experiences for today’s customers requires a solid web analytics platform that prioritises data privacy and accurate analytics. And choosing the wrong one could even mean ending up in legal trouble or scrambling to reconstruct your entire analytics setup.
Matomo provides privacy-friendly analytics with 100% data accuracy (no sampling), advanced privacy controls and the ability to run A/B tests and user session analysis within the same platform (limiting risk and minimising costs).
It’s easy to get started with Matomo. Users can access clear, easy-to-understand metrics and plenty of pre-made reports that deliver valuable insights from day one. Form usage reports can help banks and fintechs identify potential issues with broken links or technical glitches and reveal clues on improving UX in the short term.
Over one million websites, including some of the world’s top banks and financial institutions, use Matomo for their analytics.
Start your 21-day free trial to see why, or book a demo with one of our analytics experts.
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swscale/aarch64 : add hscale specializations
26 mai 2022, par Swinney, Jonathanswscale/aarch64 : add hscale specializations
This patch adds code to support specializations of the hscale function
and adds a specialization for filterSize == 4.ff_hscale8to15_4_neon is a complete rewrite. Since the main bottleneck
here is loading the data from src, this data is loaded a whole block
ahead and stored back to the stack to be loaded again with ld4. This
arranges the data for most efficient use of the vector instructions and
removes the need for completion adds at the end. The number of
iterations of the C per iteration of the assembly is increased from 4 to
8, but because of the prefetching, there must be a special section
without prefetching when dstW < 16.This improves speed on Graviton 2 (Neoverse N1) dramatically in the case
where previously fs=8 would have been required.before : hscale_8_to_15__fs_8_dstW_512_neon : 1962.8
after : hscale_8_to_15__fs_4_dstW_512_neon : 1220.9Signed-off-by : Jonathan Swinney <jswinney@amazon.com>
Signed-off-by : Martin Storsjö <martin@martin.st> -
Live stream doesn't seem to be passed to AWS correctly
12 août 2024, par NoobAmII'm trying to stream my live video into Amazon IVS and I don't see it on the live channels.


Is it possible I have a mistake in my FFMPEG configuration ?
I'm expecting to see this in my playback url or on the console screen for playback but I see nothing at the moment.


As I understand it, shouldn't I see some kind of playback in the live channels if a stream is being sent that channel ?


` async sendDataToIvs(channelArn: string, payload: any): Promise<void> {
 const injestServer = '***.global-contribute.live-video.net';
 const streamKey = 'sk_us-east-1_*****';
 
 const ffmpeg = spawn('ffmpeg', [
 '-re', // Read input at native frame rate
 '-i', '-', // Input from stdin (live stream data)
 '-r', '30', // Frame rate
 '-c:v', 'libx264', // Video codec - H.264
 '-pix_fmt', 'yuv420p', // Pixel format
 '-profile:v', 'main', // H.264 profile
 '-preset', 'veryfast', // Encoder quality setting
 '-x264opts', 'nal-hrd=cbr:no-scenecut', // Additional x264 options
 '-minrate', '3000', // Minimum bitrate
 '-maxrate', '3000', // Maximum bitrate
 '-g', '60', // GOP size
 '-c:a', 'aac', // Audio codec
 '-b:a', '160k', // Audio bitrate
 '-ac', '2', // Audio channels
 '-ar', '44100', // Audio sample rate
 '-f', 'flv', // Output format
 `rtmps://${injestServer}:443/app/${streamKey}` // Output destination
 ]);
 
 ffmpeg.stdin.write(payload, (err) => {
 console.log(payload)
 if (err) console.error('Error writing payload to FFmpeg stdin:', err);
 });
 
 ffmpeg.on('close', (code) => {
 console.log(`FFmpeg process exited with code ${code}`);
 });
 
 ffmpeg.stdin.on('error', (err) => {
 console.error('Error writing to FFmpeg stdin:', err);
 });
 
 ffmpeg.stderr.on('data', (data) => {
 console.error(`FFmpeg error: ${data}`);
 });
 } `
</void>

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