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Shorten your trade reporting and compliance cycles from weeks to SECONDS with Blockhouse AI. Check out our live demo @ www.blockhouse.app 👇

When implemented well (with a lot of great, relevant data) AI can be a surprisingly useful tool for financial institutions. https://buff.ly/4e0dDcG #creditunions #communitybanks #branchandATMlocators #fintech

When implemented well (with a lot of great, relevant data) AI can be a surprisingly useful tool for financial institutions. https://buff.ly/4e0dDcG #creditunions #communitybanks #branchandATMlocators #fintech

Private markets infrastructure is unscalable because it is full of manual operations. We think AI agents can help to solve this from onboarding to fund accounting and treasury services. Here's a simple example of how agents can clear LPs through KYC/AML & accreditation from our CTO Tushar Nair. If you're a GP looking to use advancement in AI to scale your AUM and/or LP base while cutting or maintaining your current cost basis, let's chat. #aiagents #fundadministration #ai #appliedai #fintech

One of the really fun things about my conversation with David Haber at the Israeli Fintech Founder breakfast we co-hosted at the Andreessen Horowitz office in NYC was that both of us come from an operator background (our companies even competed for a short while) so we got to cover not just macro topic but also some lessons from starting and operating successful fintechs as well. We promised some highlights, so here they are: 1. As a fintech infrastructure provider (e.g. Plaid), the more fragmented data sources you bring together, the stronger the moat you build. This doesn't just have to do with numbers, but also with how these sources are distributed in terms of relevance for your customers (e.g. how long the long tail is). 2. Many fintech products have inherent conversion penalties (e.g. approval rates in credit, insurance, etc.) That's why for your learning, it's often better if possible to start with a software product that allows you to get wider distribution at a lower CAC, and expand using financial services. 3. There's a crawl-walk-run approach to selling AI into financial institutions, where you start with streamlining manual labor (e.g. extracting data from unstructured docs), graduate to decision support using data compilation and recommendation, then once you built trust, move to owning the decision yourself.

Many financial institutions are still solely relying on traditional rules-based transaction monitoring systems. To make sure they’re monitoring transactions as efficiently and effectively as possible, they cast a wide net of rules to not miss anything, which generates high alert volumes and exceptionally high false-positive rates. That’s time-consuming and expensive. You need assistance in aggregating the vast amount of data and supporting documentation in case management systems, so we built Isaac. He’s an AI Transaction Monitoring Investigator who assists with transaction monitoring alert management by using machine learning capabilities to work first-level alerts. He’s easy to work with and even easier to hire. Click here to get him on board: https://bit.ly/45dON3D #digitalworkers #futureofwork #automation #intelligentautomation #artificialintelligence #fintech #fincrime #amlcompliance #transactionmonitoring

I've recently going through Algorithmic Trading Platforms to build one for one of clients, and have some concerns to share and few queries. My journey, while innovative and exciting, has also been clouded by a notable lack of transparency, especially concerning back-testing data. It's vital for platforms to provide such data so users can gauge the reliability and potential performance of trading algorithms. However, what's more concerning is that many platforms do not share their back-testing results, leaving us in the dark about the risks and efficiencies of the algorithms. This opacity doesn't just raise questions about performance but also about the trustworthiness and ethical standards of these platforms. This brings me to an important query: Are there specific SEBI guidelines that govern the disclosure of algorithmic back-testing data? How can investors and traders ensure they are not stepping into poorly regulated or opaque waters? Tried to search a lot on these guidelines, but could not find any. Pls suggest some articles or suitable links to work on the guidelines if any. #AlgorithmicTrading #Fintech #Transparency #SEBIGuidelines #EthicalInvesting

I've recently going through Algorithmic Trading Platforms to build one for one of clients, and have some concerns to share and few queries. My journey, while innovative and exciting, has also been clouded by a notable lack of transparency, especially concerning back-testing data. It's vital for platforms to provide such data so users can gauge the reliability and potential performance of trading algorithms. However, what's more concerning is that many platforms do not share their back-testing results, leaving us in the dark about the risks and efficiencies of the algorithms. This opacity doesn't just raise questions about performance but also about the trustworthiness and ethical standards of these platforms. This brings me to an important query: Are there specific SEBI guidelines that govern the disclosure of algorithmic back-testing data? How can investors and traders ensure they are not stepping into poorly regulated or opaque waters? Tried to search a lot on these guidelines, but could not find any. Pls suggest some articles or suitable links to work on the guidelines if any. #AlgorithmicTrading #Fintech #Transparency #SEBIGuidelines #EthicalInvesting

Never search for a consent form again! 📝 With PineappleONE, managing your deals is a breeze. Our secure digital vault automatically syncs consent forms with applications, making access easy. Stay compliant with automatic notifications for missing conditions, saving you time and letting you focus on growing your business and enjoying life. PineappleONE simplifies deal management, giving you more time for what truly matters. #MortgageTech #Fintech #PineappleONE #DealManagement #pineapple #pineapplemortgage #pineappletechnology #technology #ai #BusinessGrowth #Efficiency #Compliance #DigitalTransformation

(Fintech Takes 3-2-1 Newsletter) STORY #1 A group of Senators and Representatives in the U.S. Congress are proposing a new law: 🔹 A bipartisan group of members unveiled legislation that would direct federal financial regulators to create “regulatory sandboxes” for financial firms to experiment with artificial intelligence. 🔹 Led by Sens. Mike Rounds (R-S.D.) and Martin Heinrich (D-N.M.) plus Reps. French Hill (R-Ark.) and Ritchie Torres (D-N.Y.), the bill is titled the Unleashing AI Innovation in Financial Services Act. 🔹 This sandbox bill from Rounds, Heinrich, Hill and Torres would allow firms to apply and “experiment with AI test projects without unnecessary or unduly burdensome regulation or expectation of retroactive enforcement actions.” 🔹 That application would let firms request that compliance with specific regulations be “waived or modified.” Companies could also propose an “alternative method” for complying with existing regulations. 🔹 Companies would need to demonstrate their project wouldn’t present a “systemic risk” to the U.S. financial system and comply with anti-money laundering laws. Source: Alex Johnson #FinancialServices #financialfirms #aisandbox #sandbox #ai #aitestprojects #regulations #airegulations #regulatorycompliance #compliance #Buckler #governance #riskmanagement #systemicrisk #regulatoryexpectations https://lnkd.in/eXjQqrEU