Effectiv

⚠️ Beware the Business Email Compromise Scam! ⚠️

𝐓𝐑𝐔𝐒𝐓 - {𝒏𝒐𝒖𝒏} - firm belief in the reliability, truth, or ability 🏗️ Building trust among employees, shareholders, and especially customers is paramount to the success of a company BUT... 🤷♂️ What happens when these groups become too trusting? Greed and corruption most likely Wirecard, for example, leveraged the trust of 👇 👤 𝗦𝗵𝗮𝗿𝗲𝗵𝗼𝗹𝗱𝗲𝗿𝘀 🕵️ 𝗖𝗼𝗺𝗽𝗹𝗶𝗮𝗻𝗰𝗲 𝘀𝗽𝗲𝗰𝗶𝗮𝗹𝗶𝘀𝘁𝘀 🏛️ 𝗚𝗲𝗿𝗺𝗮𝗻 𝗴𝗼𝘃𝗲𝗿𝗻𝗺𝗲𝗻𝘁 to commit unprecedented amounts of fraud... What is there to learn from this catastrophic collapse? -> That regulatory and compliance fraud is still prevalent -> That checks and balances are an essential part of business 💳 While Wirecard is an example of internal fraud, FinTech companies deal with frustrating amounts of external fraud each year as well... ...$51 Million worth 𝗽𝗲𝗿 𝗰𝗼𝗺𝗽𝗮𝗻𝘆, to be exact ⬇️ Common external fraud types include ⬇️ Payment fraud Loan fraud -𝙖𝙣𝙙 𝙤𝙛 𝙘𝙤𝙪𝙧𝙨𝙚- Account takeover fraud Leveraging the best tools in the marketplace to combat the top FinTech fraud methods can legitimately turn that $𝟱𝟭,𝟬𝟬𝟬,𝟬𝟬𝟬 number into nearly $𝟬. Best practices and strategies can be found by following the link in the comments👇

👏 Welcome to the team Chris, Swati, Rajneesh, and Abhishek!

🗣 Counterfeiting a check is much easier than one might think Taking a ✅ PROACTIVE instead of a ❌ REACTIVE approach by using real-time monitoring solutions can significantly improve the security of your customer's accounts Do not be naive in thinking your customer's bank information is 100% secure❗

Let's hear them 👇

🤖 Whether you’re an FI or fintech, no one wants to be the target of a cyberattack Such attacks are not only costly but damage years and years of customer trust 🤝 What's worse is that it's often one small mistake—such as an employee clicking a malicious link—that causes the breach… …and can lead to thousands of customer records hitting the dark web, and ultimately 👇 -> An uptick in synthetic identity fraud -> Unauthorized account takeover 🧠 As fraudsters arm themselves with more data, fraud fighters need to arm themselves with tools to stop bad actors How? 📱 Device behavior checks at the time of onboarding AND transaction 📩 Step-up liveness and document verification checks for medium and high-risk applicants 📈 Graph networks to detect anomalous behavior, such as geo-location distance between devices used at the time of application to the time of transaction Those are just a few… Just make sure the tool and team you’re working with is as passionate about stopping fraud as a dog is about chasing squirrels 🐶

🎉 Exciting News! We're proud to announce our partnership with pave.dev! Pave's real-time cashflow analytics + Effectiv's risk decisioning = smarter, more accurate underwriting decisioning❗ 👇 Put simply by the Pave Team 👇 With Effectiv + Pave.dev, lenders can: ✅ Backtest and optimize credit decisions with cashflow-driven champion-challenger models. ✅ Dynamically change rules using Pave’s Attributes and Scores within Effectiv’s drag-and-drop UI. ✅ Combine financial data from diverse sources to predict repayment behavior. 🔗 Link to read more is in the comments

🤔 Have you ever wondered how fraudsters turn synthetic IDs into real cash? With hundreds of thousands of account details leaked in the Evolve Bank & Trust data breach It is important to understand how fraudsters take advantage of this unfortunate opportunity 👇 #databreach #fraudsters #syntheticID

😞 By now you've probably heard about the Evolve Bank data breach... ...33TB's of data leaked including unfathomable amounts of PII What relevance does this have for FIs and Fintechs not affected by the breach? Surprisingly, a lot more than meets the 👁 Let me break it down for you 👇 Thanks to the breach, fraudsters now have: 👤 Name 📧 Email address 📱 Phone number 🔓 Account number on 155,586 accounts❗ By combining fake names with breached SSNs, synthetic IDs are created These synthetic IDs slowly build up a credit history and eventually pass for real people 🤷♂️ And there you have it, soon completely fabricated individuals are opening fraudulent credit cards and bank accounts Well...what's the solution? 👉 FIs and Fintechs need to implement multiple risk checks into their account opening flow, such as: -> Document verification + Liveness checks -> Validate SSN against gov databases -> Verify name match to address, email, and phone number -> Device checks for unusual behavior -> Credit bureau checks -> Anomaly detection and predictive modeling using ML 🟣 That’s where Effectiv comes in, pulling from all the data sources you need and decisioning each applicant in lock-step with the level of risk with which you are comfortable

Declining a safe transaction is similar to saying "better to be safe than sorry" 🤔 These same declines costing $443B/yr is a completely different story... False declines are not only a strong indicator of a weak fraud prevention strategy, they also 👇 -> Lead to high levels of customer churn. (38% of people switched merchants after experiencing a false decline) -> Damage future fraud prevention strategies due to bad data -> Damage merchant brand reputation Naturally, How can FIs and Fintechs find the balance between minimal and over-the-top transaction monitoring? While it is true that each will have to find their own happy medium, thanks to custom-trained ML models and drag-n-drop velocity + distance rules 👇 💡 Customizing a payment fraud solution has never been easier 🟣 Effectiv's platform enhances detection accuracy with ready-to-use and customizable ML models. It also supports back-testing and A/B testing for new rules, and offers thousands of pre-computed payment fraud rules for immediate deployment on day one. Find the right balance and build trust💪