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Anyone can fund deals, but how is your portfolio performance? AdvanceIQ.ai integrates PortIQ with LendSaaS to give MCA and RBF funders live portfolio intelligence and risk analytics. Details: wix.to/KSVkBwA #Fintech #RiskAnalytics #LendSaaS

We are delighted to host Reny Mustikawati โ€” Head of Risk Analytics MIS & Regulatory Reporting at Atome, as an ๐—˜๐˜€๐˜๐—ฒ๐—ฒ๐—บ๐—ฒ๐—ฑ ๐—ฆ๐—ฝ๐—ฒ๐—ฎ๐—ธ๐—ฒ๐—ฟ ๐—ฎ๐˜ ๐—–๐—ฟ๐—ฒ๐—ฑ๐—ถ๐˜ & ๐—–๐—ผ๐—น๐—น๐—ฒ๐—ฐ๐˜๐—ถ๐—ผ๐—ป๐˜€ ๐—ฆ๐˜‚๐—บ๐—บ๐—ถ๐˜ ๐—”๐˜€๐—ถ๐—ฎ ๐Ÿฎ๐Ÿฌ๐Ÿฎ๐Ÿฒ, with CBI Credit Bureau Indonesia as the Official Partner. At Atome, where millions of transactions move across consumers, merchants, and markets, Reny Mustikawati plays a pivotal role in turning data into directionโ€”shaping how ๐—ฟ๐—ถ๐˜€๐—ธ, ๐—ฟ๐—ฒ๐—ฝ๐—ผ๐—ฟ๐˜๐—ถ๐—ป๐—ด, ๐—ฎ๐—ป๐—ฑ ๐—ฝ๐—ผ๐—ฟ๐˜๐—ณ๐—ผ๐—น๐—ถ๐—ผ ๐—ฝ๐—ฒ๐—ฟ๐—ณ๐—ผ๐—ฟ๐—บ๐—ฎ๐—ป๐—ฐ๐—ฒ come together in real time. Her expertise across ๐—ฎ๐—ป๐—ฎ๐—น๐˜†๐˜๐—ถ๐—ฐ๐˜€, ๐—ด๐—ผ๐˜ƒ๐—ฒ๐—ฟ๐—ป๐—ฎ๐—ป๐—ฐ๐—ฒ, ๐—ฎ๐—ป๐—ฑ ๐—ฐ๐—ผ๐—น๐—น๐—ฒ๐—ฐ๐˜๐—ถ๐—ผ๐—ป ๐˜€๐˜๐—ฟ๐—ฎ๐˜๐—ฒ๐—ด๐˜† enables smarter decision-making at scaleโ€”supporting a business model built on speed, flexibility, and access. With a strong focus on aligning risk with growth, she brings a perspective grounded in executionโ€”where insights donโ€™t just inform strategy, they drive it. Step into the thinking behind scalable, data-led lending ecosystems. ๐—๐—ผ๐—ถ๐—ป ๐˜‚๐˜€ ๐Ÿฎ๐Ÿญ๐˜€๐˜โ€“๐Ÿฎ๐Ÿฎ๐—ป๐—ฑ ๐—๐˜‚๐—น๐˜† ๐Ÿฎ๐Ÿฌ๐Ÿฎ๐Ÿฒ ๐—ฎ๐˜ ๐—›๐—ผ๐—น๐—ถ๐—ฑ๐—ฎ๐˜† ๐—œ๐—ป๐—ป & ๐—ฆ๐˜‚๐—ถ๐˜๐—ฒ๐˜€, ๐—๐—ฎ๐—ธ๐—ฎ๐—ฟ๐˜๐—ฎ. ๐—ฅ๐—ฒ๐—ด๐—ถ๐˜€๐˜๐—ฒ๐—ฟ ๐˜๐—ผ๐—ฑ๐—ฎ๐˜†: asia.collectionsummit.com/ #CreditCollectionsSummitAsia #RiskAnalytics #DataDriven #BNPL #FinTech #CollectionsStrategy #Leadership #JakartaEvents #FutureOfFinance
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๐ŸŽฅ Watch the teaser. Then join 100 lending, risk, and collections leaders in Bangalore. Save your spot - lnkd.in/d4bxyf7x Website - lnkd.in/d5gw2GTD #RiskAnalytics #CollectionsInnovation #FintechIndia #AIinLending #DigitalCollections #BangaloreEvents #CreditRisk
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FY26 Banking Fraud Snapshot: โ€ข Cases โ†“ 57% โ€ข Amount โ†‘ 46% โ€ข โ‚น48,021 Cr involved โ€ข Advances frauds contributed 85% of total value An important shift in India's banking risk landscape. - RBI Annual Report 2025-26 #RBI #Banking #RiskAnalytics #FinancialResearch
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Most people trying to break into Capital Markets donโ€™t understand how trades actually move. And thatโ€™s exactly why they fail interviews. Banks expect you to already understand: โ€ข trade lifecycle โ€ข systems โ€ข risk โ€ข execution flow That gap is expensive. ๐Ÿ‘‰ ebooks.mdmarketinsights.com/ #MDMarketInsights #CapitalMarkets #BusinessAnalysis #FrontOffice #TradingSystems #FinanceCareers #TradeLifecycle #RiskManagement #FinancialMarkets #FinTech #CareerGrowth #CareerTransition #ProfessionalDevelopment #BreakIntoFinance #CapitalMarketsTraining #FrontOfficeBA #TradingCareers #RiskAnalytics #FinancialEngineering #FinanceEducation
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The #2ndixglendtech is coming to Bangalore. 100 leaders. Real case studies. Awards. Don't miss it. ๐Ÿ‘‰ Save your spot - lnkd.in/d4bxyf7x #ilendtechseries #LendTech #Collections #RiskAnalytics #Fintech #Bangalore #AIinRisk #DigitalCollections #NBFCs #LendTechAwards
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๐Ÿšจ 90% of Data Analyst Interviews Repeat the Same Questions - But Most Candidates Still Walk In Unprepared. After years working as a Data Analyst, Power BI Developer, Data Engineer and Automation Expert - across Gold Standard Consulting Firms, Fintech, and Enterprise Environments, Iโ€™ve noticed something interesting: ๐Ÿ‘‰ Interview questions change slightlyโ€ฆ ๐Ÿ‘‰ But the core evaluation NEVER changes. Companies are testing 3 things: โœ… Can you think analytically under pressure? โœ… Can you translate business problems into data solutions? โœ… Can you communicate insights to decision makers? The difference between average candidates and top performers is simple: Preparation with intention. So Iโ€™ve compiled 50 real interview questions Iโ€™ve personally encountered or seen used repeatedly across analytics, BI, and risk/data roles. ๐Ÿ”ฅ50 Data Analyst Interview Questions You Should Be Ready For 1. Introduce yourself 2. โ What are historical and transactional data. 3. โ Different types of schemas in Data Warehousing. 4. โ What is Filter and Row context. 5. โ Partitioning and Indexing in SQL. The types and what they are used for. 6. โ Explain Inactive, Active and Churn Customers. 7. โ What do you do when the head of an organization like the C level are not interested in your BI. 8. โ Biggest challenge youโ€™ve faced and how did you overcome it. 9. โ What other tools do you use asides Power BI. 10. โ How do you test for Accuracy in your BI. 11. โ How do you do your ETL. 12. โ Explain KPIs and Metrix. 13. โ Which other tools can you do your ETL on. 14. โ What storage is your DAX stored on. 15. โ What is DAX and M Code. 17. Difference between OLAP and OLTPโ€ฆ. Also when do you use them ? 18. โ Tell us what you know about our organization 19. Youโ€™re asked to present your findings to execs. How do you simplify your insights? 20. What is a Risk Score, and how would you calculate it? 21. Explain the difference between logistic regression and decision trees for a non-technical stakeholder. 22. A senior executive tells you your report must show improvement in risk KPIs but your analysis shows the opposite. What do you do? 23. How do you maintain data security and privacy while working with customer data from home? 24. Have you ever worked remotely with stakeholders across time zones? How did you ensure effective collaboration and communication? 25. Imagine you find that most defaults come from applicants under 25 with a credit score under 600. What action would you recommend to the risk team? 26. Whatโ€™s your process for dealing with dirty or incomplete financial datasets? 27. What are your most used DAX queries or measures 28. Letโ€™s get technical. How would you calculate the default rate in SQL using a loans table with a default_flag column? 29. Tell me about a time you analyzed risk data and your findings influenced a business decision. 30. Can you walk me through your background and why you're interested in this role? 31. Can you share your experience working with cross-functional teams ? 32. How do you ensure security and compliance while handling sensitive risk data ? 33. Describe a time you had to analyze data that contradicted management's expectations. 34. Youโ€™re working remotely and need urgent data from another team thatโ€™s unresponsive. How do you handle it? 35. How would you monitor fraud using data? 36. What do you think are key risks in financial services that a data analyst should help monitor? 37. How would you handle missing or incomplete data in a financial dataset? 38. Whatโ€™s the difference between correlation and causation? Why does it matter in risk analytics? 39. How would you approach building a risk scoring model from scratch? 40. How do you prioritize tasks when working on multiple datasets or requests? 41. How do you explain technical insights to non-technical stakeholders? 42. How comfortable are you with SQL? Can you write a query to find customers with overdue loans greater than 30 days? 43. How comfortable are you with SQL? Can you write a query to find active customers for the last 30 days? 44. How do you ensure data quality before analysis? 45. What KPIs would you track in a risk analytics dashboard? 46. Can you describe a project where you worked with risk data? 47. How do you calculate agent sales percentage ? 48. How do you forecast sales both on Power BI and Excel and see the forecast figures ?? 49. How do you calculate running total of sales by date ? 50. Lastly, do you have any questions for us about the role or company? ๐Ÿ’กPro Tip: Most analysts over-focus on tools (Power BI, SQL, Excel, Python). But senior roles are won through: ๐Ÿ‘‰ Business thinking ๐Ÿ‘‰ Stakeholder communication ๐Ÿ‘‰ Risk awareness ๐Ÿ‘‰ Decision-making storytelling Technical skills get you shortlisted. Strategic thinking gets you hired. If youโ€™re preparing for interviews right now: Save this. Study it. Practice explaining answers OUT LOUD. Your future self will thank you. #DataAnalytics #PowerBI #DataAnalyst #Excel #SQL #BusinessIntelligence #CareerGrowth #RiskAnalytics
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we ask: "Under what conditions WILL they repay?" That changes: โ€ข pricing โ€ข insurance design repayment schedules Risk doesn't disappear It becomes measurable. #Banking #RiskAnalytics #CreditScoring
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Liquidations tell the truth before price does. AIW3โ€™s Total Liquidations ยท Liquidation Heatmap visualizes where forced exits concentrate across the market โ€” in real time, on-chain. See: โ€ข Where leverage is overcrowded โ€ข Which price zones carry cascading risk โ€ข How liquidation pressure reshapes market structure This isnโ€™t just data. Itโ€™s execution intelligence for strategy builders. #AIW3 #LiquidationHeatmap #OnChainData #Perps #DeFi #RiskAnalytics
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