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Clarity on constantlyevolving Business DynamicsData backed decisionsare more contemplativeand thus wiserData Disabled Deci...
AgendaAbout the CompanyCapabilities and Services Predictive Analytics Solutions Other Services Descriptive Analytics So...
About the Company4Copyright © Gmid Associates.Experienced Team –Professionals with decades ofInternational ExperienceDeliv...
Gmid Associates has a global footprint5Copyright © Gmid Associates.HQGmid Rep officeTie ups/networksCaliforniaLondonAustra...
Services6Copyright © Gmid Associates.
Analytics is at the core of banking7Copyright © Gmid Associates.IdentificationValidationAuthentication
Predictive Analytics Solutions8Copyright © Gmid Associates.Using statistical techniques –Regression, Time Series, Neural M...
Descriptive Analytics Solutions9Copyright © Gmid Associates.Use statistical clustering schemes, econometric techniques an...
•We help organizations transform and combine disparate data, remove inaccuracies,standardize on common values, parse value...
MIS/ Dashboards/ Simulation Tools11Copyright © Gmid Associates. Measure efficiencies/inefficiencies Ability to identify ...
Case Studies12Copyright © Gmid Associates.
Outline BenefitsProject DescriptionMonthly defaultprediction modelsfor active Auto Loanportfolio After implementing themo...
Outline BenefitsProject DescriptionCollection Scorecardsand Strategy for RetailBank Write-off losses downby 4% within six...
Outline BenefitsProject DescriptionDe-duplication ofRecords on a MultiProduct FinancialPortfolio The client was able tokn...
Thank YouMudit ChandraSales and Marketing HeadGmid AssociatesMobile Number+91-98107-96148Emailmudit.chandra@thegmid.comWeb...
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Gmid associates services portfolio bank

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Gmid associates services portfolio bank

  1. 1. Clarity on constantlyevolving Business DynamicsData backed decisionsare more contemplativeand thus wiserData Disabled DecisionsData Powered DecisionsThe Power of Analytics…2Copyright © Gmid Associates.
  2. 2. AgendaAbout the CompanyCapabilities and Services Predictive Analytics Solutions Other Services Descriptive Analytics Solutions Data Mining & Cleansing MIS / Executive Dashboard/ Simulation ToolsRelevant Case Studies3Copyright © Gmid Associates.
  3. 3. About the Company4Copyright © Gmid Associates.Experienced Team –Professionals with decades ofInternational ExperienceDelivery Across theGlobe – Analytics PartnerBest Talent –Graduates from IITs, IIMs, ISIIndustry Knowhow –Complete Lifecycle of Industry
  4. 4. Gmid Associates has a global footprint5Copyright © Gmid Associates.HQGmid Rep officeTie ups/networksCaliforniaLondonAustraliaDelhiMumbaiBangaloreNew Jersey
  5. 5. Services6Copyright © Gmid Associates.
  6. 6. Analytics is at the core of banking7Copyright © Gmid Associates.IdentificationValidationAuthentication
  7. 7. Predictive Analytics Solutions8Copyright © Gmid Associates.Using statistical techniques –Regression, Time Series, Neural Models etc. on historical information, one canaccurately predict the outcomes of future events and use this information to plan preemptivelyModel Development Framework% Population0%10%20%30%40%50%60%70%80%90%100%0% 20% 40% 60% 80% 100% ofDelinquent80% lift!Model Validation ChartMaximize the divergence between the distributions oftarget / non target (good / bad) accountsEstimate the unknown population characteristics based onsample informationUse propensity scores to calculate probabilities of default,expected loss, intentional fraud etc.Maximize revenues, rationalize expenses.
  8. 8. Descriptive Analytics Solutions9Copyright © Gmid Associates.Use statistical clustering schemes, econometric techniques and overlay with business inputs to group‘identical accounts’ from a pool of customer population and create targeted segments for focusedtreatmentUse segmentation solutions to optimally allocate marketing budgets, increase customer service levels andloyalty, manage bad debts and maximize collections
  9. 9. •We help organizations transform and combine disparate data, remove inaccuracies,standardize on common values, parse values and cleanse dirty data to create consistent,reliable informationData Cleansing and Enrichment•Your customer contact numbers are buried in a dataset that has all sorts of text entries.This makes contactability on those datasets very difficult•We have tools that dig valid phone numbers from deep into the text data, intelligentenough to complete incomplete numbers (i.e. adding STD codes)•Tools can be customized to suit your business requirementsContactability Improvement Tools•We have proven tools and expertise to run customer de-duplication algorithms on data,identifying unique customers/ households/ relationships and establishing mappingsamongst them•This helps you understand your customer data, draw critical conclusions and makemeaningful business decisionsData De-duplication SolutionsData Mining & Data Cleansing10Copyright © Gmid Associates.
  10. 10. MIS/ Dashboards/ Simulation Tools11Copyright © Gmid Associates. Measure efficiencies/inefficiencies Ability to identify and correct negative trends Ability to generate new business opportunities Align strategies and organizational goals Save time over running multiple reports Gain total visibility of all systems instantlyEnables better decisionsmaking by buildingmonitoring systems that are :• Real time,• Correct, and• EfficientWe use advanced Analytical techniques to make sure that thetechniques which best captures the business problem is used. Theoutcome algorithm is built into scenario analyzer tools.Ability to make more informed decisions based oncollected business intelligence
  11. 11. Case Studies12Copyright © Gmid Associates.
  12. 12. Outline BenefitsProject DescriptionMonthly defaultprediction modelsfor active Auto Loanportfolio After implementing themodel, the monthlydefault rates are down by16% A 100 year old leading vehicle finance company from US with a sub primeportfolio wanted to make scientific and optimal collection strategies. We developed an early warning delinquency predictor scorecard on theportfolio and implemented the same on the client’s system. The scorecardruns on the last day of every month and gives scores to all the accountsbased on their propensity to default on the payments in the next month. Italso categories the accounts into risk segments, using which the companycan make effective, targeted collection strategies‘Bad’ ApplicationPrediction system forUS Auto Financecompany Early Write off losseshave gone down by 12%within 4 months ofmodel implementation A leading auto finance company from Texas wanted to devise effectivestrategies to separate good applications from bad ones to improve theportfolio quality and minimize future credit losses We developed two predictive scorecards- write off prediction and early payoff prediction. Since both of these were loss making scenarios for thebusiness, we clubbed them together and devised “high/ Medium/Low” riskbands. Every application is given scores and risk segment and businessmakes effective acquisition strategiesCase Studies: Predictive Analytics13Cross-sell Strategies ona diversified financialportfolio Cross-sell penetrationincreased from ~1% to~4% on a base of2,50,000 accounts in 8months time afterimplementation A global financial services firm needed to develop effective and easilyimplementable cross-sell strategies on a diversified portfolio containingmutual funds, life insurance, general insurance and mortgage loans Developed multiple statistical models and used clustering techniques,overlaid with business rules to design efficient cross-sell strategiesCopyright © Gmid Associates.
  13. 13. Outline BenefitsProject DescriptionCollection Scorecardsand Strategy for RetailBank Write-off losses downby 4% within sixmonths. Impact in therange of $5million South India’s leading bank wanted to put in place a centralized collectionssystem powered by predictive analytics. Two statistical models were developed- first on the current portfolio topredict potential payment default cases and second, a payment predictionmodel on the 90+ DPD portfolio. Segmentation and collection strategy put in place to run preventivecampaigns in order to minimize delinquencies at lowest expensesCase Studies: Predictive Analytics14Copyright © Gmid Associates.Churn PredictionScorecards for USTelecom Major 85% potential churnscaptured in top 20%‘risky’ population 15days in advance Churn rates down by 7% One of the world’s largest Telcos wanted to replace their existing churnprediction system with a better quality product to arrest increasing churn intheir consumer and business portfolio Two fold problem description- early identification of subscribers most likelyto churn, identification of important factors driving the churn. Developed predictive models to aid in churn prevention campaigns. Ranstatistical tests to identify most important variables that affect churnbehaviour.Sales Forecast Modelfor world’s biggestfancy dress e-retailer 80% accurate forecastfigures within 3 monthsof model deployment Increased service level byabout 41% The client, a large textile manufacturer in UK, wanted to build a reliablemodel that complements or takes over their in house traditional approach toforecasting primarily driven by gut instinct. Developed a multi variable time series forecasting model for all of theproduct categories. The model uncovered patterns caused by seasonalvariations, lead times, minimum quantities, re-order quantities,extraordinary usage (special orders) etc.
  14. 14. Outline BenefitsProject DescriptionDe-duplication ofRecords on a MultiProduct FinancialPortfolio The client was able toknow exactly how manycustomers it had As a result of customer-to-account mapping, theyare able to make betterinformed business plans A leading private sector Insurer was having troubles managing their datawarehouse (DW) because there was no unique identifier at client level. Everynew acquisition was a new relationship at DW level. Developed a de-dup algorithm by using matching algorithms like levenshteindistance, soundex, metaphone etc. Created a new client level UID.IntensityOptimization for aCards CollectionsCampaign• The collections unit wasable to reduce theircosts by 15% for thesame collectionrevenues. A multinational bank’s cards collection business needed help to identifyoptimum reach out intensity/ channel at bucket and segment levels. Using statistical and econometrics techniques on historical data, we devisedoptimum channels and intensities at bucket and segment levels.Data Cleansing on aLife Insuranceportfolio database• As a result of improvedcontactability, cross-sellswent up by 11% in ayear’s time Our client, a leading Insurer needed to increase phone numbercontactability on their database. The phone numbers were not in machinedialable format s hence dialer machines could not be used directly forcustomer reach out/ cross-sell/ renewal campaigns. Developed an algorithm which picks correct phone numbers from textstrings and modifies them into machine dialable format (adds std code onlandlines, if required). Automated it in an excel tool to be used onincremental data.Case Studies: Data Mining & Cleansing15Copyright © Gmid Associates.
  15. 15. Thank YouMudit ChandraSales and Marketing HeadGmid AssociatesMobile Number+91-98107-96148Emailmudit.chandra@thegmid.comWebwww.thegmid.comCopyright © Gmid Associates. 16

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