U GRO Capital | An Overview August 2020 The Indian SME Lending - - PowerPoint PPT Presentation

U GRO Capital | An Overview

August 2020

The Indian SME Lending Market

A large yet untapped market opportunity

2

The Indian Government is looking to bolster the MSME sector to greatly increase financial inclusion | The MSME Credit Gap is a barrier to growth and inclusion in the MSME space | U GRO is targeting the Credit Gap using an innovative mix of Knowledge + Technology

3

Small Businesses in India Face a Severe Credit Availability Problem

60M

MSMEs in India

$560B

Gross Value Add

10%

MSMEs with Access to Credit

29%

(2019)

MSME Contribution to India’s GDP

50%

(Proj. 2024)

111M

(2019)

Number of People Employed by MSMEs in India

150M

(Proj. 2024)

The Government of India has proposed the above aggressive growth targets for the MSME space and has installed significant incentives for Indian MSMEs. These include a favorable tax regime, interest subvention, and the MUDRA and CGSTME schemes.

US$300 B | SME Credit Gap

20.1 23.7 45.0 2.9 0.7

Banks NBFCs Other institutions Total Formal Supply Total Addressable Demand

Potential Addressable Credit Gap: ₹ 21.3 T growing at 7%+ per annum

₹ T

Difficult to understand businesses/cash flows Fragmented set of customers High dependence on the ecosystem Lack of data

Challenges in lending to the SME segment…

High cost of customer acquisition

4

?

…leading to a Frustrating Borrowing Experience for Small Businesses

Time consuming

• ffline process

Non-tailored credit assessment Rigid collateral requirements Product mismatch

Traditional Lenders continue to find mid market and large corporate more rewarding – not necessarily true!!

Traditional Lenders remain unfocused on SMEs due to Business Model Diversity

Product

Customized products based on the nature of business, non-financial parameters, end use, payment capacity/ frequency of underlying customer Loans against property, supply chain financing, unsecured loans Loans against property, supply chain financing

Distribution

Omnichannel Ecosystem based lending Branch/DSA led Branch/DSA led

Credit Appraisal

Sector specific approach, Cash Flow Based Automated Review One size fits all Collateral/Bureau score One size fits all Collateral/Bureau score

Turn-Around Time

4-5 days 15-20 days 30-45 days

Documentation

Combining traditional and non- traditional sources. Use of information available in public and private domains. Digital document submission Financial Statements, P&L Account, Balance Sheets, Bank Statements Project Reports. Projected financials, Bank Statements.

5

Specialized SME Lenders Traditional NBFCs Banks

Specialized SME Lenders are Better Positioned to Bridge the SME Credit Gap

Technology is Essential to Achieve a Specialized Model at Scale

6

OPERATIONS CREDIT UNDERWRITING COLLECTIONS DISTRIBUTION

▪ Quick and easy integration with distribution partners ▪ Paperless login enabled by API integrations and OCR ▪ Lower turn-around time ▪ Faster product launches and process iterations ▪ Direct to customer interface and pre-approved programs ▪ Access and process the large trove of private and public data ▪ Centralize underwriting knowledge ▪ Customized scorecards ▪ Automate processes to reduce errors and increase throughput ▪ Access and analyze surrogate data ▪ Comprehensive notification/trigger mechanism for best-in-class client servicing ▪ Banking integration for automated disbursement, deductions ▪ Digital self service and support ▪ Digital process enablers such as eSign, eKYC, eStamping ▪ Processing at scale ▪ Automated, analytics led early warning systems ▪ Cash less EMI collections ▪ Geo-tagging of customers

Technology has created a new breed of fin-tech lenders in India | Digital lending to increase 10-15 times by 2023, scaling up to ~$100B in annual disbursements

| Better Assessment | Shorter TAT | Personalized Customer Journeys |

U GRO Lies at the Intersection of Technology Focused and Specialized NBFCs…

Fintech Platforms Specialized NBFCs

Sector Specialization Product Specialization Geographical Specialization Supply Chain Platforms Digital Lenders Off-Balance Sheet Lenders

U GRO intends to create a specialized, scalable platform optimized for end-to-end lending

7

▪ Scale a challenge ▪ Restricted to niches ▪ Opex heavy models ▪ High credit costs ▪ Liability challenged ▪ Mostly loss making

…Leveraging the Best of Both Worlds to Create a Truly Scalable Lending Model

Traditional – Fin-Touch Alternative – Fin-Tech

Adopting a hybrid model comprising best practices of traditional lenders and modern fin-tech companies

Traditional credit assessment models like CIBIL scores Alternate credit assessment models leveraging analytics + publicly available data Physical processes such as visits to customers Leverage technology to automate processes thus reducing manual errors Focus on collateral driven lending Unsecured credit solutions Limited to term loans Variety of loan products

8

The U GRO Incarnation

The Assimilation of Aspirations

9

Our Mission

‘To Solve the Unsolved’

India’s $600B+ SME Credit Availability Problem

10

U GRO Capital | Who We Are

Knowledge Technology

Large Institutional Capital

~₹920 Cr Of Equity Raised

Strong Corporate Governance

Board Controlled, Management Run

Experienced Management Team

250+ Years of Experience

A highly specialized, technology enabled small business lending platform

Deep domain expertise of target segments to better understand the customer A scalable, data driven approach to ensure dissemination of knowledge

11

26 years of experience in creating institutions across the financial services domain

• Mr. Shachindra Nath

Executive Chairman and Managing Director

12

Lending Capital Markets Asset Management Insurance

SME Lending Built India’s 4th largest Non- Banking Finance business, focused on SMEs with a book size of over USD 2.3 billion Housing Finance Started the housing finance arm focused on funding the affordable housing segment Retail Broking Created a platform with over 1,350 points of presence across India Wealth Management JV with Macquarie providing wealth management solutions to ultra HNI clients Investment Banking Mid-market focused institutional equities and investment banking platform with presence in 8 countries Asset Management Largest alternative asset management out of India : Over $ 21 B of AUM with presence across the US, Europe, Asia and Africa Marquee funds included Northgate, IBOF, Landmark Partners and Quadria Capital Life Insurance Life insurance JV with AEGON NV of the Netherlands Health Insurance One of India’s first specialized health insurance companies

Key Exits: Sale of the life insurance stake to Aegon, sale of the mutual fund business to Invesco, sale of Northgate to TCP, sale of Landmark Partners to the management team

▪ Core pillar

• f

Religare’s successful growth journey ▪ 6-year stint as the Group- CEO of Religare Enterprise ▪ Transitioned the company from an operating loss of ~USD 80 million in 2013 to USD 50 million

• f

net profitability in 2016 ▪ Presented the “CEO of the Year” award at the Asia Banking, Financial Services & Insurance Excellence Awards in August 2015 ▪ Started his entrepreneurial journey in 2016.

Founder With Experience Creating Institutions Across Financial Services…

Manish Agarwal Chief Risk Officer AUM Managed: ₹ 1,200 B Rajni Khurana Chief Human Resources Officer AUM Managed: NA Anuj Pandey Chief Operating Officer AUM Managed: ₹ 120 B Kalpesh Ojha Chief Financial Officer Liability Raised: ₹ 700 B J Sathiayan Chief Business Officer AUM Managed: ₹ 80 B Abhijit Ghosh CEO and Whole Time Director AUM Managed: ₹ 180 B

172

employee count

Fully formed team 4/5 Rated employees Deep and large ESOP pool

13

…Supported by a Leadership Team With a Strong Track Record of Execution…

Sunil Lotke Chief Officer – Legal & Compliance AUM Managed: NA

Strong Corporate Governance Framework Enshrined in the Articles…

▪ High degree of regulatory oversight and transparency ▪ An institution created with a long-term view, designed for continued operational efficiency ▪ Access to permanent capital ▪ Deloitte appointed as the statutory auditor and PWC appointed as the internal auditor ▪ Independent directors to comprise majority for perpetuity ▪ Any shareholder holding >10% to qualify for a board seat ▪ Key committees to be headed by an independent member with required credentials ▪ The majority of the NRC, ALCO and Audit Committees to comprise of independent directors ▪ Any proposed loan >1% of net worth or to a related party to require unanimous approval of ALCO and the Board ▪ Board approved multi-layer credit authority delegation ▪ Removal of key management (including CRO, CFO) to require 3/4th board approval ▪ Any significant action by the Company to need 3/4th approval of the Board

Special Resolution of Shareholders required for effecting any changes to the AoA Promoters/Management do not have unfettered rights to divert business strategy

14

…Supervised by an Independent Board Comprising of Industry Luminaries (1/2)

▪ Ex-Chairman, MCX, Ex-CIC, GoI, Ex-Director - SIDBI ▪ Over 40 years with the Indian Administrative Services ▪ Indian Administrative Services (Batch of 1973) ▪ M.A., Utkal University, M.Sc., London School of Economics ▪ Ex – DMD, SIDBI ▪ Over 38 years with experience with SIDBI, UCO Bank and IDBI ▪ PGDM from MDI ▪ Currently a director with MUDRA, MFIN, NSCCL, Aye Finance, member of the advisory committee at Ivy Cap and Lok Capital ▪ Board Member – ICRA, Ex-Senior Partner, Deloitte ▪ Over 30 years of experience with Deloitte, Vaish and Associates ▪ CA from ICAI and a BA from Delhi University ▪ Currently an independent director at ICRA, Shubham Housing, Indo Ram Synthetics, Joyville Shaapoorji Housing

NK Maini - Chairman, Risk Management Committee Satyananda Mishra - Chairman, CSR Committee Ranjana Agarwal - Chairman, NRC Committee

▪ Ex-CFO, Citi-India ▪ Over 40 years of experience with Citi, CEAT, Tata ▪ PGDM from IIM Kolkata and B. Tech from IIT Kharagpur ▪ Advisor to EY, Independent Director at Trent, Cashpor Microcredit, Kalyani Forge, India First Life Insurance

• S. Karuppasamy - Chairman, Compliance Committee

▪ Ex-Executive Director, RBI ▪ Over 40 years of experience with the RBI ▪ PG Diploma in Bank Management, Indian Institute of Banking & Finance, CAIIB (Honorary Fellow) & MA (Economics) ▪ Currently a member of the RBI services board, and a director at ARCIL and Vidharan (MFI)

Abhijit Sen - Chairman, Audit Committee

Board members selected for the specific skillsets they bring to the table

Specialization: Personnel Mgmt Specialization: Credit, SME Specialization: Finance Function Specialization: RBI Regulations Specialization: Audit, Tax

15

Legend: Independent Directors, Non-executive Directors

Shachindra Nath – Executive Chairman and Managing Director

▪ 26 years of experience in creating institutions across the financial services domain ▪ 6-year stint as the Group-CEO of Religare Enterprise ▪ Qualified lawyer and a University Rank holder from the Banaras Hindu University (India)

Supervised by an Independent Board Comprising of Industry Luminaries (2/2)

U GRO’s Board also includes CEO Abhijit Ghosh as an Executive Director

16

Legend: Independent Directors, Non-executive Directors

Specialization: Retail Banking ▪ Ex-Head of Branch Banking, HDFC Bank ▪ Over 30 years of experience at HDFC Bank and ANZ Grindlays Bank ▪ B. Com from St. Xavier’s College Calcutta, MBA from Texas Christian University and CA from ICAI ▪ Currently a member of the Equitas Small Finance Bank board

Navin Puri

▪ Founding Partner of NewQuest ▪ B.Tech. from Regional Engineering College, Kurukshetra University, Haryana. PGDM from Indian Institute

• f

Management (IIM), Bengaluru, Karnataka. ▪ Was the Non-Executive Director of Ujjivan Financial Services Limited

Amit Gupta

▪ Managing Director at Samena Capital ▪ Chartered Financial Analyst (AIMR), Chartered Alternative Investment Analyst and holds a master’s in management (Finance) from the University of Mumbai.

Chetan Gupta

▪ Partner at ADV ▪ 22 years of experience in financial services across private equity investments, structured finance, distress debt acquisition & resolution, corporate and financial restructurings in India ▪ Chartered Accountant (C.A.) from Institute

• f

Chartered Accountants of India. B. Com (Hons) from Delhi University

Manoj Sehrawat

▪ Partner and PM at PAG ▪ 27 years of experience in financial services across investment banking, trading and distressed asset investment. ▪ MBA from NYU Stern School of Business

Kanak Kapur Rajeev K. Agarwal - Chairman, Stakeholder Committee

▪ Ex-Whole Time Member, SEBI ▪ Over 30 years with experience with SEBI, FMC, IRS ▪ Indian Revenue Service (Batch of 1983) ▪ B. Tech, IIT Roorkee Specialization: SEBI Regulations

Formation of Chokhani Securities Preferential Allotment Qualified Institutional Placement Birth of U GRO Capital Preferential Allotment

1994: Formation of Chokhani 1995: Listing on the BSE 2004-Present: 14-year track-record

• f profitability

₹ 4,350 M raised from global private equity firms

• ADV

Partners, NewQuest and IndGrowth ₹ 1,120 M raised from public market funds, insurance companies Acquisition

• f

Chokhani Securities Revamp of the management team Demerger of the lending business of Asia Pragati approved – ₹ 1,750 M ₹ 1,920 M raised from large family

• ffices / HNIs through a preferential

allotment of shares

1994 - 2017 Dec 2017 Dec 2017 Aug 2018

Disbursements started in January, 19

May 2018

17

Private Equity Funds Public Market Funds Insurance Firms Family Offices

Chhattisgarh Investments MK Ventures

Group

family Taparia family

Jaspal Bindra

Backed by Diverse and Marquee Shareholders

18

Data as of 30 June 2020

Focus on sustainable growth and building long-term partnerships during the current period of challenging market conditions

Where We Stand Now

Metric

BFSI Partners Disbursals Employees AUM GRO Partners Ecosystem Partners Customers Branches Secured Co-Origination Partners

₹1,397Cr

9

₹847Cr

4 69% 393 7,343 26 172 27

Significant Impact to Date, Large Development Goals in Pipeline

SMEs Directly Financed Total SMEs Financed % Portfolio – Education % Portfolio – Healthcare

7,500+ 15,000+ 21% 5%

Education and Healthcare Funding

▪ Two sectors where U GRO has already made a social mark are Education and Healthcare, which combine for a quarter of U GRO’s portfolio ▪ U GRO has introduced innovative and specialized programs within these sectors: ➢ Healthcare: Highly tailored loans specific for dental clinics,

• phthalmology clinics, nursing homes, consulting doctors etc.

➢ Education: Liquid income program ▪ U GRO targets significant expansion in these two sectors

Female Empowerment and Renewable Energy Programs

▪ U GRO has plans to roll out two programs which will stimulate India’s social development by empowering women and the renewables sector ▪ Financial Freedom for Women Program: A proposed program where female entrepreneurs would receive discounted commercial terms (on a case-by-case basis) and fast-tracked loan processing, to lower their barriers to entry ▪ Renewable Future Program: A proposed program where companies involved in the production of parts where the end use is renewable energy, e.g. solar panels, are provided funding at rates favourable to market rates

Financial inclusion and social development are core goals at U GRO, to be achieved through current and future programs

19

Know More, Grow More Sector based approach to specialization

20

21

Deep Analysis of Macro and Micro Economic Factors…

Reached Targeted 8 Sectors

Future business prospects Size of lending

• pportunity

Relative competition lending Impact of regulatory developments

180+ Sectors 20 Sectors

Interest coverage Asset Turnover ratio Demand supply gap & cyclicality in demand Impact of change in technology Working Capital Cycle Revenue Growth EBITDA Margins Upgrade & downgrade ratio Median rating Gearing Sector specific government policy Environmental issues Input risk Criteria

21

Criteria

An 18-month process involving extensive study of macro and micro economic parameters carried out in conjunction with market experts like CRISIL

…to Arrive at a Set of 8 Sectors

Focus on SME clusters in India

~50% - Contribution of the 8 sectors to the overall SME

lending market in India

Validated independently by CRIF, CRISIL and the

company distribution and underwriting teams Selected sectors aside from Auto Components have been relatively less affected by the economic slowdown

22

Large lending

• pportunity

Lower impact of regulatory changes Secular consumption driven growth Low geographical concentration Relatively less competition from banks

Top 8 Sectors

Healthcare Education Chemicals Food processing/ FMCG Hospitality Electrical equipment and components Auto components* Light engineering

Halted disbursals to Auto Components sector

We Further Narrowed Down on Select Sub-sectors

Healthcare Education Chemicals Food Processing/FMCG Hospitality Electrical Equipment and Components Auto Components Light Engineering

Key sub-sectors: General nursing homes, eye clinics, dental clinics, diagnostic labs, radiology/pathology labs, pharma retailers Key clusters: NCR, Mumbai, Bengaluru, Hyderabad and Chennai Key sub-sectors: Fine dining (standalone), QSRs, fine dining chains, manpower agencies, boutique hotels, guest houses Key clusters: NA Key sub-sectors: K-12 schools, play schools Key clusters: NCR, Mumbai, Coimbatore, Chennai, Hyderabad and Pune Key sub-sectors: Dyes and pigments, bulk and polymers, agrochemicals Key clusters: Mumbai, NCR, Ahmedabad, Vadodara and Surat Key sub-sectors: B2B, B2C Key clusters: NCR, Pune, Bengaluru, Chennai, Aurangabad and Rajkot Key sub-sectors: Engine parts, drive transmission and steering parts, body and chassis, suspension and breaking parts, electrical parts, other equipment, traders Key clusters: NCR, Mumbai, Kolkata, Hyderabad and Bengaluru Key sub-sectors: Dairy and dairy products, non-alcoholic beverages, consumer foods, poultry, sea food, food and beverage traders Key clusters: NCR, Mumbai, Chennai, Hyderabad and Pune Key sub-sectors: Casting and forging, medical equipment and devices, pipes, process control instruments, traders Key clusters: NCR, Chennai, Pune, Ludhiana, Bengaluru, Ahmedabad and Rajkot 23

Sub-sectors selected basis the contribution to the overall sector credit demand and risk profiles

India’s First Sectoral and Sub-sectoral Statistical and Expert Scorecards

24

A Seamless, Customized Customer Journey

25

File Flow for a Secured Loan

~8 segment specific statistical scorecards Log-In ▪ Plug and play distribution module ▪ Machine learning based OCR software Pre-defined Criteria Met? Loan Approved Pre-approval checks Quarterly Monitoring Feedback Loop ▪ Defined ticket size, sectors, turn-over ▪ Geographical location ▪ Borrowing history ~38 sub-segment specific scorecards ▪ Legal Verification ▪ Fraud Control Unit Check ▪ Field Investigation ▪ Valuation Criteria 1,000+ Parameters evaluated 20+ Data Sources Data Enrichment ~Sub-sector Specific PD Templates Statistical Scorecards Expert Scorecards

In Principal Approval in 60 mins Final Approval in 48 to 72 hours

Sub-sector Policies

Data and Analytics Touch and Feel Experience

Disbursement Statement Analyzers

Utilization of Big Data to Arrive at U GRO’s Sectoral Scorecards

Default rate across score ranges

26

3.45% 1.23% 0.75% 0.56% 0.40% 0.45% 0.26% 0.12% 0.08% 0.00% 718 751 798 823 846 871 907 980 1,341 1,500

‘Bad rates’ across intervals

8M+ 850 60%+ 70%

U GRO Behavioral Score Parameters per loan Loan records GINI coefficient ‘Bads’ eliminated by removal of bottom 20% by score

Look-alike based application scores for each of our 8 sectors Ability to estimate risk enables the company to move to a risk-based pricing model U GRO has received the 2020 Finnoviti Award for Business Model Innovation for the Development of Sector-specific Scorecards

Supplemented by Industry First ‘Expert Scorecards’ for all Sub-sectors

Parameters Factors Case A Case B Case C Facility related Vintage of the entity 20% 15% 10% Doctor’s Experience 20% 15% 10% Arrangement with pharmacy unit 30% 30% 40% NABH accreditation 30% 40% 40% Operational Share of IPD revenues in overall nursing home revenue 15% 20% 20% Share of insurances cases in overall IPD admissions 15% 20% 20% Govt empanelled cases in overall insurance admissions 10% 10% 10% Occupancy rate 30% 20% 20% Revenue per occupied bed 30% 30% 30% Financial Operating margins 15% 15% 15% Return on Capital Employed 20% 20% 20% Interest coverage 30% 30% 30% Asset turnover ratio 20% 20% 20% Receivable days 15% 15% 15% 27

Facility 40% Operational 40% Financial 20%

Case A: Less than 20 bedded nursing home

Facility 30% Operational 30% Financial 40%

Case B: 20-50 bedded nursing home

Facility 20% Operational 20% Financial 60%

Case C: 50-100 bedded nursing home

Sector: Healthcare Sub Sector: Nursing Homes

▪ Combination of operating and financial parameters ▪ Scorecards developed in consultation with CRISIL market experts ▪ Methodology ▪ 1,000+ personal interviews across 9 locations ▪ Responses for over 50+ curated questions for each sub-sector

Program-specific Policies in Place

Detailed policy norms

Income program Banking program GST program P/L program Low LTV program

Credit scorecard cut offs at sector level Current year turnover* No drop in turnover Profit (EBIDTA)** Current ratio* Interest coverage ratio >= 2.5 Debtor turnover days* Inventory turnover days* Total obligations to adjusted tangible net worth <=3 12 months banking Inward bounces <=3% CC/ OD utilization within limits Credit summation* ABB to EMI ratio No delay in filing GST returns Single buyer/ seller concentration DSCR

Scorecard Financials Turnover Banking GST Eligibility

GST, P/L turnover programs – eligibility derived basis actual

• bserved turnover, validated with banking credit

summation, and using industry margins Banking program – eligibility derived basis average liquid balance in account, observed as daily average over one year Low LTV program – eligibility basis restricted LTV (45%) for residential and commercial properties (industrial properties not allowed) Overlays for alternate programs & unsecured product 1. Stricter ticket size restriction 2. Lower LTV caps across collateral types 3. Lower family exposure 4. Additional checks at pre-disbursal stage a) no delay in GST return filing b) No delay in ITR filing c) <25% concentration for any buyer/ supplier 5. Further overlays for unsecured products, on credit testing, cheque bounce, property ownership and residence stability

*measured against sub-sector level benchmarks **Computed basis industry margin for GST & P/L programs

28

▪ An extensive array of parameters are analyzed in each program, allowing us to lend to thin-file customers while not compromising our credit standards ▪ Sectoral policies will have subsector-specific questions embedded within them

Digital Channel Underwriting Design

29

Policy framework Element Source of data

Business vintage Bureau footprint – 24 months KYC verification CIBIL IDV Repayment ability Credit score based Fraud check E-mail based fraud check Property ownership Cersai - debtor search Hunter

SME Express score – a proprietary individual SME score

▪ First-in-industry score for individual business owners, designed to predict default in business loans ▪ Gini coefficient of 60+ in training & testing datasets ▪ Validated on industry data*

Digital KYC verification with CIBIL IDV score

10.4% 4.6%

< 750 750 +

*Co lending partner (own 90 dpd+ %)

Financial documents None (< 5 lakhs) 12M banking (5-10L)

15.5% 2.5%

< 750 750 +

*DA partner (bureau 90 dpd+ %)

2.2% 1.3%

< 750 750 +

U GRO logins till Jul 19 (bureau 60 dpd + %)

Single verification score based on ▪ Match algorithm on CIBIL database ▪ Screening multiple KYC parameters, enquiries, repayment events

Emailage – power of email-based Fraud check

Email fraud score

Loans up to 10 lakhs purely based on data-driven decisioning Loans up to 5 lakhs without any financial documents Customized SME credit scores for entity and individual, validated on bureau & industry data

Credit Risk – Supplemented by Enterprise Risk

30

Asset Liability Management Liquidity equivalent to 6 months of liability and 2 months of advances to be maintained at all times The one year bucket mis-match will be positive or equivalent to zero Asset strategy influenced by liability strategy Fraud Risk Background/Fraud checks on all outsourcing partners, agencies and employees before onboarding Seeding checks conducted regularly Operational Risk Standard operating procedures defined for all processes End to end automation of processes to limit manual intervention

PORTFOLIO LEVEL RISK ENTERPRISE LEVEL RISK

Concentration Secured loans to be ~70% of overall portfolio Single sector concentration is capped at 25%, single geography is capped at 20% The BFSI channel to be <20% of the overall portfolio FCU Checks An independent team with deep market expertise Partnerships with multiple FCU agencies and Hunter Property appraisal Collateral specialist hired 2 valuation agencies appointed for loan disbursal > ₹ 1 Cr FI verification Personal visits by employees Geo-tagging of customer location End-to-end automation of FI initiation and completion Early warning systems Automated, analytics led, early warning systems basis proprietary rules framework incorporating social, sector, macro-economic feeds

Credit Process Enabled by Integrated Technology

31

An In-house Technology Platform that Enables Our Underwriting Process

32

Fintech-enabled Four Channels

Customer Acquisition Customer Onboarding

360° view of the customer

Customer Management

Expert Scorecards Early Warning Systems

1 2 3

Bank/GST Statement Analyzer Statistical Scorecards ML-Enabled OCR Distribution Module LOS LMS Data Integrations Fraud Control

8 sectoral statistical scorecards 38 sub-sectoral expert scorecards 25+ API integrations

Automated policy checks Multiple industry firsts to enable a

60-minute in-principal approval

Completely seamless, paperless onboarding

Plug and Play Distribution Module

33

A Plug and Play Distribution Module GRO Partners BFSI Channel Corporates Customer

Customer ERP GRO App Partner LOS

A paperless, and seamless customer onboarding process Multiple customer touchpoints

GRO LOS

Data Enrichment Layer No documents needed

Customer Devices

Credit Evaluation Authenticity Verification Business Prominence Collateral Valuation

OCR Technology with Machine Learning to Expedite Processing

34

150+

Applications processed

80%+

Savings in time to process

<5

Central Ops resources

50+

System coded validation checks

100+

Financial parameters stored per case

3,000+

Pages machine-read P&L Statement, Balance Sheet 7-10 pages ingested per income assessment instance Extensive accounting checks on P/L and Balance sheet entries Determines if OCR output needs curing or if repeat upload is needed Based on Natural Language Processing and Machine Learning System assisted curing window Handles unstructured text semantically Work of over 1 day can be compressed inside 60 mins

Ingestion Validation Image Processing Curing

A Machine Learning Based OCR system

System capable of handling pdfs and scanned copies Accordingly cases progress in the workflow Integration with legacy software through RPA and APIs Curing data used by ML engine for progressive improvement

Advanced Bank, GST and Bureau Analyzers to Size Up the Customer’s Cash Flows, Ability to Repay, Risk-Return Metrics and Estimate Loan Exposure

▪ ~ 100 different product variants basis bureau standard definitions classified into ROI/tenor buckets ▪ Product level ROI, tenor assumptions to compute obligations ▪ Product specific obligations computation encoded ▪ Process replicated for all financial applicants for footprint across both Commercial and Consumer bureaus

Category Counterparty State Month

▪ 400+ data parameters ▪ Validate monthly sales, expenses, gross margins ▪ Insight into borrower's business network and concentration ▪ Digitization of sector identification ▪ State-wise break up providing information on operating markets

Overview Aggregate Transactions Bounces

▪ Information related to bank statement analysis obtained from Perfios through an API integration customized to U GRO requirements ▪ Ability to validate business transaction trends (sales, expenses, margins), cheque bounce patterns, loan/EMI details, supplier & vendor identification and concentration

Bank Statement Analysis Bureau Record Analysis GST Statement Analysis

35

Tradelines Granular Details

▪ OFAC ▪ Interpol (Red and Yellow Notices) ▪ UN Sanctions and Wanted Lists ▪ Development Bank Blacklists (World Bank, ADB, KfW, AFDB) ▪ NIA Terrorist Lists ▪ Wanted List under COFEPOSA

AML

LOS ▪ Case logged in through another channel for same product ▪ Rejected in last 6 months due to default/ fraud LMS ▪ Automated existing customer check ▪ In case of duplication, good-bad logic is run – checking bounces/ defaults in last 3 months ▪ Group exposure ▪ Family exposure

Internal De-dupe

Comprehensive de-dupe including internal LMS de-dupe, AML, litigation search covering BIFR, NCLT, all district courts, high courts, supreme courts, DRT, DRAT, ITAT

BIFR

▪ Array of BIFR Cases ▪ Status of the BIFR Case ▪ Name of the Entity ▪ BIFR Case Number / Year ▪ Address of the Entity ▪ Last date of Order

NCLT

▪ Name of Advocate ▪ Status of Case ▪ Names of all parties ▪ Interim Orders ▪ Date of Order ▪ Order/Judgement

36

Comprehensive de-dupe including internal LMS de-dupe, AML, litigation search covering BIFR, NCLT, all district courts, high courts, supreme courts, DRT, DRAT, ITAT

Courts and Tribunals

▪ Access to court records of Indian District, High and Supreme Courts ▪ API Integration through eCourts Services ▪ Comprehensive checks against database of 900,000+ cases

Fraud Checks and Litigation

Automated Policy Approvals Reducing Subjectivity in Credit Appraisal

37

| Highly flexible | Capable of handling complex computations and policies |

Automated comparison to policy Computation of loan amount and ROI Machine learning based credit systems Industry leading TAT and productivity No manual errors Auto-escalation to relevant authorities Parallel processing against all policies to capture best fit

Large and Scalable Distribution Platform Enabled by Technology

38

39

Development of System Architecture for Full-Suite SME Lending

GRO-Protect

Core Engine

GRO-Xstream

Partnerships

Core LMS

System of Records

GRO-Direct

Direct Interface

GRO-Chain

Supply Chain

GRO-Plus

Intermediaries

Anchor

Buyers Suppliers

Banks/FIs/DFIs Insurance/Mutual Funds/HNIs NBFCs/ Fintechs

An uberized distribution model capable of

• nboarding DSAs, CAs and
• ther intermediaries

Direct to customer (Online) channel – went live in beta phase in December 2019 Supply chain financing platform for vendor and dealer/distributor financing An online marketplace for large banks to partner with smaller NBFCs to either co-

• riginate or purchase assets

A comprehensive set of modules that will allow for maximal lending outreach within our mandate

Four Distribution Channels that Drive Our Asset Engine

40 ▪ 393 intermediary GRO-Partners

• nboarded

in 9 branches across key SME clusters in India ▪ Facilitated by our proprietary GRO-Plus app, an Uberized distribution model which enables GRO Partners and allows Principle Approval within one hour ▪ U GRO’s BDMs achieve industry leading productivities and TATs through our tech-enabled approach

Traditional Channel | GRO-Plus

▪ Our Ecosystem Channel involves partnering with Anchor companies, to gain access to their base of vendors for invoice-backed supply chain financing ▪ This model allows for credit provision to reach dealers, distributors and tier 2 suppliers who are not eligible for traditional financing ▪ Development ongoing of GRO-Chain, an SCF platform for vendor and dealer/distributor financing

Ecosystem Channel | GRO-Chain

▪ Partnerships spanning co-lending, onward lending and

• securitization. We have partnered with 27 BFSIs, with

an emphasis on serving ‘bottom of the pyramid’ SMEs ▪ Driven by GRO-Xstream, an industry-first

• nline

marketplace for large banks to partner with smaller NBFCs to either co-originate or purchase assets

BFSI Partner Channel | GRO-XStream

▪ Our proprietary Digital Lending Platform GRO-Direct aims to allow SMEs to directly apply for credit, increasing borrowing ease and further reducing TATs ▪ Digital partnerships signed with several fintech marketplaces, service providers and aggregators

Direct Digital Channel | GRO-Direct U GRO’s distribution model is geared towards catering SMEs across all geographies and ticket sizes. We create tailored products which allow for highly structured deployment of capital – optimized for both the distribution channel and customer

Turnover: Up to ₹5 Cr Ticket Size: Up to ₹2 Cr Turnover: Up to ₹1 Cr Ticket Size: Up to ₹50 L Turnover: Up to ₹20 Cr Ticket Size: Up to ₹5 Cr Turnover: Up to ₹50 Cr Ticket Size: Up to ₹5 Cr

Traditional Channels | A New Approach to the Old…

41

▪ Rigorous vetting of 1,200+ partners to reach an initial list of 100 channel partners. ▪ Selection criteria: ₋ Track-record of 3+ years ₋ Infrastructure Readiness ₋ Portfolio performance ▪ Partners have a track-record of acquiring ₹5,000 Cr+ per month ▪ Channel partners pay an onboarding fee – a first in the industry Delhi Jaipur Hyderabad Bangalore Ahmedabad Kolkata Mumbai Chennai Branch Offices Head Office

Locations identified through SME cluster analysis and portfolio benchmarking Partner Selection Criteria Partner App: An Industry First

Vijaywada Coimbatore Pune Nashik Nagpur Rajkot Vapi Surat Baroda Jodhpur Indore Ludhiana Chandigarh Planned Branches

Value Proposition for Channel Partners

▪ Lower TAT : In principal approval in 1 hour ▪ Higher productivity: High conversion (~60%) post the in-principle approval ▪ Analytics-driven opportunity to cross-sell/top-up within their customer bases ▪ U GRO co-lends with larger banks, allowing partners to originate larger ticket sizes ▪ Payment within 7 days resulting in improved working capital management

…Leading to Higher Productivity Across the Value Chain

Traditional Model U GRO Model

Customer Journey ▪ Needs to fill lengthy forms, submit multiple documents to 7-10 NBFCs, wait 6-10 days for an in principal approval and then 30 days for a final approval post multiple rounds of follow-ups ▪ In-principal approval in 60 mins by submitting

• nly the GST/PAN details, and financials to the

DSA ▪ Post submission, disbursal in 4-5 days for 60-70 percent of cases Partner Universe ▪ Mainly Direct Sales Agents ▪ DSAs, Chartered accountants, Mutual Fund/Insurance brokers Turn-around time ▪ Channel Onboarding: 1 week ▪ Loan Onboarding: 30-45 days ▪ Channel Onboarding: 1 day ▪ Loan Onboarding: 1 hour in-principal approval; 4- 5 days for disbursement Role of a branch sales manager ▪ Co-ordinating with the credit team, collecting documents, relationship management ▪ Managing relationships with the customer, and the channel partner FOS productivity ▪ 2 secured files/month ▪ 4-5 unsecured files/month ▪ 5-6 secured files/month ▪ 9-10 unsecured files/month Credit productivity ▪ Manual CAM preparation, review of every logged in file ▪ Automated CAM, trigger-based review

42

Disrupting the traditional branch led model through technology

Partnership with a smart energy solutions platform

▪ Pre-approved program based on data analytics for unsecured & secured loans to energy product vendors ▪ Performance data of vendor partners with U GRO to be shared by the aggregator — Vintage, location, transaction history ▪ Pay-outs to vendors routed through an escrow account created for the program

43

Independent vertical headed by the Chief Growth Officer ▪ Each sector to be led by a ‘sector head’ Develop partnerships in prioritized segments with key participants e.g. sector specific lenders, industry bodies ▪ E.g. Anchor led supply chain financing, partnerships with equipment suppliers

Dedicated “Growth Team” to build industry partnerships Ability to go deep into the partner value chain

Hotel Franchisor (Anchor) Receivable financing to their partner ecosystem Cross-sell of other products to the franchisees Ability to tap into the end consumer by providing travel loans

Ability to tap into the partners’ network of distributors, dealers, suppliers and then eventually the end customer through an ecosystem-based lending strategy

Growth Channels | Ecosystem Based Lending

BFSI Partnership Channels | Ability to service the bottom of the pyramid

44

Symbiotic partnerships to cater to the MEL segment

Challenges faced by NBFCs: ▪ Given scale of NBFCs, their regional concentration and the target segment, access to credit for such NBFCs is limited U GRO Solution: ▪ Create a steady liability solution for such NBFCs through multiple modes including direct lending, on tap assignment, co-lending and debt syndication ▪ Joint under-writing by U GRO and the partner NBFC Advantage to U GRO ▪ Ability to create a large, granular micro-enterprise book without incurring significant opex ▪ First loss credit enhancement from the NBFC

The BFSI partnership channel is U GRO’s strategy to cater to the micro-enterprise segment without incurring high Opex costs

Large Corporates Small and Medium Enterprises Micro Enterprises U GRO target segment Mainly located in large SME customers in metros/Tier 1 cities Catered to by smaller regional NBFCs Needs heavy investments in branches/feet on street especially in Tier 2/3 cities Mainly catered to by large banks Ticket size > ₹50 Cr

Fintech Service Providers/Aggregator Platforms Payment Gateway Food Hotels Healthcare Online Marketplace/ Listing # addressable set

<100 29,000 <100 500,000+ 200,000 125,000 11,000

*Monthly txn vol **lending potential + program cap

< ₹5Cr* ₹22Cr* < ₹5 Cr* ₹1,750Cr** ₹600 Cr** ₹375Cr** ₹50 Cr+ ₹1,600Cr**

Using platform data to create a customized program for each alliance

50 ₹50Cr*

OD limit for hospital based

• n past trend of purchases on

platform Exclusive credit program based

• n scorecard, banking and

platform sales; repayment adjusted from sales by escrow Loans to hotels based on rental receivables from OYO Pre-approved program with pre-defined eligibility and no income proof; loans up to ₹5 lakhs Financing of insurance claims by hospitals; payment from insurance company routed to escrow account

1M SMEs conducting trades/ activated online ₹391Cr of trade finance

• pportunity per month

₹3,500Cr+ of prequalified loan eligibility All marketplace programs with risk cover/ receivables escrow Access to 20M+ self- employed individuals/ SMEs

Accessing SMEs through a diverse set

• f ecosystem

partners… …including niche entrants & some of the largest players B2B Marketplaces Metals Solar Energy Financial Services Medical Supplies

2 Million+

45

Digital Channel | Fintech Partners

Our Innovation-Driven Digital Lending Platform

Product Development

▪ Sectoral Need Gap Identification based on Perception Maps ▪ E.g. Solutions available for Dentists Loan (Healthcare → Doctors) & Kirana Shop Loans (FMCG → Trading)

Marketing

▪ Customer Data Identification ▪ Push & Pull Marketing Campaigns ▪ Personalised Communication ▪ Personalised on-boarding journey (ChatBots)

Product and Marketing

Innovation driven by Micro-Level Focus within Sub-sectors Sector-Focused Partnerships

▪ Ecosystem Players ▪ Aggregators ▪ Web Portals Listings ▪ Payment Gateways ▪ Marketplaces ▪ Industry Bodies/Associations

Direct To Customer Campaigns

▪ Integrated Marketing Automation Tool for campaign delpoyment ▪ Medium: SMS/Flash Message /WhatsApp/Voice Blasts/Email ▪ Outbound Calling with loan solutions to optimise conversion

Acquisition

Micro–targeting of customer and partner audiences for onboarding

▪ Based on Industry First Sector Specific Scorecards ▪ Pings other Tech Platforms for information gathering and validation via customized APIs ▪ Assisted models (Outbound Calling) to induce customers to convert ▪ Outsourced partners to collect documents and meet regulatory compliance

Underwriting/Fulfilment

60 Mins Decisioning – 100% Digital

▪ Completely Digital Customer Servicing ▪ No reliance on human interrvation ▪ Web-service based APIs for instant query/request handing over app/web

• r IVR call

Customer Service

Chatbot based, integrated with popular message apps (proposed)

46

Launched in Dec 2019

Distribution Network

47

Branches BFSI Partners GRO Partners Ecosystem Partners Co-lending Partners 9 26 311 21 3 20 45-50 800-1000 50-60 10-15 Current FY24P

Deep Sectoral Understanding

Leading to Tailor-made Product Solutions

48

Our Product Philosophy

To create sub-sector specific products by modulating the following attributes to meet customer requirements…

Loan Structuring Collateral Tenor Assessment Parameters Pricing

Moving beyond conventional products offered by most NBFCs in the market…

49

Supply Chain Financing Unsecured Loans Secured Loans Mostly long tenor, loan against property Short term working capital loans 30-90 day loans against invoices

A Holistic Product Solution…

Pricing

Rate of Interest / Processing Fee

Methods of assessment

| Financial |Banking | Turnover |

Collateral

Movable/ Immovable Property

Tenor

Repayment Frequency/ Repayment Period

3 Sector based product parameters

Loan structuring

Ability to offer structured disbursement and repayment solutions

Scenario: Hospitality/restaurants; franchise set up ▪ 1st disbursal – transferred to master franchisee account – repayment to start post 6 months ▪ 2nd disbursal –for infrastructure development – repayment post 6 months ▪ 3rd Disbursal – as the first disbursal as a line of credit, valid for 12 months, quarterly bullet repayments Scenario: Healthcare Retailers ▪ Data on prospective borrower is provided by super distributor ▪ Includes monthly / yearly procurement and payment pattern Sales and recovery report from the supplier / super distributor taken as document proofs Scenario: Education ▪ Repayment frequency to match the frequency of fee receipt ▪ If the fee is received once in a quarter, the EMI frequency can also be structured accordingly 50 Scenario: Education Industry ▪ Future fee receivables as primary collateral ▪ Institution building as the secondary collateral Scenario: Type of collateral ▪ ROI to vary basis collateral ▪ Self occupied residential property to have lower ROI as compared to vacant residential properties ▪ K12 / Hospital buildings to have higher ROIs

…With Tailored Products for Each Sub-Sector

51

Sector Sub-sector Key Insights

Boutique Hotels

▪ Boutique hotels want a convenient and hassle- free loan process ▪ Business data available on digital marketplaces ▪ Very open to completely digital process

Hospitality Healthcare Food Processing & FMCG

Dental Clinics FMCG Traders

Key Propositions Target Segment

Two/three star mid sized and budget hotels Restaurants and QSRs Quick service restaurants and fine dining restaurants

▪ Restaurants with different formats have highly disparate sources of income ▪ Broad range of margins across sub-types, affected in particular by owning a liquor license ▪ Pre-approved loan disbursement based on marketplace data e.g. trivago, MakeMyTrip etc. ▪ Parameters for loan decision include online rating, # of rooms, average room rate etc. ▪ Restaurant format-based eligibility approach - QSR standalone, QSR franchise and fine dining ▪ Scorecard approach with higher scores for

• wned property, liquor license, home delivery

Existing dental clinics

▪ Loan eligibility in this sector is quite margin reliant ▪ Dental clinics offering high end, very specialized services have higher margins ▪ Procedure based lending approach ▪ Liquid Income program available based on specialization of the dentist ▪ Parameters for loan decision include doctor’s qualifications, clinic vintage etc.

Kirana shops measuring a minimum of 200 sq. ft

▪ Outlook and repayment behavior have a strong correlation with shop size and business vintage ▪ Volume is very dependent on speed at which they can rotate stock ▪ Business and sourcing stability are also of critical importance ▪ Loans offered based mainly on floor area and business/shop vintage ▪ Further parameters monitored include supplier stability, quantity of stock maintained, inventory turnover etc.

Leading to a Portfolio that Caters to the Needs

• f a Diverse Set of Liability Providers

52

Liability is an ‘Art’ – U GRO is designed to perfect this Art..

Liability led asset strategy

▪ Build a diversified, granular book catering to prime/near prime customers ▪ Start with a primarily secured book and slowly build the unsecured part ▪ 95% of the book to be Priority sector/Impact lending ▪ Minimal asset-liability mismatch

Diversified Liability Base

▪ Diverse liability mix to include – all major banks, debentures, capital market and insurance companies ▪ Access funding from new sources of funding such as multilateral agencies, impact funds, development bank etc. ▪ A mix of on and off-balance sheet assets

53

Active engagement with stakeholders

▪ Enhance ratings through close partnerships with rating agencies and by creating a diverse and secure lending book ▪ Early conversations with banks to secure debt and co-lending partnerships

| Build loan book starting from high equity/low leverage to higher leverage over a period of time | Achieve low cost of borrowing basis high credit rating over a period of time |

U GRO’s asset strategy would lead to a low cost of capital Key tenets of our liability strategy

Our Liability Strategy | A Tri-Pronged Approach

54

U GRO Platform Knowledge | Technology U GRO Capital Larger Banks/NBFCs

Balance-sheet Co-origination

Insurance Firms/Mutual Funds

Assignment

| Ability to generate significant fee income | More competitive interest rates | Ability to cater to customers of all risk profiles | Increased scale | Minimize ALM mismatch

Partnerships already signed with SBI, ICICI Bank and Bank of Baroda Specialized programs for DFIs/multi- lateral organizations Policy of actively securitizing the loan book to ensure that the mismatch in the greater than 5-year bucket is funded by equity Co-origination with larger banks to originate higher ticket loans Healthcare, education, female entrepreneurs, clean energy

Co-origination Partnerships with Three of the Largest Banks in India

Bank of Baroda

(Loan Book: ₹7.1 lakh crores) Secured Business Loans Signed October 5, 2019

State Bank of India

(Loan Book: ₹23.7 lakh crores) Small Ticket SBL & UBL Signed November 8, 2019

55

ICICI Bank

(Loan Book: ₹7.1 lakh crores) Secured Business Loans Signed December 13, 2019

Co-origination is a value accretive strategy

Customer pays a single blended rate of 12% The Co-lending bank receives 80% of the loan at an ROI of 10.5% U GRO receives 20%

• f the loan at an ROI
• f 12%

U GRO also receives the differential between the ROI received on the 80%

• f the loan and the

bank rate as a fee (i.e. 1.5% on the 80%)

Numbers provided are for illustrative purposes only

▪ U GRO achieves a high total income per loan with this model, leading to a higher ROE ▪ Co-origination provides a channel for quasi-liability at an attractive cost of debt ▪ U GRO’s income from 80% of the loan is classified as fee income, for which there are no capital adequacy requirements ▪ The full responsibility for origination, underwriting and collections (if required) lie with U GRO Capital ▪ Co-lending model allows U GRO to better cater to varying risk classes

Example of Co-origination Model

Sustained and Controlled Early Growth

56

57

21% 17% 16% 15% 9% 9% 8% 5%

Sectoral Mix*

Education Light Engineering Electrical Equipment Hospitality Food Processing Auto Components Chemicals Healthcare

Portfolio Snapshot (As on June 30, 2020)

Geographical Mix*

*Does not include Onward Lending or Portfolio Buyouts

▪

Delhi/NCR

▪

Karnataka

▪

Gujarat

▪

Telangana

▪

Maharashtra

▪

Rajasthan

▪

West Bengal

▪

Tamil Nadu

▪

Haryana

▪

Uttar Pradesh

▪

Punjab 21% 12% 7% 7% 16% 9% 8% 10% 1% 4% 3% 69% 31%

Secured Mix

Secured Unsecured

Our portfolio mix remains largely unchanged from last quarter due to COVID disruptions in Q1 FY21

Balance Sheet

▪ Remain liquid with over ₹300 crores of immediate liquidity on the balance sheet ▪ CRAR: 99.4% ▪ GNPA: 1.02% ▪ NNPA: 0.57% ▪ Book Value per Share (BVPS): 131.31

58

Balance Sheet (₹ Lakhs) Q4 FY20 Q1 FY21 Financial Assets 114,441 116,530 Loans* 83,238 82,789 Cash and Investments 8,448 1,368 Other Financial Assets 22,755 32,373 Non-Financial Assets 6,805 7,250 Total Assets 121,246 123,780 Financial Liabilities 28,745 30,789 Trade/Other Payables 1,420 954 Borrowings & Debt Securities 25,454 27,919 Other Financial Liabilities 1,871 1,915 Non-Financial Liabilities 349 377 Total Equity 92,152 92,614 Equity Share Capital 7,053 7,053 Other Equity 85,100 85,561 Total Liabilities + Equity 121,246 123,780

*AUM as of end Q4 FY20 and Q1 FY21 are ₹861Cr and ₹847Cr respectively, the ‘Loans’ figure adjusts for net payouts and ECL as per Ind-AS

Income Statement

59

Ind-AS accounting standards have been in place since Q1 FY20 *The Company has recorded Deferred Tax of Rs. 1,391 lacs on the tax losses transferred from Asia Pragati Cap Fin Private Limited on account of acquisition based on the reasonable certainty of the future taxable profits

Income Statement (₹ Lakhs) Q4 FY20 Q1 FY21 Interest Income on Loans 2,763 2,748 Other Operating Income 952 331 Financing Costs 642 684 Net Income 3,073 2,395 Operating Expenses 1,884 1,867 Provision 603 115 Profit Before Tax 586 413 Tax (1,449)* 40 Profit/(Loss) for the period 2,035 373

▪ Other operating income for Q4 FY20 included a one-time income of INR 5.55 crores ▪ Financing costs have gone up despite weighted average borrowing costs reducing due to our desire to build out our liability book, which includes incurring negative carry ▪ Absolute value of provisioning expense has come down in Q1 FY21 because the majority

• f the COVID-19 provisioning was accounted

for in Q4 FY20