U GRO Capital | An Overview The Indian SME Lending Market A large - - PowerPoint PPT Presentation

U GRO Capital | An Overview

The Indian SME Lending Market

A large yet untapped market opportunity

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61.0

64.4

FY18 FY19

FDI Net Inflows ($ B)

Investors Still Bullish On Long Term Growth Prospects

Despite Near-Term Headwinds, the Indian Economy is Anchored by Political Stability and Long-Term Structural Reforms

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Sustained Growth Despite Near-Term Challenges

7.4% 8.0% 8.2% 7.2% 6.8% 5.0% 5.9%

FY15 FY16 FY17 FY18 FY19 FY20F FY21F

Real GDP Growth Rate

• 25

25 50 75

Mar-16 Sep-16 Mar-17 Sep-17 Mar-18 Sep-18 Mar-19

Consumer Confidence Perception

Current 1-Year

Consumer Confidence Improving Signaling Spending Growth Revival Unprecedented Structural And Political Stability Facilitating Long Term Reforms

▪ Corporate Insolvency Resolution Process yielded resolution of 94 cases with total claims settlement of $24.2B as of March 2019 ▪ India’s new 15% tax rate (down from 35%) on new manufacturers is the lowest amongst its peers, and will drive growth for manufacturing-based SMEs ▪ PSU Banks have been consolidated for operational efficiencies, coupled with a $7.8B capital infusion to reinvigorate the financial sector

The NBFC Liquidity Crunch is Transitional in Nature

▪ Current liquidity crunch an outcome of idiosyncratic governance issues in certain NBFCs ▪ Subsequent slowdown in the auto, SME segments re- emphasizes the critical role played by NBFCs ▪ Intervention from the Central Gov/RBI very likely – Increasing bank exposure limits, classification of credit for on-lending to SMEs up to $28.5K as PSL ▪ The RBI has instituted a Partial Guarantee Scheme for NBFCs, with $5.6B sanctioned and $1.4B already disbursed ▪ First government with an outright majority since 1984 ▪ Geopolitical stability has been maintained despite sporadic flare-ups | India has moved to 4th on the Asia- Pacific Power Index ▪ Inflation (3.3% YoY rising to 4.0% by Sep ‘20) and the fiscal deficit are well under control ▪ India jumped from 77th to 63rd in the World Bank’s ease-

• f-doing-business index, the third year in a row that India

has been among the top 10 improvers in rank

The broader economy and the NBFC sector expected are expected to normalize in 2020

▪ Real Private Final Consumption Expenditure (PFCE) will increase from 5.5% in 2019-20 to 7.0% in 2020-21

India Represents a Large, Significantly Underpenetrated Credit Market

One of the largest and fastest growing economies in the world However, the credit to GDP ratio is still much lower than other markets Leading to high credit growth in the country led by the NBFC sector Significant government impetus for the growth of credit

14.1 13.9 9.0 10.9 8.2 10.0 17.9 15.6 18.8 16.6 14.6 21.2

FY13 FY14 FY15 FY16 FY17 FY18

Credit Growth Rate (%)

Bank NBFC

▪ Grant of universal banking, payment banking and small finance banking licenses ▪ Focus on financial inclusion – Jan Dhan Yojana1, Pradhan Mantri Awas Yojana2 ▪ India Stack – Cashless, Paperless, Presence-less ▪ Credit guarantee scheme for MSMEs

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25.1 20.2 10.3 5.5 4.2 4.0

China US India Japan Germany Russia

6.1% 2.1% 5.0% 1.9% 0.6% 1.7%

GDP PPP – $ T, Real GDP Growth

160.0% 73.6% 44.8% 99.9% 54.3% 49.1%

China US India Japan Germany Russia

Total credit to non-financial corporations as a % of GDP

154.3 178.6 212.9 254.3 297.1 338.6 385.7

FY14 FY15 FY16 FY17 FY18 FY19E FY20P

Total credit to the private non-financial sector ($ B)

The overall lending market in India is expected to grow at 10-11% with NBFCs growing at 15-17% over the next 5 years ~$1T lending opportunity over the next 5-6 years | Significant head-room for many more banks and NBFCs to emerge !

1Jan Dhan Yojna: A govt initiative to ensure that every individual has a bank account; 2A govt initiative to ensure housing for all by incentivizing low cost housing and providing access to credit; 3set of APIs that

allows businesses, startups to utilize an unique digital Infrastructure to solve India’s hard problems towards presence-less, paperless, and cashless service delivery (Aadhar, eKYC, Unified Payments Interface)

Source: IMF, BIS

NBFCs Have Certain Structural Advantages and Disadvantages Vis-à-vis Banks…

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▪ 100 % foreign ownership permitted ▪ Ability to be nimble – lesser restrictions on branches, allowed businesses ▪ No obligation to lend to “priority” sectors or open branches in rural areas ▪ No requirement to maintain Cash Reserves/Statutory Liquidity ▪ Still very regulated – NBFC-ND SI1 as regulated as a bank ▪ Cannot offer liability products ▪ Higher capital adequacy ratios ▪ Higher cost of funding

NBFCs have over the years proved themselves to be nimbler and more specialized than traditional banks

1NBFC-NDSI are non-deposit taking NBFCs having total assets of greater than ₹ 500 Cr; which are classified as systemically important by the Reserve Bank of India

...Resulting in Significantly Higher Value Creation by NBFCs

16% 18% 4% 7% 9% 14%

• 2%
• 7%
• 14%
• 13%

11% 47% 3% 5% 3% 1% 15% 9% 19%

• 20%

0% 20% 40% 60% 21% 23% 14% 12% 17% 28% 34% 3%

• 6%

6% 19% 38% 25% 20% 16% 22% 33% 16% 18% 17% 12% 0% 3% 8% 13% 7% 2%

• 51%
• 23%

14% 22% 27% 18% 15% 17% 18% 17% 21%

• 60%
• 40%
• 20%

0% 20% 40%

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5-year AUM Growth (FY14-19) ROE (FY19) 5-year Annual Share Price Growth Rate

Mean: 23% Mean: 15% Mean: 19% Mean: -1% Mean: 13% Mean: 3%

NBFCs Banks

Public Sector Banks ▪ ¾ of total credit ▪ Limited by high NPA ▪ Low CAAR (Basel-III) ▪ High levels of bureaucracy/ interference NBFCs ▪ Diversified geographical presence ▪ Higher assessment ability ▪ Limited by cost of funds and capital investment Private Banks ▪ Increasing NPA ▪ Limited Geo. reach ▪ Limited assessment ability as compared to a NBFC

• Constrained credit growth
• Structural issues
• Higher NPA
• Low rating and leverage
• Long term sustainable ROE is challenged
• Muted equity value creation.
• Healthy credit growth
• Current players are limited by credit availability,

lower assessment ability & distribution reach.

• Pricing advantage & structural support available.
• Favorable demographics
• Increasing income
• Increasing debt appetite
• Faced with heavy price competition
• Needs strong capital base and a long gestation period

The NBFC Lending Market Can Be Broadly Divided Into Three Segments

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Consumer SME Corporate, Infra, Real Estate

Current Scenario Future Projection

• +

+ + + +

• Scalable business with

attractive returns Low gestation period

50 M 29% 560 B

MSMEs in India Contribution to India’s GDP Gross Value Add (US$)

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

Bridging the $300B gap will need $60-70B in incremental equity capital | Growth isn’t a challenge for small business financiers!

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10%

MSMEs with access to credit

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

Small Business Lending Isn’t a Small Business

₹ 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

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?

…leading to a Frustrating Borrowing Experience for Small Businesses

Time consuming

• ffline process

Non-tailored credit assessment Rigid collateral requirements Product mismatch

Traditional Lenders remain unfocused on SMEs due to Business Model Diversity

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

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.

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Specialized SME Lenders Traditional NBFCs Banks

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

…a Trend Previously Witnessed in Consumer Finance

Specialists vs. Generalists | A comparison of value creation by select NBFCs over a 5-year period

On an average, specialized NBFCs have created long-term value for shareholders | These companies have leveraged their deep knowledge of their segments to generate faster AUM growth/better ROEs as compared to generalist NBFCs

AUM CAGR between FY14-19; ROE for FY19

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Stock returns scaled to 100 AUM Growth ROE 3% 20% 9% 18% 12% 13% NA 18% 13% 21% 19% 22% Specialized NBFCS

10 68 139 333 351 511 08/14 08/15 08/16 08/17 08/18 08/19

Reliance Cap L&T Finance Magma Fincorp Cholamandalam Muthoot Manappuram

Technology is Essential to Achieve a Specialized Model at Scale

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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

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▪ 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

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The U GRO Incarnation

The Assimilation of Aspirations

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Our Mission

‘To Solve the Unsolved’

India’s $600B+ SME Credit Availability Problem

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U GRO Capital | Who We Are

Knowledge Technology

Large Institutional Capital

₹920Cr (~$130M) 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

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

• Mr. Shachindra Nath

Executive Chairman and Managing Director

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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 Sandeep Kakar Chief Growth Officer AUM Managed: ₹ 150 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 Chief Executive Officer AUM Managed: ₹ 180 B

164

employee count

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

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

… and a Strong Second Layer Management Team

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Arun Arora Fraud Control Dhruv Suri Corp Channels Irem Sayeed Product & Strategy Makarand Mandke Policy Anshuman Tiwari Credit (Secured) Nilesh Asher Collateral Management Shelvin Mathews Credit (Unsecured) Subrata Das Analytics Sudhakar Mogera BFSI Partnerships Vivek Seshadri Strategy & IR Sunit Vakharia Technology Sunil Lotke Legal and Compliance

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

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…Supervised by an Independent Board Comprising of Industry Luminaries

▪ 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, Board Member of Capital Small Finance Bank ▪ 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, RBL Bank, 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 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 ▪ 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

Independent Members of the Board

Specialization: Government Policies Specialization: Credit, SME Specialization: SEBI Regulations Specialization: Finance Function Specialization: RBI Regulations Specialization: Audit, Tax

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Specialization: Retail Banking ▪ Ex-Head of Branch Banking, HDFC Bank, Board Member Equitas ▪ 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 Amit Gupta

NewQuest

Non-Executive Directors

Manoj Sehrawat

ADV

Kanak Kapur

PAG

Chetan Gupta

Samena

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

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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

Our Journey Thus Far

GRO-Plus GRO-Chain GRO-Direct GRO-Xstream

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26 31 80 108 187 276 422 515 575 647 702 753

Jan-19 Feb-19 Mar-19 Apr-19 May-19 Jun-19 Jul-19 Aug-19 Sep-19 Oct-19 Nov-19 Dec-19

First Term Loan from a Small Finance Bank First Securitization deal Traditional and BFSI Channels Activated Ecosystem Channel Activated SBI Co- Lending Partnership Bank of Baroda Co- Lending Partnership D2C Channel Announced – Dec 2019 Launch Completion of Asia Pragati Demerger Crossed $100M in Disbursals Crossed $10M in Disbursals Crossed $50M in Disbursals

AUM Growth (₹ Cr)

First Digital Partnership Signed First NCD Issuance Reached 100 employees Received A/A1 Rating from Acuite ICICI Co- Lending Partnership Crossed $100M in AUM First Term Loan from a General Bank

U GRO Tech Module Development

First Machinery Loans Partnership Achieved Profitability for Q3 FY20

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

Metric

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

₹1,073Cr

9

₹753Cr

3 67% 311 7,512 15 164 26

Where We Stand Now

Data as of 31 December 2019

Know More, Grow More Sector based approach to specialization

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27

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

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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

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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 29

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

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A Seamless, Customized Customer Journey

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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

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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% 33

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

Credit Risk – Supplemented by Enterprise Risk

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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 in FY20 Single sector concentration is capped at 25%, single geography is capped at 20% The BFSI channel to be <20% of the overall portfolio in FY20 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

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An In-house Technology Platform that Enables Our Underwriting Process

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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

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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

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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

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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

40

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

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| 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

42

43

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

44 ▪ 311 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 26 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…

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▪ 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 $700M+ 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

46

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

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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

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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 > $7M

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)

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Launched in Dec 2019

Distribution Network

50

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

51

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…

52

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 53 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

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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

55

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

56

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

57

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: $67B) Secured Business Loans Signed October 5, 2019

State Bank of India

(Loan Book: $312B) Small Ticket SBL & UBL Signed November 8, 2019

58

ICICI Bank

(Loan Book: $84B) 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

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Progression of Growth Metrics

82 300 702 1,073

FY19 Q1 FY20 Q2 FY20 Q3 FY20

Total Disbursals (₹ Cr)

80 276 575 753 FY19 Q1 FY20 Q2 FY20 Q3 FY20

AUM (₹ Cr)

49 525 6,395 7,487 FY19 Q1 FY20 Q2 FY20 Q3 FY20

Number of Customers

76 131 232 311 FY19 Q1 FY20 Q2 FY20 Q3 FY20

GRO Partners

3 11 15 21 FY19 Q1 FY20 Q2 FY20 Q3 FY20

Ecosystem Partners

10 19 19 26 Q4 FY19 Q1 FY20 Q2 FY20 Q3 FY20

BFSI Partners

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16% 18% 10% 15% 17% 10% 9% 5%

Sectoral Mix*

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

Portfolio Snapshot (As on Dec 31, 2019)

Geographical Mix*

*Includes Traditional and Ecosystem Channels

▪

Delhi/NCR

▪

Karnataka

▪

Gujarat

▪

Telangana

▪

Maharashtra

▪

Rajasthan

▪

West Bengal

▪

Tamil Nadu

▪

Haryana

▪

Uttar Pradesh

▪

Punjab

▪

Chhattisgarh 21% 12% 7% 8% 14% 9% 8% 9% 1% 1% 5% 3% 67% 33%

Secured Mix

Secured Unsecured

Well diversified by geography and sector | Majority secured book, with unsecured running down faster through end FY20

Presence in 100+ cities across India

Balance Sheet

▪ Remain liquid with ₹277 crores

• f

immediate liquidity on the balance sheet ▪ ₹66 crores obtained from the conversion

• f warrants in Q3

▪ CRAR: 88.9% ▪ GNPA: 0.07%

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Balance Sheet (₹ Lakhs) Q3 FY20 Q2 FY20 Financial Assets 106,436 91,682 Loans 74,722* 56,729 Cash and Investments 23,317 29,310 Other Financial Assets 8,398 5,643 Non-Financial Assets 4,941 4,882 Total Assets 111,377 96,564 Financial Liabilities 20,942 13,434 Trade/Other Payables 905 825 Borrowings & Debt Securities 16,690 9,359 Other Financial Liabilities 3,347 3,251 Non-Financial Liabilities 364 397 Total Equity 90,071 82,733 Equity Share Capital 7,053 5,690 Other Equity 83,018 77,043 Total Liabilities + Equity 111,377 96,564

*AUM as of Q3 is ₹753Cr, the ‘Loans’ figure adjusts for net payouts and ECL as per Ind-AS

Income Statement

63

Ind-AS accounting standards have been in place since Q1 FY20

Income Statement (₹ Lakhs) Q3 FY20 Q2 FY20 QoQ Q3 FY19 YoY Interest Income 2,389 1,517 57.5% 1,014 135.6% Other Operating Income 501 649

• 22.8%

599

• 16.4%

Less: Financing Costs 523 116 350.8% 39 NA Net Income 2,366 2,050 15.4% 1,574 50.3% Operating Expenses 1,683 2,410

• 30.1%

1,238 35.9% Provision 104 250

• 58.4%

2 NA Profit Before Tax 579 (611) NA 334 73.3% PBT after Exceptional Items 579 (347) NA 334 73.3% Less: Tax (110) (22) NA (19) NA Profit/(Loss) for the period 689 (325) NA 353 95.1% Other Comprehensive Income (Net

• f Tax)

(6) 3 NA

• NA

Total Comprehensive Income 683 (322) NA 353 93.4%

▪ Operating income has increased as a result of expansion of loan book ▪ The reduction in

• perating

expenses as compared to Q2 FY20 is primarily due to us having previously incurred one-time expenses that were not present in Q3