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Case Study

LEADING MICRO-FINANCE FIRM IN INDIA

Introduction

  • Micro-finance loan provider based in India
  • $200 mn loan book
  • More than 1.5 mn active loan accounts
  • Based on Grameen model of group lending

Problem Statement

  • Duplication across loan books, same customer with multiple profiles and dummy entries
  • Very high collection costs due to manual cash collections
  • Poor integration between systems
  • Long time lag between actual and reports

Requirement

  • Streamline operations
  • Provide granular visibility on entire loan book
  • Provide reporting in international formats and raise funding from UK

Solution

  • Put together full stack tech team to integrate operations across all centers
  • Limit manual handling of cash via two-factor SMS authentication
  • Faster reconciliation of cash with tech based MIS system ensured proper visibility of risk to all stakeholders
  • Term sheets from international banks was secured for the client
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DEVELOPMENT FINANCE PROVIDER IN UK

Introduction

  • P2P funded provider of development finance loans to UK real estate developers
  • £125 mn loan book
  • Complex loan type due to bullet payment of interest and multiple drawdown stages
  • Loan were like pawn lending with regular accrual of interest with payment at maturity but interest costs to investors were paid monthly

Problem Statement

  • 5 year old loan book
  • Missing and duplicate data
  • Excessive paper dependence with very low digitization
  • Asset valuation was not updated at each drawdown stage
  • No clear funding strategy

Requirement

  • Data cleaning and reconciliation of loan book with paper trail
  • Funding on loan book to match asset cash flow
  • Prepare investor presentation and organize road shows including obtaining credit rating

Solution

  • Cleaned present and historical loan records to remove inconsistency
  • Post data cleaning put together cash flow model to project funding requirements
  • Warehousing line was arranged with a refinancing through a securitization structure
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COMMERCIAL PROPERTY ACQUISITION IN LONDON

Introduction

  • Client was looking to acquire a portfolio of four Serviced Apartments in London
  • £190 mn acquisition notional
  • Each property is a standalone asset which has its own operating cash flows
  • Senior, Mezz and Equity sources of capital, lease operator, management company and several layers of charges

Problem Statement

  • Each asset is a standalone performing entity and has its own specific costs and allocation of resources
  • The seasonality of ADR/RevPAR meant lot of flexibility required to model each asset
  • All cashflows combine at the acquisition vehicle level and the distributions are made at the consolidated level
  • Although everything is consolidated, any asset can be disposed anytime individually

Requirement

  • Granular modelling of each asset, profitability and ADR/RevPAR of each asset is monitored individually
  • Consolidate all the operating cashflows and allocate cashflows to all sources of capital depending on their specific contracts/termsheets
  • Coupon Buffers, Interest Coverage, Sensitivity Analysis, Missed coupon tracking, IRR Hurdle check

Solution

  • A comprehensive model was presented which gave the flexibility to add/remove assets as required
  • Lot of variables which gave the client freedom to stress test and understand the portfolio in great granularity
  • All cashflow waterfall was directly taken from the different terms with different capital providers
  • Ongoing support and comparable analysis was also provided along-with primary market research
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AUTO LENDING PLATFORM FINANCIAL MODEL

Introduction

  • Client was looking to set-up a new Auto lending platform
  • UK based with support staff in India
  • The model has to be scaled up as the business grows from a zero start loan book
  • Senior and Equity sources of capital, with different term structure and repayment profiles and complex waterfall

Problem Statement

  • Three different kinds of loans depending on the underlying credit, each with its own Default and Prepayment curves
  • The recovery lag is different for each kind of auto loan, reserves requirement vary accordingly
  • As each loan pay both principal and interest every month, proper breakdown and allocation is necessary
  • Monte Carlo Simulations and CPR/CDR methodology used to compare the defaults curves

Requirement

  • There was a ramp up period of 3 years and stabilization period of 5 years and then the book was run down to maturity
  • Monthly payment of both interest and principal and defaults from earlier periods need to be tracked and reserves to be allocated correctly
  • Loan book modelling to be separate from the platform as assets needed to be bankruptcy remote

Solution

  • There was a ramp up period of 3 years and stabilization period of 5 years and then the book was run down to maturity
  • Each specific cashflow was subject to its CPR/CDR probability and the cashflows were combined and tracked across periods to reflect collectively the cash position and capital at risk numbers at any point in time
  • Each cost had its own scaling factor and the scaling factor were also non-linear which gave the flexibility to model the whole business profile for 5-7 years in a single comprehensive model
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