The Big 5
Jan 27 2014
Regardless of the nature of financing, size of the deal, type of borrower and financing entity, activities in the financing business can be classified under find, formulate, filter, finance and facilitate
Regardless of the nature of financing, size of the deal, type of borrower and type of financing entity, the activities involved in financing business can be classified in simple terms as — find, formulate, filter, finance and facilitate.
The sign board on the lending relationship street has changed overtime from “one way traffic” to “two way traffic”: banks are increasingly focusing on reaching out to prospective customers.
Deployment of business intelligence models, expansion of partner networks and preapproved loan offers though alternate channels are clear indicators of proactive customer acquisition strategies.
However, these proactive acquisition strategies would only be successful if a systematic lead conversion process is established. Putting in place an IT environment that seamlessly integrates the customer acquisition, lead management and conversion functions across channels with focus on providing actionable information is necessary for effective lead conversion process.
Risk vs return is the biggest trade off that lenders have to consider. credit filtering is the first step towards arresting/ minimising the risks inherent to lending, for the simple reason that prevention is not just easier than collection, but also much cheaper.
Incomplete and discrete information, subjectivity, inconsistent risk calculations, insufficient portfolio considerations are some of the factors that adversely affect the efficacy of a credit filtering/ approval process. Prescribing lending limits for a single borrower/ group of associated entities, capping exposure concentrations at various levels like industry/sector, employing scientific risk rating models and putting in place risk based pricing mechanisms can help lenders minimise risk and maximise yield.
Automated credit origination systems, apart from reducing turnaround times and underwriting costs, most importantly, reduce subjectivity by minimising manual intervention, add accuracy to the risk ratings through standard rules, ensure compliance to underwriting policy guidelines without bias through preconfigured checklists, ensure smooth business process management through workflows and achieve optimum pricing through rule based risk adjusted pricing mechanisms.
The loan onboarding or closing process involves functions like preparation and execution of loan/collateral documents, pre-disbursement condition checks followed by loan funding.
With the growing complexity in loan structures, loan documentation has become intricate. Standard credit agreements may need to be revisited every time a new credit facility is approved or any credit actions are performed on existing credit facilities. The boiler plate language in the loan agreements is dependent on a wide variety of factors like type of entity, type of credit facility, secured or not, type of collateral, type charge to name a few. An automated document generation system, by providing a flexible rule based text assembly mechanisms and integrations with origination systems for data mapping can facilitate this complex process of credit agreement generation.
Straight through processing plays an important role in the facility onboarding process by ensuring data integrity is maintained. Lending systems that support seamless integration with origination systems, provide for drawdown condition checks and support rule based exceptions for executing funding requests can ensure smooth onboarding and funding.
If change is the only constant, innovation is the only force that can keep lenders meet change.
Split loans, equity lines, revolving loans with term out options, loans to finance energy efficient home improvements, offset loans, derivative linked credit lines all are a result of lending innovations to meet the ever changing borrowing needs.
Ability to predict and adopt to changing market needs is vital for the current day lenders. Lending systems with support for flexible product definitions, deal structuring and modelling features can immensely help in formulating and offering quickly credit solutions in line with the market expectations or requirements of a specific borrower.
Credit servicing life cycle consists of a myriad functions ranging from simple transactions like billing and payment collection to tracking non-payments, restructuring of facilities, provisioning, write off / charge off. A robust servicing system is a must to facilitate processing of customer requests and at the same time ensure credit operations are in compliance with internal as well as regulatory controls. In general, borrower’s credit worthiness does not deteriorate overnight. Ability to repay weakens over a period of time. Lending systems which support features like capturing and tracking of credit conditions/covenants, provide actionable information on repayment history, alert the overdue positions and deterioration in the collateral coverage can help simplify the complex credit monitoring process.
In a market place which is becoming challenging by the day, lenders are forced to cut costs, innovate in order to respond quickly to the changing market demands, reduce risks and increase profitability. An enterprise level IT environment that seeks to provide systematic and process driven solutions throughout the lending lifecycle, can help fine tune the critical five aspects of financing. zz
(The writer is product manager, Infosys Finacle)