Advisory for the implementation of transaction lending Bookmark has been added
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Advisory for the implementation of transaction lending
Support for the initiation of a loan business based on data such as transaction histories, with a view to entry into finance
The entry of non-financial actors into the field of finance has progressed in recent years, and transaction lending, which utilizes data, has become a leading service in the industry. Deloitte Tohmatsu’s team, composed of experts in fields such as big data, IoT, Fintech, AI, and credit risk, provides a full array of support services, from advance surveys to formulation of implementation plans, for clients looking to implement transaction lending.
Explore Content
- What is transaction lending?
- Service overview
- Phase 1: Advance survey
- Phase 2: Scoring model PoC
- Phase 3: Implementation planning
What is transaction lending?
Transaction lending involves collecting various types of data, including transaction history data such as purchase records and customer assessments, and using that data to evaluate the state of a business in real time in order to approve or deny a loan to said business. Loan decisions have traditionally been based on business plans centered on financial statements, but transaction lending allows for the shortening of screening periods by deciding on creditworthiness and loan conditions on the basis of a scoring model.
| Traditional lending | Transaction lending | |
|---|---|---|
| Screening | Loan decision made on the basis of a business plan centered on the financial statement | Loan decision made on the basis of real-time assessment of business situation, sales, inventory, reputation, etc |
| Information used | Financial statements, business plans, guarantees, etc. | Purchase and payment data, customer evaluations, products handled, etc. |
| Screening period | From 2 weeks | Can be as short as a few minutes |
Service overview
Deloitte Tohmatsu’s advisory service for the implementation of transaction lending is provided by a team of professionals composed of financial business experts, credit risk advisory experts, and analytics experts proficient in constructing scoring models that make use of big data and AI, and involves the provision of effective advice across the three phases described below.
Phase 1: Advance survey
The advance survey includes introduction of existing initiatives, examination of the use value of owned data, examination of a business model, and formulation of a proof of concept (PoC) plan (roadmap). Based on examples of initiatives from both Japan and elsewhere, we will examine to what extent the data held by the company aiming to implement transaction lending can be used, and review the company’s business model, including targets and monetization, after which, looking ahead to the modeling phase, a PoC plan (roadmap) will be formulated.
Phase 2: Scoring model PoC
In the scoring model PoC, data to be analyzed and related materials are specified, and once the characteristics of the data set are understood and its quality confirmed, integrated data for analysis is prepared. Points of contention on the way to building the business are then reviewed and a roadmap is drafted. In the scoring model PoC phase, we will also use AI and other analysis technology to analyze actual data that can be used.
Phase 3: Implementation planning
In the implementation planning phase, we will begin with the formulation of a concrete scheme for starting up the transaction lending business. After designing credit operations, including the incorporation of legal, system, and other perspectives, we will formulate a detailed roadmap for implementation.
Professionals
