the next era of lending business - bot

Roongkiat Ratanabanchuen, Ph.D.

The next era of

lending business

1

Alternative data and pain points in lending

business

Prepared by Roongkiat Ratanabanchuen, Ph.D. 2

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Why do we need alternative data?

Prepared by Roongkiat Ratanabanchuen, Ph.D.

What are the main problems

in terms of lending?

Thin file

No-hit

(No bureau

record)

Credit invisible

Asymmetric information!Moral hazard

Adverse selection

1. Transaction-based lending 2. Relationship-based lending

Recent credit, 5%

Depth of credit, 21%

Balances, 11%

Available credit, 3%

Payment history, 40%

Utilization, 20%

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Information for making lending decision

Prepared by Roongkiat Ratanabanchuen, Ph.D.

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Information for making lending decision

Prepared by Roongkiat Ratanabanchuen, Ph.D.

Digitization

Big data stored in file-based

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Information for making lending decision

Prepared by Roongkiat Ratanabanchuen, Ph.D.

Conventional data

• GDP, Inflation, Consumption

• Import/Export

• Financial statement

• Annual reports

• Corporate news

• Changes in shareholder structure

• Industry outlook

Alternative data

• Satellite imagery

• Social data

• Google trend

• IoT sensor device

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Information for making lending decision

Prepared by Roongkiat Ratanabanchuen, Ph.D.

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Fintech providing information

Prepared by Roongkiat Ratanabanchuen, Ph.D.

The future of lending landscape

Prepared by Roongkiat Ratanabanchuen, Ph.D. 9

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Alternative data for lending

Prepared by Roongkiat Ratanabanchuen, Ph.D.

Players in the credit scoring are

now experimenting to use

alternative data to predict default

rates.

Source: Rieke (2014)

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Alternative data from smartphones

Prepared by Roongkiat Ratanabanchuen, Ph.D.

Mobile banking platform

Location services

Transaction data – bills, purchases, sends and receives

Communication habits

Clickstream data

Internet usage – web site, facebook, Instagram, whether forecasts

Call patterns – timing, frequency, and duration of calls

Prepaid-minute purchase patterns

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Alternative data from smartphones

Prepared by Roongkiat Ratanabanchuen, Ph.D.

Alipay

Sesame

credit

score

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Alternative data from smartphones

Prepared by Roongkiat Ratanabanchuen, Ph.D.

Utility bill and supplier data

Bill payments – frequency and timing

Wholesale suppliers – demand patterns and payment patterns

POS devices and retailer loyalty program

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Alternative data from smartphones

Prepared by Roongkiat Ratanabanchuen, Ph.D.

Utility bill and supplier data

What is actually

the main reason

of E-market place?

Source: BOT

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Alternative data from smartphones

Prepared by Roongkiat Ratanabanchuen, Ph.D.

Psychometric testing

Knowledge, abilities, attitudes and personality traits

Cognitive biases – long and short term biases, opportunisms, and overconfidence

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Alternative data from smartphones

Prepared by Roongkiat Ratanabanchuen, Ph.D.

Public records

Address zip code

Records of disbursement

Health inspection reports

Police reports

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Alternative data from smartphones

Prepared by Roongkiat Ratanabanchuen, Ph.D.

Social media data

Social media usage

Posts and texts

Image analysis

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Lending landscape in Thailand

Prepared by Roongkiat Ratanabanchuen, Ph.D.

Relationship-based lending

Transaction-based lending

Presented by Roongkiat Ratanabanchuen, Ph.D. 19

Thank you