Retail Banking Product Recommendation

ML recommenders in bank apps.

recommendation

0named models

9candidates

3deployments

3in Indonesia

Named Models

The research names no model for this use case.

Where this comes from

Models the research names for this use case. Research, with sources on each model record.

Who Runs It

production, 2planned, 1

Bank MandiriCountry: IndonesiaGenerative AI marketing content for Livin' products and AI personalisation on Livin' pre-login and home screens (models not stated)Vendor: not statedproductionDate5 Oct 202527 million users reached by generative AI content; take-up up to 1.7 times; more than 300 assets for more than 30 products; content production up to 3 times faster (company claims)Evidence: company statementConfidence: lowSource: investortrust.id

Bank Rakyat Indonesia (BRI)Country: IndonesiaPersonalized Product Recommendation on Cloudera AIVendor: ClouderaproductionDate–Reported 30% uplift in engagement and approval rates; integrated into BRImo and BRISPOTEvidence: company statementConfidence: lowSource: cloudera.com

OCBC IndonesiaCountry: IndonesiaGenerative AI and transformer models for personalised recommendations on the Cloudera hybrid data platformVendor: ClouderaplannedDate2 Jul 2024None statedEvidence: company statementConfidence: lowSource: itnews.asia

Where this comes from

Documented uses by named organisations. The evidence column says who made the claim.

Candidate Models

OneRec-Foundation 1.7BKuaishou, recommendationReleasedJan 2026open weightslast 18 months

OneRec-Foundation 8BKuaishou, recommendationReleasedJan 2026open weightslast 18 months

OneRec-ThinkKuaishou, recommendationReleasedOct 2025last 18 months

OneRec-V2Kuaishou, recommendationReleasedAug 2025last 18 months

MTGRMeituan, recommendationReleasedMay 2025last 18 months

HSTU (Generative Recommenders)Meta, recommendationReleasedFeb 2024open weights

OneRec (V1)Kuaishou, recommendationReleasedFeb 2025none

DCN V2Google, recommendationReleasedAug 2020none

DLRM-dcnv2Google, recommendationReleasednot in the notesnone

Where this comes from

Derived, not researched: models in the directory whose class matches a class this use case uses, excluding family records and models shut down or deprecated. Ranked by how many fit facts they meet, then by release date. Each fit fact is read from the model record.

Use Case

Industry: finance and insurance
Model classes: recommendation
Benchmarks or datasets: not in the notes
Regulatory notes: Surat Edaran Menkominfo 9/2023 Etika Kecerdasan Artifisial, Kementerian Komunikasi dan Informatika (now Kementerian Komunikasi dan Digital)Retail banking product recommendation is an AI-based service run by an electronic system operator, and the circular asks such operators to build and use AI on the values of inclusivity, transparency, humanity and security.
UU 27/2022 Pelindungan Data Pribadi, DPR and President of the Republic of Indonesia (administered by Kementerian Komunikasi dan Digital)Retail banking product recommendation processes personal and financial data of customers, which the law treats as a specific category of personal data, so the controller needs a lawful basis, must protect the data and must honour data subject rights.
Tata Kelola Kecerdasan Artifisial Perbankan Indonesia (2025 guideline), Otoritas Jasa Keuangan (OJK)Retail banking product recommendation is an AI use in banking, which OJK's AI governance guideline covers across the AI life cycle, including bias, explainability and cyber risk.
Panduan Kode Etik Kecerdasan Buatan yang Bertanggung Jawab dan Terpercaya di Industri Teknologi Finansial (2023), Otoritas Jasa Keuangan (OJK) with the fintech associationsRetail banking product recommendation is also offered by fintech providers, for whom OJK's AI code of ethics sets principles of being beneficial, fair and accountable, transparent and explainable, and robust and secure.
POJK 22/2023 Pelindungan Konsumen dan Masyarakat di Sektor Jasa Keuangan, Otoritas Jasa Keuangan (OJK)Retail banking product recommendation deals directly with financial consumers, so the provider's duties on fair treatment, clear information, data protection and complaint handling apply.

Where this comes from

From the industry tracks T08 to T10 of the research notes.

R&D Topics

Links to R&D topics are awaiting review.

Where this comes from

Which R&D topics would most change this use case. Drafted by Claude from the topic definitions and the use case; proposed until approved.

Incidents

UK High Court Found Sky Betting & Gaming Unlawfully Used Automated Profiling and Targeted Marketing to Exploit a Recovering Problem GamblerUnited Kingdom, 2017-07-28, financialIn the UK, the High Court found that Sky Betting & Gaming unlawfully used automated profiling and targeted direct marketing to pursue a recovering problem gambler from July 28, 2017 onward without valid consent.

Where this comes from

Documented failures, harms or misuse in this kind of use, Indonesia first, then the region, then well-known cases elsewhere (AI Incident Database, OECD AI incidents monitor, reputable news). Not a claim about any deployment listed here.

In Neighbouring Countries

UOB (UOB TMRW app)Singapore, production, 2024UOB TMRW AI and ML personalised recommendations

Where this comes from

Documented deployments of this use case in Malaysia, Singapore, Thailand, Vietnam and the Philippines, each with its source.

Opportunities

Opportunities are awaiting review.

Where this comes from

Gaps found by rule in what the directory holds for this use case. Each is a proposal for review.

Links

IndustryFinance29 use cases, 46 deployments

Use CaseRetail Banking Product RecommendationFinance

Modelsnone recorded

Who Runs It

Bank MandiriIn production, 5 Oct 2025

OCBC IndonesiaPlanned, 2 Jul 2024

Bank Rakyat Indonesia (BRI)In production

Graph

Deployments 3

Bank MandiriGenerative AI marketing content for Livin' products and AI personalisation on Livin' pre-login and home screens (models not stated), Indonesia Bank Rakyat Indonesia (BRI)Personalized Product Recommendation on Cloudera AI, Indonesia OCBC IndonesiaGenerative AI and transformer models for personalised recommendations on the Cloudera hybrid data platform, Indonesia

Sources

PT Bank Rakyat Indonesia | Customers | Cloudera cloudera.com https://cloudera.com/customers/bank-bri.html
Bank Negara Indonesia Strengthens Partnership with Cloudera to Scale AI-Powered Business Transformation | AAP aap.com.au https://www.aap.com.au/aapreleases/globenewswire9507748/

To cite this page: Project AURION, AI Use-Cases Research & Innovation, "Retail Banking Product Recommendation", https://aurion.semai.id/usecases/fin-product-recommendation/, records of October 2026.