RenaAi (legal name: 주식회사 레나에이아이) is a B2B data company that builds alternative data with its own methodology and connects it to global financial markets. It turns source data from three domains (market areas, equities, and patents) into indicators such as probability of default, pre-disclosure change signals, and patent quality scores, and supplies them to lenders, rating agencies, and asset managers through APIs and data feeds. The company was founded in Seoul on April 21, 2026.

Are RenaAi and 레나에이아이 the same company?

Yes. The registered legal name is 주식회사 레나에이아이, and RenaAi is its English brand name. The official website is renaai.co. Several overseas projects and accounts use similar names, but they are not related to us. RenaAi does not run a cryptocurrency or trading business.

What is alternative data?

Data that sits outside financial statements and credit records. Examples include store density and sales volatility in a market area, regulatory filing and trading-flow patterns of listed companies, and the rights structure of patents. Even where the fields that conventional assessments rely on are empty, this data can provide a basis for judgment.

What does alternative credit scoring for small businesses look at?

It looks at the conditions of the market area a business operates in, not at the individual borrower. Indicators include the concentration of same-industry stores, sales volatility, and co-movement with neighboring market areas. Businesses with no credit history can be assessed with these signals. Without using any financial information, we confirmed an out-of-sample AUC of 0.83.

What is equity alternative data?

For listed companies, we align sources that differ in format and frequency, such as regulatory filings, prices, and trading flows, on a single standard and read them together. The method carries the normalization we use for market-area data over to the individual stock level, and turns changes that move before earnings are announced into growth and risk signals. This is a data and indicator supply service. It is not investment advisory or discretionary investment management, and it is not a recommendation to buy or sell any security.

What is patent intelligence?

Data that reads patents by quality, not by count. We quantify forward citations, global family, enforceability, and design-around difficulty into a patent quality score, and connect it to company assessment, investment and valuation, and IP finance such as collateral and securitization.

What does an AUC of 0.83 mean?

AUC measures how well a scoring model separates risky cases from safe ones. Pick one business that actually ran into trouble and one that did not, at random: AUC is the share of such pairs in which the model gave the troubled business the higher risk score. A value of 0.5 is a coin flip and carries no information; the closer to 1, the better the separation. In finance, a model above 0.7 is generally considered usable in practice, and above 0.8 is considered strong. Card companies' retail scoring, which uses decades of payment history, falls in the 0.70 to 0.80 range. RenaAi confirmed an out-of-sample 0.83 without using a single line of credit history.

Why does out-of-sample matter?

It means the model was scored on data from a period that was not used to build it. Scoring on the training data always looks good, so it proves nothing. We rolled the clock back to 2019, made predictions without using any later data in the score calculation, and then compared them with what actually happened. That is why we publish only out-of-sample scores.

What evidence supports the technology?

Three things. An out-of-sample AUC of 0.83 confirmed using market-area data alone, without credit history; a patent application filed with 9 claims; and academic validation. A paper has been submitted to Finance Research Letters (Elsevier, SSCI); it has not been accepted for publication. Issue No. 86 (Summer 2026) of Credit Finance, the journal of the Credit Finance Association of Korea (CREFIA), published an article by Professor Hyuntak Lee and CEO Byung-Geun Choi, "Small business credit scoring and the use of market-area information," which was distributed to member companies.

Who runs the company?

The company is led by CEO Byung-Geun Choi. He studied electrical engineering at Seoul National University, earned a master's in Management of Technology at EPFL, and completed doctoral coursework (ABD) in industrial engineering at the University of Michigan, Ann Arbor. He researched credit risk at the NUS Risk Management Institute (RMI), and has served as a global equity fund manager at Samsung Asset Management, a team head at NH-Amundi Asset Management, and head of product strategy at Korea Investment Management. At RenaAi he leads the alternative data methodology, credit and valuation models, and the data supply business. Patent rights and legal matters are handled by CLO Yoo Yeon, a patent attorney and lawyer. Business development and operations with institutional clients and partners in Korea and abroad are led by co-founder and COO Michael T. He is a former Relationship Manager at Société Générale CIB in Hong Kong, where he covered global hedge funds and connected them to financial products, and a crypto expert who managed digital assets as VP, Trading and Investment at Asia Innovations Group.

Institutions that run assessment models, such as credit bureaus, credit finance companies, and asset managers, inquire about data partnerships and supply. Technology companies and research institutions that hold patents also look for patent intelligence. Inquiries are welcome at renaai.co/en/inquiry or info@renaai.co.

Is RenaAi a credit rating agency?

No. RenaAi is not a licensed credit rating business that assigns and sells ratings or scores. It is a B2B data company that supplies source data, which financial institutions and asset managers feed into their own assessment models. Final underwriting and decisions are made by the financial institutions that use the data.

Is RenaAi an AI company or a data company?

A company that makes data. We use AI and statistical models as tools to organize scattered source data and separate out signals. What we sell is not the model but the indicators and data it produces.

Who uses each of the three data sets, and how?

Small business probability of default (PD) built from market-area data is used in underwriting by lenders such as savings banks and capital (consumer finance) companies, and by rating agencies. Pre-disclosure change signals from equity alternative data are used by asset managers and research teams for stock screening and risk monitoring. Patent quality scores are used for company assessment, investment, and IP finance.

In what form is the data delivered?

Through a REST API and data feeds. Before adoption, a PoC applies the data to your own data and models first so you can see the effect.

Can it be used alongside existing credit scoring models?

Yes. It does not replace existing models; it fills their gaps. You can combine market-area and patent signals with your portfolio and scoring models and measure the improvement directly in a PoC.

After you contact us, we agree together on the scope for combining market-area and patent signals with your portfolio and scoring models, then test the effect, for example PD estimates for businesses with no credit history or patent quality indicators. The first validation is free and confidential, and is handled personally by our CEO, a former fund manager. We get back to you within 24 hours of your request.

How does RenaAi make money?

From B2B data supply contracts. The basic structure is usage-based API pricing plus annual data feed subscriptions.

What is probability of default (PD)?

The likelihood that a borrower will default within a given period, expressed as a probability between 0 and 1. It is the basic indicator lenders use to decide whether to lend and at what rate. RenaAi estimates this value from market-area data, including for small businesses with no credit history.

How is the data produced?

In three steps. First, normalization: data that differs in format and frequency, such as spatial coordinates, filing text, and patent claims, is aligned on a single standard. Next, signal separation: temporary noise is filtered out so that only signals tied to real risk and value remain. Finally, standardized indicators: the signals become indicators such as probability of default, a leading market-area risk index, and patent quality scores, delivered through an API.

What does RenaAi's patent protect?

A patent application has been filed with 9 claims. Its core is protecting the methodology itself for scoring businesses with thin credit files (Claim 9), not just its outputs. The application was handled by Kyung-min Woo, representative patent attorney at Meta Patent Law Office.

How do patent count and patent quality differ?

How many patents a company holds says little about its technological competitiveness. RenaAi looks at how often a patent is cited (forward citations), in how many countries it is filed (global family), how solid the rights are (enforceability), and how hard it is for competitors to work around (design-around difficulty).

About

We build alternative data
and connect it to global financial markets

RenaAi (레나에이아이) builds three kinds of alternative data (market-area, equity, and patent) with its own methodology, validates it through papers and a patent application, and connects it to financial markets in the forms lenders, rating agencies, and asset managers use: APIs, indices, and subscriptions.

This page introduces who is building that whole process, and what experience they bring to it.

Data partnership & supply inquiry See the founder’s background

At a glance

Name: RenaAi · 레나에이아이 (Renaissance + AI)
What we do: Create alternative data → validate → connect to financial markets
Data assets: Market areas (alternative credit scoring for small businesses) · equity alternative data · patent intelligence
Delivery: APIs · indices · subscriptions
Users: Lenders · rating agencies · asset managers · investors
Team: Byung-Geun Choi, CEO · Yoo Yeon, CLO · Michael T., COO

Name

Renaissance and AI

Our name combines two words. In Korean, it is written 레나에이아이.

Rena · Renaissance

Just as the 15th-century Renaissance broke down the boundaries between art, science, and philosophy and carried civilization forward, RenaAi uses data to break down the boundary around ‘what could not be assessed.’ We call it a renaissance: bringing back into the market what sat in the blind spots of assessment, such as 3.16 million small businesses turned away for lack of credit history, or patents sleeping in a drawer.

AI · artificial intelligence

AI is the means to normalize scattered public, market-area, and patent data into a single ontology, and to extract signals at a scale no person could read. The entire layer that turns data into ‘signals’ is AI, and on top of it, collective intelligence and networks make the judgment.

What we do

We make the data ourselves and carry it through to execution

Our scope differs from companies that collect and sell data, or AI companies that automate tasks. We build alternative data ourselves, make judgments with it, act on those judgments, and take responsibility for the outcome.

Data vendor	AI solutions company	RenaAi
Collects, processes, and sells	Focused on task automation	Owns source alternative data (patent · papers)
Interpretation left to the client	Cost-reduction KPIs	Interpreted through collective intelligence
No accountability for outcomes	Sells a tech stack	Carries through to execution
Competes on generic data	No proprietary data	Outcome = higher enterprise value

Hypothesis

If what could not be assessed becomes assessable,
what becomes possible next?

Data creates value, value creates judgment, and judgment moves capital. That is why we start from alternative data and arrive at private equity.

Methodology

Where the methodology comes from

Experience analyzing the micro-level world of market areas with multidimensional ontologies and attention mechanisms carried over into enterprise value analysis and AI adoption strategy. This is the foundation of the data creation stage.

Multidimensional ontology design
To analyze the micro-level world of market areas, he designed a methodology that integrates heterogeneous data (industry, foot traffic, sales, time of day, competitive density) into a single ontology. That experience became a core capability of RenaAi: redesigning internal company data into a structure AI can read.
Attention-based micro analysis
Applied the Transformer attention mechanism to market-area analysis to break down, layer by layer, "how much each variable contributes to sales." The same approach decomposes a company's EBITDA drivers and quantifies where AI intervention lifts enterprise value the most.
Investment-grade EV modeling
Ten years as a fund manager, personally modeling EBITDA, multiples, and EV for thousands of companies. Combining a numbers-first view of companies with the ability to translate AI adoption into EV, RenaAi delivers its assessments in the language investors use.
Connecting to private capital markets
In the Liberti project, while pursuing license applications for a Singapore RMO and a Japan PTS, he planned and designed a structure linking assessed enterprise value to an unlisted-asset exchange. The path by which RenaAi connects data to capital markets starts from this experience.

Why we started

Why this company was founded

“I am not someone who analyzes data.
I have spent my career looking in data for signals that move capital.”

Byung-Geun Choi · Founder & CEO

01
Seoul National University, electrical engineering
2004 –
Training in framing complex realities as problems of systems and data.
TodayOntology design: aligning heterogeneous public data on a single standard
02
A*STAR SIMTech · data research
2013 – 2014
Research on finding patterns and signals in large-scale data.
TodayThe foundation for market-area networks and graph-based analysis
03
NUS Risk Management Institute · credit risk
2017 – 2019
How to translate signals into the language of finance: probability of default. Product Manager for the BuDA toolkit, co-developed with the IMF.
TodaySBCR: alternative credit scoring that carries forward intensity over to market-area data
04
Global equities · quant investing
2019 – 2023
A step beyond data analysis: judging how much a signal actually connects to value.
TodayValuation: the standard for turning signals into value
05
Asset management product strategy
2023 – 2024
A level above individual investments: designing how data becomes a product and reaches capital markets.
TodayAPIs · indices · subscriptions: a business that sells the same engine repeatedly
06
Liberti SG / JP · exchange planning
2024 – 2026
Planned and designed an exchange for unlisted assets while pursuing license applications for a Singapore RMO (Recognised Market Operator) and a Japan PTS (proprietary trading system).
TodayConnection: the path from data-based valuations to actual trades and capital
07
RenaAi
2026 –
Brings the previous six together inside one company.
TodayData → signal → value → execution → capital

Putting a value on something takes four perspectives

Engineer

“What is this technology?”

Electrical engineering · data research

“What is the signal in all this material?”

Ontology · models

Patent attorney · lawyer

“Is it protected by rights?”

Yoo Yeon, CLO

Fund manager

“So what is the asset worth?”

Byung-Geun Choi, CEO

One to read the technology, one to extract the signal, one to protect the rights, and one to set the value. Only when all four are on one team do you get numbers institutions will accept.

RenaAi is a company that uses AI and data to build what I kept looking for throughout my career: ‘value outside the financial statements.’

Founder

Byung-Geun Choi, CEO

The same story again, in chronological order, with what he actually did in each role.

ORCID 0009-0009-7540-7503 Google Scholar · Byung-Geun Choi LinkedIn

Education

Seoul National UniversityDepartment of Electrical Engineering
EPFLMaster's, Management of Technology
University of Michigan, Ann ArborIndustrial Engineering, doctoral coursework completed (ABD)

Role at RenaAi

Drawing on his experience in asset management and credit risk research, CEO Byung-Geun Choi leads RenaAi's alternative data methodology, credit and valuation models, and data supply business.

2013 – 2014
A*STAR SIMTech (Singapore Institute of Manufacturing Technology, A*STAR)
Big data researcher
Presented work on portfolio optimization, recommender systems, and VRP problems in project networks at international conferences such as IEEE Big Data and in journals. Built the foundations of his multidimensional data structure and graph-based analysis methods during this period.
Academic papers (IEEE · Operations Research)
- Multi-period portfolio optimization: Translation of autocorrelation risk to excess variance
  BG Choi, N Rujeerapaiboon, R Jiang
  Operations Research Letters 44 (6), 801–8072016Cited 10×doi:10.1016/j.orl.2016.10.006
- Profit estimation error analysis in recommender systems based on association rules
  G Ertek, X Chi, G Yee, OB Yong, BG Choi
  IEEE International Conference on Big Data (Big Data), 2138–21422015Cited 2×doi:10.1109/bigdata.2015.7363998
- Graph-based analysis of resource dependencies in project networks
  G Ertek, BG Choi, X Chi, DZ Yang, OB Yong
  IEEE International Conference on Big Data (Big Data), 2143–21492015Cited 2×doi:10.1109/bigdata.2015.7363999
2017 – 2019
NUS Risk Management Institute (RMI) (National University of Singapore)
Researcher
Researched credit risk modeling for Asian capital markets (Credit Research Initiative). Served as Product Manager for BuDA (Bottom-up Default Analysis), a stress-testing toolkit co-developed with the IMF. Applied the multidimensional data analysis skills built at A*STAR to financial ontology design. This credit research group now sits under NUS AIDF, jointly established by MAS, NRF, and NUS.
2019 – 2022
Samsung Asset Management
Global equity fund manager
Managed global equity portfolios. Applied enterprise value (EV) analysis, EBITDA modeling, and multiple-based valuation across thousands of companies.
Media appearances
- [Global Issue Check] Reading public interest in the metaverse through big data, ft. Byung-Geun Choi, Manager, Samsung Asset Management
  3PROTV2021-08-10In Korean
Press · regulatory filings
2022 – 2023
NH-Amundi Asset Management
Head of global equity team
Set team-level investment strategy. Systematized sector re-rating mechanisms and the multiple structures of AI and tech companies.
Press · regulatory filings
- NH-Amundi notice of amendments to prospectuses (including summary prospectuses) and trust agreements: change of portfolio manager (Hye-jung Park → Byung-Geun Choi)
  NH-Amundi Asset Management2022-04-29Filing
- ChatGPT, the would-be game changer: should you hold it through Korean ETFs?
  Edaily2023-02-01
2023 – 2024
Korea Investment Management
Head of product strategy
Planned AI-based new product strategy and designed EV structures for the asset manager. Quantified the potential for AI transformation of the firm's managed assets.
2024 – 2026
Liberti SG / JP
PM, unlisted equity exchange project
Pursued license applications for a Singapore RMO (Recognised Market Operator) and a Japan PTS (proprietary trading system), and planned and designed an exchange for unlisted assets. This is where he worked on how assessed enterprise value turns into trades and capital.
2026 –
RenaAi
Founder & CEO
Founded a company that builds alternative data with its own methodology and connects it to global financial markets. Also designed the AI EV partnership here, combining financial investment expertise with AI technology.

Press and filing titles are English translations of Korean originals. KRW amounts converted at ₩1,340 = US$1 (October 2026).

Head of IP · CLO

Yoo Yeon, representative attorney

From patent attorney to representative attorney: a career that links technology to rights, and rights to capital. Yoo Yeon entered Seoul National University's Department of Electrical Engineering in 2004, in the same class as the CEO.

Official website · seoyeonpapa.com

2004 – 2009
Seoul National University, Department of Electrical Engineering
Engineer (engineering student)
Entered the Department of Electrical Engineering in 2004 in the same class as CEO Byung-Geun Choi, and graduated in 2009. Built the engineering foundation to read semiconductor and electronics technology in its own terms. Twenty years later, the two engineers meet again in IP.
2010 – 2017
Shinsung Patent Law Firm
Patent attorney
Seven years of patent prosecution, registration, and trial work for semiconductor companies including SK hynix. Trained in turning technology into "rights," learning the language of technology and the language of patents at the same time.
2017 – 2020
Sungkyunkwan University School of Law
Juris Doctor · graduated first in class
From patent attorney to lawyer. Beyond "creating" rights, added the power to "enforce" them in court. Graduated first in class from law school.
2020 – 2025
Shin & Kim · Barun Law
Intellectual property lawyer
Spent most of this period at Shin & Kim and one year at Barun Law, handling IP disputes at major Korean law firms. Gained hands-on experience actually defending rights, from patent injunctions and damages to trade secrets and unfair competition.
Main dispute · advisory areas
Patent injunctions · damagesCriminal trade secret misappropriationUnfair competition disputesPreliminary injunctions on job changes · non-competesTrademark · copyright infringementFair trade advisoryInternational joint R&D advisory
2025 –
Libro Law Firm
Representative attorney
Became representative attorney in 2025. Leads corporate legal work and IP litigation, directing disputes that protect the rights of technology companies.
2026 –
RenaAi
CLO · Head of IP
Owns the rights and enforcement side of patents, building IP finance together on the principle that "finance (Byung-Geun Choi) sets the value, law (Yoo Yeon) secures the rights." Provides the legal judgment in turning dormant patents into capital.

Co-founder · COO

Michael T.

A crypto expert and former Relationship Manager at Société Générale in Hong Kong, where he covered global hedge funds and connected them to financial products. After digital asset management, investing, and APAC partnerships, he now connects the data RenaAi builds to the market.

2011 – 2012
Université Paris 1 Panthéon-Sorbonne
MSc in Banking and Finance, with honours
Completed an MSc in banking and finance with honours at Université Paris 1 Panthéon-Sorbonne. Interned at firms including HSBC (France) during his studies, and worked as an analyst at Columbia Threadneedle Investments in 2012.
2013 – 2018
Société Générale CIB Hong Kong (Global Markets)
Relationship Manager · Team lead, client acquisition desk
As a Relationship Manager in Hong Kong covering global hedge funds and institutional clients, he was responsible for revenue and retention across his client portfolio. Connected FX, rates, and structured products to hedge funds, proprietary trading firms, and asset managers, and personally ran the full process for new institutional clients, from origination through KYC and legal documentation to first trade. Promoted to team lead of the client acquisition desk, coordinating APAC coverage.
2018 – 2022
Asia Innovations Group
VP, Trading and Investment
Managed a digital asset portfolio and invested in and advised early-stage Web3 companies. Built and maintained an institutional network of market makers, custodians, exchanges, venture capital firms, and family offices.
Main areas
Digital asset managementEarly-stage investingMarket structure · token strategyInstitutional partnerships
2021
Draper University
Blockchain Pre-Acceleration Program
Completed the blockchain pre-acceleration program run jointly by Tezos Israel and Draper University (blockchain, entrepreneurship, venture capital).
2023 –
AIE Labs
Co-Founder · COO
Leads business development and strategic partnerships for a Web3 AI platform operating in APAC, building collaborations with exchanges, infrastructure providers, and AI research institutions. Since 2025 he has independently researched trading and brokerage infrastructure (API-first architecture, real-time data pipelines).
2026 –
RenaAi
Co-Founder · COO
Leads business development and operations that connect RenaAi's data to institutional clients and partners in Korea and abroad. Drawing on his experience serving institutional clients at a global investment bank, he carries the data through to where it is actually used.

Value · rights · connection

Finance sets the value, law secures the rights, and markets open the connection to global capital

Byung-Geun Choi, CEO
Builds the data and sets the value
Yoo Yeon, CLO
Protects the rights behind that value
Michael T., COO
Connects the data to institutional clients and markets

With a former fund manager as CEO, a patent attorney and lawyer as CLO, and a crypto expert and former global hedge fund RM as COO on one team, data finally becomes ‘capital’ that financial markets can use.

Q&A

Frequently asked questions

The questions we hear most about the company and its technology.

What does RenaAi do?: RenaAi (legal name: 주식회사 레나에이아이) is a B2B data company that builds alternative data with its own methodology and connects it to global financial markets. It turns source data from three domains (market areas, equities, and patents) into indicators such as probability of default, pre-disclosure change signals, and patent quality scores, and supplies them to lenders, rating agencies, and asset managers through APIs and data feeds. The company was founded in Seoul on April 21, 2026.
Are RenaAi and 레나에이아이 the same company?: Yes. The registered legal name is 주식회사 레나에이아이, and RenaAi is its English brand name. The official website is renaai.co. Several overseas projects and accounts use similar names, but they are not related to us. RenaAi does not run a cryptocurrency or trading business.
What is alternative data?: Data that sits outside financial statements and credit records. Examples include store density and sales volatility in a market area, regulatory filing and trading-flow patterns of listed companies, and the rights structure of patents. Even where the fields that conventional assessments rely on are empty, this data can provide a basis for judgment.
What does alternative credit scoring for small businesses look at?: It looks at the conditions of the market area a business operates in, not at the individual borrower. Indicators include the concentration of same-industry stores, sales volatility, and co-movement with neighboring market areas. Businesses with no credit history can be assessed with these signals. Without using any financial information, we confirmed an out-of-sample AUC of 0.83.
What is equity alternative data?: For listed companies, we align sources that differ in format and frequency, such as regulatory filings, prices, and trading flows, on a single standard and read them together. The method carries the normalization we use for market-area data over to the individual stock level, and turns changes that move before earnings are announced into growth and risk signals. This is a data and indicator supply service. It is not investment advisory or discretionary investment management, and it is not a recommendation to buy or sell any security.
What is patent intelligence?: Data that reads patents by quality, not by count. We quantify forward citations, global family, enforceability, and design-around difficulty into a patent quality score, and connect it to company assessment, investment and valuation, and IP finance such as collateral and securitization.
What does an AUC of 0.83 mean?: AUC measures how well a scoring model separates risky cases from safe ones. Pick one business that actually ran into trouble and one that did not, at random: AUC is the share of such pairs in which the model gave the troubled business the higher risk score. A value of 0.5 is a coin flip and carries no information; the closer to 1, the better the separation. In finance, a model above 0.7 is generally considered usable in practice, and above 0.8 is considered strong. Card companies' retail scoring, which uses decades of payment history, falls in the 0.70 to 0.80 range. RenaAi confirmed an out-of-sample 0.83 without using a single line of credit history.
Why does out-of-sample matter?: It means the model was scored on data from a period that was not used to build it. Scoring on the training data always looks good, so it proves nothing. We rolled the clock back to 2019, made predictions without using any later data in the score calculation, and then compared them with what actually happened. That is why we publish only out-of-sample scores.
What evidence supports the technology?: Three things. An out-of-sample AUC of 0.83 confirmed using market-area data alone, without credit history; a patent application filed with 9 claims; and academic validation. A paper has been submitted to Finance Research Letters (Elsevier, SSCI); it has not been accepted for publication. Issue No. 86 (Summer 2026) of Credit Finance, the journal of the Credit Finance Association of Korea (CREFIA), published an article by Professor Hyuntak Lee and CEO Byung-Geun Choi, "Small business credit scoring and the use of market-area information," which was distributed to member companies.
Who runs the company?: The company is led by CEO Byung-Geun Choi. He studied electrical engineering at Seoul National University, earned a master's in Management of Technology at EPFL, and completed doctoral coursework (ABD) in industrial engineering at the University of Michigan, Ann Arbor. He researched credit risk at the NUS Risk Management Institute (RMI), and has served as a global equity fund manager at Samsung Asset Management, a team head at NH-Amundi Asset Management, and head of product strategy at Korea Investment Management. At RenaAi he leads the alternative data methodology, credit and valuation models, and the data supply business. Patent rights and legal matters are handled by CLO Yoo Yeon, a patent attorney and lawyer. Business development and operations with institutional clients and partners in Korea and abroad are led by co-founder and COO Michael T. He is a former Relationship Manager at Société Générale CIB in Hong Kong, where he covered global hedge funds and connected them to financial products, and a crypto expert who managed digital assets as VP, Trading and Investment at Asia Innovations Group.
Who contacts RenaAi?: Institutions that run assessment models, such as credit bureaus, credit finance companies, and asset managers, inquire about data partnerships and supply. Technology companies and research institutions that hold patents also look for patent intelligence. Inquiries are welcome at renaai.co/en/inquiry or info@renaai.co.
Is RenaAi a credit rating agency?: No. RenaAi is not a licensed credit rating business that assigns and sells ratings or scores. It is a B2B data company that supplies source data, which financial institutions and asset managers feed into their own assessment models. Final underwriting and decisions are made by the financial institutions that use the data.
Is RenaAi an AI company or a data company?: A company that makes data. We use AI and statistical models as tools to organize scattered source data and separate out signals. What we sell is not the model but the indicators and data it produces.
Who uses each of the three data sets, and how?: Small business probability of default (PD) built from market-area data is used in underwriting by lenders such as savings banks and capital (consumer finance) companies, and by rating agencies. Pre-disclosure change signals from equity alternative data are used by asset managers and research teams for stock screening and risk monitoring. Patent quality scores are used for company assessment, investment, and IP finance.
In what form is the data delivered?: Through a REST API and data feeds. Before adoption, a PoC applies the data to your own data and models first so you can see the effect.
Can it be used alongside existing credit scoring models?: Yes. It does not replace existing models; it fills their gaps. You can combine market-area and patent signals with your portfolio and scoring models and measure the improvement directly in a PoC.
How does a PoC work?: After you contact us, we agree together on the scope for combining market-area and patent signals with your portfolio and scoring models, then test the effect, for example PD estimates for businesses with no credit history or patent quality indicators. The first validation is free and confidential, and is handled personally by our CEO, a former fund manager. We get back to you within 24 hours of your request.
How does RenaAi make money?: From B2B data supply contracts. The basic structure is usage-based API pricing plus annual data feed subscriptions.
What is probability of default (PD)?: The likelihood that a borrower will default within a given period, expressed as a probability between 0 and 1. It is the basic indicator lenders use to decide whether to lend and at what rate. RenaAi estimates this value from market-area data, including for small businesses with no credit history.
How is the data produced?: In three steps. First, normalization: data that differs in format and frequency, such as spatial coordinates, filing text, and patent claims, is aligned on a single standard. Next, signal separation: temporary noise is filtered out so that only signals tied to real risk and value remain. Finally, standardized indicators: the signals become indicators such as probability of default, a leading market-area risk index, and patent quality scores, delivered through an API.
What does RenaAi's patent protect?: A patent application has been filed with 9 claims. Its core is protecting the methodology itself for scoring businesses with thin credit files (Claim 9), not just its outputs. The application was handled by Kyung-min Woo, representative patent attorney at Meta Patent Law Office.
How do patent count and patent quality differ?: How many patents a company holds says little about its technological competitiveness. RenaAi looks at how often a patent is cited (forward citations), in how many countries it is filed (global family), how solid the rights are (enforceability), and how hard it is for competitors to work around (design-around difficulty).

Want to test signals from outside the financial statements together?

We propose a PoC that combines market-area and patent signals with your portfolio and scoring models.
A valuation check is also available, and the first validation is free.

Data partnership & supply inquiry Request a valuation check

We build alternative dataand connect it to global financial markets

Renaissance and AI

Rena · Renaissance

AI · artificial intelligence

We make the data ourselves and carry it through to execution

Where the methodology comes from

Multidimensional ontology design

Attention-based micro analysis

Investment-grade EV modeling

Connecting to private capital markets

Why this company was founded

Seoul National University, electrical engineering

A*STAR SIMTech · data research

NUS Risk Management Institute · credit risk

Global equities · quant investing

Asset management product strategy

Liberti SG / JP · exchange planning

RenaAi

Putting a value on something takes four perspectives

Byung-Geun Choi, CEO

Yoo Yeon, representative attorney

Michael T.

Frequently asked questions

Want to test signals from outside the financial statements together?

We build alternative data
and connect it to global financial markets