Accern
Financials
Estimates*
USD | 2018 | 2019 | 2020 | 2021 | 2023 |
---|---|---|---|---|---|
Revenues | 2.7m | 3.8m | 3.8m | 7.9m | 7.3m |
% growth | - | 41 % | - | 107 % | - |
Date | Investors | Amount | Round |
---|---|---|---|
- | N/A | - | |
$200k | Angel | ||
$1.3m | Seed | ||
* | $3.0m | Series A | |
N/A | Convertible | ||
$2.5m | Convertible | ||
* | $13.0m | Series A | |
N/A | $4.2m | Convertible | |
$11.0m | Convertible | ||
* | $20.0m | Series B | |
* | $20.0m | Series B | |
Total Funding | AUD116m |
Related Content
Recent News about Accern
EditAccern is a technology company that specializes in providing AI-driven Natural Language Processing (NLP) solutions to transform unstructured data into actionable insights for financial services. The company serves a diverse range of clients including banks, asset managers, insurance companies, Fortune 1000 enterprises, and startups. Operating in the financial technology market, Accern's business model revolves around offering a no-code platform and pre-built applications that enable clients to enhance their data analytics capabilities without extensive IT resources. The company generates revenue through subscription fees for its platform and applications, as well as through custom solutions tailored to specific client needs.
Accern's platform allows clients to categorize content by companies, people, locations, themes, events, and sentiments, and to extract essential information into more editable and structured data formats. This enables financial institutions to generate intelligent filters, alerts, and explanations, which can be integrated into their business intelligence dashboards. For instance, Mizuho Bank used Accern's NLP app to identify early warnings of liquidity risk, while Standard Bank leveraged the platform to gauge health scores for small businesses in South Africa.
Accern's solutions help clients save time and costs on taxonomy model building and expensive data IT resources, allowing them to focus on maximizing performance and reducing risk. The company's pre-trained models and pre-built taxonomies are specifically designed for financial services, accelerating the development of industry-specific applications.
Keywords: AI-driven, NLP solutions, unstructured data, financial services, no-code platform, data analytics, risk reduction, performance maximization, pre-built applications, financial technology.