We are inviting a few customers to gain early access to Weave.AI Spectrum Engage, a transformative solution that turbocharges client engagement to boost customer acquisition and retention, and grow AUMs.
Market your financial products—ETFs, mutual funds, ESG funds—via a modern information format that is snackable, digestible, engaging, and measurable.
Watch the video below to learn more and click here to sign up.
Read Less. Know More.
Turn content into insight. Insight into returns.
Weave Spectrum constantly scans the Internet for relevant reports, investor calls, videos and transcripts, company news releases, and other relevant content to remain up-to-date when analysts or investors want answers.
The Spectrum ESG Markets
ESG for Investors
- Quickly analyze and benchmark corporate disclosures.
- Gap analysis reveals which portfolio companies are excelling at ESG factors, and which need to improve.
- Track portfolio performance to improve investment decisions, drive client engagement and reduce risk.
ESG for Companies
- Refine your ESG profile to improve investor relationships.
- Leverage gap analysis to differentiate your ESG profile for competitive advantage.
- Streamline your ESG reporting for compliance and performance management.
ESG for CI
- Understand competitive positioning against peer ESG profiles.
- Gain key insights from peers by jumping to the most relevant positioning statements.
- Quickly identify market trends.
Spectrum ESG FAQs
Weave Spectrum ESG employs advanced AI to automate the intelligence, analysis, benchmarking, aWeave Spectrum ESG employs advanced AI to automate the intelligence, analysis, benchmarking, and ongoing improvement of a company’s ESG performance.
Spectrum ESG helps investors evaluate the materiality of ESG claims, improve portfolio allocation, Spectrum ESG helps investors evaluate the materiality of ESG claims, improve portfolio allocation, reduce investment risks, and better engage clients, regulators, and companies.
Spectrum ESG automates industry-wide ESG question-answering with the immense power of an intelligeSpectrum ESG automates industry-wide ESG question-answering with the immense power of an intelligent AI assistant. Gap analysis helps you identify precisely where you need to improve relative to a variety of peer groups. Peer analysis enables you to dive deep into a specific top-performing peer to determine why it has high ratings to emulate its best practices.
We cover all large and mid-cap public companies in the U.S., Europe, and Canada, as well as large-cap and most mid-cap companies in other regions around the world.
If a company isn’t already in our database, we will include it if it meets our criteria.
It takes between 24 and 48 hours to include a new company in an existing benchmark.
It takes less than an hour to create a new benchmark.
Spectrum ESG analyzes ESG reports, ESG-related documents (such as diversity reports, climate impact reports, etc.), webcast transcripts, earnings call transcripts, annual reports, press releases, regulatory filings (such as 10Qs), and other reports. Spectrum ESG also analyzes news articles from authoritative sources to detect ESG-related risks, controversies, and positive developments.
Our ESG data and benchmarks are updated 24/7.
For most companies, ESG data goes back about a decade.
Yes. You can an unlimited number of PDFs to analyze in a specific benchmark.
Only you will have access to your data. Your reports will be encrypted and secured in a private repository on Amazon Web Services (AWS) S3.
Weave.AI includes sophisticated debiasing algorithms to ensure that larger companies do not end up with inflated gap analysis scores merely because they have more disclosure volumes or dramatically more news coverage. Our AI also considers the size of the company while determining how material a particular investment is.
We determine a company’s peer group using the Global Industry Classification Standard (GICS), a popular industry taxonomy developed by MSCI and Standard and Poor’s (S&P).
Yes. Customers can create custom benchmarks with a specific set of companies they wish to compare themselves against. For instance, some big-cap customers might want to compare the only against their peers but against other big-caps in their region (e.g., the EU). Asset managers Yes. Customers can create custom benchmarks with a specific set of companies they wish to compare themselves against. For instance, some big-cap customers might want to compare themselves not only against their peers but against other big-caps in their region (e.g., the EU). Asset managers might also want to create custom benchmarks for specific companies that straddle multiple industries (e.g., benchmarking Tesla against either automotive peers, solar peers, or Amazon against either technology peers or retail peers).
Weave ESG Knowledge Graph is a comprehensive database of ESG-related topics, issues, technologies, organizations, and relationships. It provides the intelligent discovery of ESG insights out of mountains of reports and facilitates intelligent ESG benchmarking, question-answering, and gap analysis.
Our AI leverages the Weave ESG Knowledge Graph within a specific peer group benchmark and Our AI leverages the Weave ESG Knowledge Graph within a specific peer group benchmark and automatically unearths which ESG issues are most material in that peer group. This helps customers solve the “I don’t know what I don’t know” problem wherein they aren’t even aware of what ESG issues matter most in their industry or peer group.
The ESG Knowledge Graph is automatically built using natural-language-processing – by analyzing millions of ESG data points daily. The graph is updated 24/7.
Yes, benchmarks can be created to only evaluate companies’ performance within a specific time period.
Traditional keyword-based relevance algorithms are very susceptible to greenwashing because they can be fooled by companies that merely pay lip service to a particular ESG issue without doing anything meaningful. Built by the team that created the core conversational AI algorithms behind Amazon Alexa, Weave.AI uses proprietary summarization algorithms to detect critical takeaways (or smart-talking points) and then employs deep learning to rank said key takeaways by materiality. To do this, it uses proprietary language models that know the difference between intent and an accomplishment and how material a particular accomplishment is, and it does all this in the context of the industry in question.
Furthermore, smart talking points are completely transparent – clicking on a smart talking point furthermore, smart-talking points are entirely transparent – clicking on a smart-talking point takes the user to the specific document and page where said company made that disclosure. This enables the user to learn more about the particular issue –right from the source.
Weave.AI performs semantic harmonization for use in analytics (gap analysis) and benchmarking. Without harmonizing, semantics and context benchmarks can often be wrong. To take an example, companies can talk about ‘diversity in a myriad of different ways, and without semantic harmonization, benchmarks and downstream analytics will likely mislead. Using proprietary AI language models and deep learning Weave.AI also understands context—and knows the difference between words like ‘waste,’ ‘fine,’ and ‘strike’ in an ESG context and said words in a generic context.
Report cards are infographics that summarize a company’s ESG performance relative to its peer group. Report cards are deeply integrated with the Weave.AI ESG Knowledge Graph and indicate precisely where a company is underperforming or over-performing relative to its peers. These topics, called themes, are generated by the knowledge graph. Report cards are also fully interactive – the user can click on a particular peer to pivot from peer to peer, find out areas of underperformance or overperformance, then click on those areas to determine the smart-talking points corresponding to said areas. The smart-talking points can then be clicked to navigate the user to the specific document where the company made said disclosure and the particular page therein. This provides an end-to-end and fully transparent experience of ESG benchmarking and analytics – instead of opaque black boxes that don’t give access to the underlying data.
Yes. You can create benchmarks based on custom themes—such as Renewable Energy or a subset of ESG (e.g., the ‘E’, the ‘S’, or the ‘G’).
Smart talking points are ranked based on materiality and distinguish empty rhetoric from material accomplishments. In addition to analyzing corporate disclosures, Weave.AI includes ESG webcast transcripts based on ESG-specific calls with Wall Street analysts. The themes are ranked by what the companies disclose and the questions ESG analysts pose to the companies. Indeed, these analyst-provided insights are categorized as being more authoritative by Weave.AI’s materiality algorithms. Weave.AI also analyzes news and videos (updated in real-time) from the world’s top sources, and these—weighted by the authoritativeness of the source—are also factored into a company’s performance rating. Weave.AI also uses these news articles and videos as inputs into its ESG Knowledge Graph. If the algorithm notices a significant issue in the news over time, it automatically adds that issue to the knowledge graph and updates the scores of the affected companies. Lastly, if our AI detects an ongoing discrepancy between a company’s public disclosures and a pattern of controversies reported in authoritative news sources, it will negatively impact its score.
Even if the entire industry is greenwashing, Weave.AI can be used to ‘raise the bar’ by benchmarking the entire parent industry group or the sector, based on the GICS taxonomy. This will illuminate companies that are under-performing and greenwashing relative to a higher-performing peer group.
We complement existing datasets and tools. We do not aim to replace your existing approaches. We complement existing datasets and tools. Most customers employ many tools and datasets to provide an overarching view of a company’s ESG performance. Asset managers also create propriety models using a variety of input datasets, including but not limited to Spectrum ESG.