Alternative data has exploded onto the scene and completely transformed the financial sector over the past few years alone. In my 10+ years working in web data extraction, I‘ve witnessed firsthand how alternative data went from a niche concept used by a handful of hedge funds to now becoming a must-have for any serious asset manager.
Our free white paper dives deep into all things alternative data – from what it is, who‘s using it, why it matters, and what the future looks like. This guide is meant for anyone looking to understand alternative data and how it can be applied in finance.
What Exactly is Alternative Data?
Alternative data refers to data gleaned from non-traditional sources outside of conventional financial statements, earnings calls, and government filings. This includes:
- Web scraped data on pricing, product reviews, jobs data, foot traffic
- Satellite and geolocation data tracking physical world activity
- Credit card transactions showing consumer spending
- Data from sensors, smartphones, and other connected devices
The key is that alternative data reveals predictive signals about a company or industry not found in traditional structured data sources.
Take web scrapings of Amazon customer reviews as an example. Analyzing review volumes, ratings, and sentiment for products can signal rising or falling demand well before it shows up on financial reports.
Adoption of Alternative Data is Surging
Alternative data has moved into the mainstream in a big way. According to a Preqin survey, 17% of hedge funds were using alternative data back in 2017. Fast forward to 2020, and that number quintupled to 55% of funds!
And it‘s no longer just quantitative hedge funds leading the way. Adoption is now growing quickest among traditional long-only managers, private equity firms, and even banks getting into alternative data.
Total spending has ballooned from an estimated $200 million in 2017 to over $1 billion in 2020. Projections have the alt data market reaching $7 billion by 2022.
The Myriad Benefits of Alternative Data
So what‘s driving this surge in alternative data? The top benefits reported by financial firms include:
- Unique insights – Alternative data reveals trends not captured in traditional data, providing an informational edge. For example, geolocation data from smartphones can show retail traffic patterns.
- Enhances investment decisions – Granular data adds new signals that improve predictive accuracy of investment models. Analysts also gain more comprehensive visibility into company fundamentals.
- Competitive advantage – Alternative data is increasingly becoming table stakes for fund managers to generate alpha and beat benchmarks.
- Risk management – More breadth of data also allows investors to better monitor risk exposure and events that traditional indicators often miss.
Real World Success Stories
The most sophisticated quantitative funds and data-driven managers have been at the forefront of adopting alternative data:
- Two Sigma – The quantitative hedge fund pioneered using satellite imagery data to predict economic activity.
- Man Group – The world‘s largest publicly traded hedge fund firm set up a dedicated alternative data science lab.
- Point72 – Steve Cohen‘s family office is aggregating 100+ alternative data sets into AI-driven models.
Even traditional firms like Blackrock, Goldman Sachs, and JP Morgan have been making large investments into alternative data capabilities.
Challenges and Limitations Persist
While adoption has grown exponentially, effectively capitalizing on alternative data still poses challenges:
- Data quality – Validating new data sources is crucial to avoid false signals or biased data. Out of 252 firms surveyed, 61% cited this as their top challenge.
- Talent scarcity – Advanced analytics skills like NLP and computer vision are required to process unstructured alt data. 46% reported this as an obstacle.
- Regulatory risks – Governance and compliance procedures need to be robust to navigate legal gray areas around web scraping and data collection.
As alternative data spreads into new domains like manufacturing, CPG, and healthcare, addressing these limitations will determine which firms extract real value.
The Outlook for Alternative Data Remains Bright
Based on current trajectories, utilization of alternative data in finance will only continue growing:
- More data sources – We‘re seeing an explosion of alternative data providers and new innovative data types.
- Improved analytics – Advances in big data engineering and AI are making it easier to process alt data.
- Growing applications – Alternative data is moving beyond just investment management into areas like credit underwriting, fraud detection and supply chain optimization.
The future opportunities lie in combining disparate alternative data signals into unified models and platforms. As data collection and processing becomes more automated, the marginal costs of expanding alternative data usage will fall dramatically.
Best Practices for Implementation
For firms looking to explore alternative data, here are some tips to drive success:
- Start with targeted hypothesis-driven pilots instead of jumping into large-scale data purchases. Quickly test potential value.
- Partner closely with data scientists and technology teams throughout the process.
- Combine alternative data with traditional data sources to supplement your existing processes.
- Ensure proper data governance, compliance and auditing procedures are in place.
- Be flexible and keep an open mindset when evaluating new data sources – move quickly and iterate.
The possibilities with alternative data are vast. As both data availability and analytical capabilities grow, those who can harness alternative signals will have a distinct competitive edge within financial services and beyond.
I hope you find our free white paper a helpful guide as you consider an alternative data strategy! Please don‘t hesitate to reach out if you have any other questions.