The Finance Archetype comprises the finance and insurance industries.[1] In 2016, it represented 275,000 jobs in the GGH, and has the highest level of job growth amongst all the Archetypes - adding about 47,000 jobs between 2006 and 2016. Toronto is Canada's financial capital, ranking seventh in importance globally and second in North America, according to the Global Financial Centres Index.[2]

Table 8: Finance Archetype Employment, GGH, 2006 and 2016




% Change






Archetypes total





Total GGH core employment





Total GGH employment





The City of Toronto accounts for 62 percent of all GGH Finance Archetype jobs. Finance employment shows a highly clustered spatial pattern, with Downtown Toronto its dominant centre. Financial services account for almost 40 percent of Downtown Toronto office space, and 52.3 percent of space in the financial heart of the city.[3] Secondary clusters are found in North York City Centre and in the Airport, Markham, and Meadowvale SKIDs. This clustered pattern is what we would expect for a dynamic, knowledge-intensive high-skills industry like Finance. Virtually all of the almost 90,000 new jobs created in the broader finance industry in the GGH between 2001 and 2014 were high-skilled or skilled. About 2,000 low-skilled finance jobs disappeared during the same period.[4]

Between 2006 and 2016, we also see a concentrated pattern of job growth - again, in Downtown Toronto, North York City Centre, and the Markham, Airport, and Meadowvale SKIDs. (See Maps 5 and 6.)

The urban environment in which Finance employment is found tends to be one of two types. Downtown Toronto and North York City Centre (an example of an older planned centre) are characterized by tall, corporate office towers. There is a broad mix of land uses, including residential apartments, diverse office-based companies, major institutions including universities, and services for workers such as shops, cafes, and gyms. These very dense areas are served by higher-order transit, but are also accessible by bicycle and on foot.

The urban characteristics of the SKIDs are very different from those of Downtown Toronto. These are planned, suburban office parks. While still dominated by corporate offices, these tend to be low- to mid-rise buildings with large surface parking lots, so the areas are of only moderate density. There are no residential uses within SKIDs. They do offer a range of office-based industries, and in some cases, include higher education institutions. Amenities for workers within the districts are limited - perhaps a coffee shop on the ground floor of an office building. Despite recent investments in transit service improvements to the Markham, Waterloo and Airport SKIDs, the districts are auto-dependent. The public realm is characterized by low walkability - buildings are far apart, often there is little attention paid to the walking environment, roads are a challenge to cross, and there are few destinations within walking distance.

Financial industries have become even more globally integrated, taking advantage of deregulation and foreign markets. Finance and insurance services exports have been the fastest-growing of any Canadian industry, goods included, as Figure 4 (taken from a 2015 Conference Board of Canada report) shows.[5] Canada's five largest banks now derive 20 to 50 percent of their revenue from non-domestic sources.[6]

Figure 4: Fastest-growing exports, Canada, 2003-2013

Figure 4: Fastest-growing service exports, Canada, 2003-2013

Source: The Conference Board of Canada, Canadian Interactive Trade Forecast-2014, 2015

Technological change continues to transform the financial services industry. At first, this took the form of the automation of certain routine tasks, as ATMs replaced much of tellers' work. More recently, automation has spread to higher-skilled tasks in financial services, such as investment advice (such as "robo-advisors") and equity trading.

The use of computer and information technologies is continuing to advance, with the integration of artificial intelligence in electronic trading. For example, RBC Royal Bank is developing an AI-enhanced platform that analyses data and adapts trading responses automatically. As a result, many new workers in the finance industries have skills in data management and analysis, and software engineering.

In the finance sector, "Job openings for information systems analysts and consultants together increased by 6,794 openings from 2015 to 2017, while openings for software engineers and designers nearly doubled in 2017 over 2015: from 1,117 to 2,209."

Lamb, Munro and Vu, Better, Faster, Stronger, Brookfield Institute, 2018, p. 84.

FIRE is among the industries in which potential employment losses to automation are judged to be comparatively low - at 28.5 percent of jobs (see Table 21).[7] Routine tasks are at risk, such as payments, investment trading, advisory services, and credit lending. Tasks that can be characterized as intermediation, such as those performed by brokers, are vulnerable to "disintermediation" - the elimination of the middleman function - as new technologies allow buyers and sellers to make their own trades directly electronically.[8] Some of the types of jobs vulnerable to automation represent significant numbers of workers.

Jobs most vulnerable to automation:

  • Insurance agents and brokers (60% automatable tasks, 27,825 jobs in Ontario, 2016)
  • Insurance adjusters and claims examiners (81% automatable, 11,886 jobs in Ontario, 2016)
  • Banking, insurance and other financial clerks (81% automatable, 11,050 jobs in Ontario, 2016)

Lamb, Munro, and Vu, Better, Faster, Stronger, Brookfield Institute, 2018

Emerging technologies have prompted the creation of new financial products and processes, including the "fintech" sector.

Fintech companies include start-ups, tech companies entering the finance field, tech giants (such as Apple Pay), and traditional financial institutions creating their own fintech products. In some cases, fintech companies compete directly with traditional financial institutions, such as wealth management and payments; in other cases their services are complementary, such as data, security, and management software.[9] There were 100 known fintech firms in Canada in 2016, 60 of which are located in Toronto, clustered in and around the financial core (see Figure 5).[10]

Fintech refers to "a new category of flexible and scalable companies focused on using technology to provide financial products and services. They differ from traditional financial firms such as banks due to their primary reliance on digital technologies and software to operate."

GWL Realty Advisors and CBRE, Banking and the New Digital Era, 2016, p. 10.

New and emerging technologies offer not only the potential to disrupt existing financial services industries and replace certain types of work, but also suggest growth potential through new firms, products, processes, and markets. A significant potential disruptor is blockchain technology - a "distributed ledger" system that could remove need for traditional institutions to confirm the authenticity of transactions, and "drastically reduce the infrastructure costs for financial services firms."[11]

Figure 5: 60+ Fintech firms and their locations in Toronto

Figure 5: 60+ Fintech firms and their locations in Toronto

Source: GWL Realty Advisors and CBRE, Banking and the New Digital Era, 2016, p. 16.

The drivers described above have important implications for the nature of work, as well as for the structure of employment, firms, and the industry as a whole in the Finance Archetype. These changes in turn have implications for the geography of Finance employment and activities within the GGH.

On one hand, routine work, which is the most vulnerable to automation, has tended to locate in suburban areas. But as automation progresses into higher-skilled tasks, we could see automation affect downtown jobs as well.

On the other hand, the growth of high-skilled jobs, the increasing technological element of Finance, the emerging firms and innovation associated with fintech, office consolidations, and an increasing role for exports - all suggest further geographic concentration, particularly in and around Downtown Toronto. Further concentration, however, will occur only if Downtown continues to offer a high-quality environment with access to the region-wide talent pool, and if the financial district can absorb future growth and access by transit remains functional.

Map 5: Finance Archetype Employment, GGH, 2016
Map 5:  Finance Archetype Employment, GGH, 2016

Map 5: Finance Archetype Employment, GGH, 2016

Map 6: Finance Archetype Employment Change, GGH, 2006-2016
Map 6:  Finance Archetype Employment Change, GGH, 2006-2016

Map 6: Finance Archetype Employment Change, GGH, 2006-2016

[1] Often the broader "FIRE" category is used, that is, Finance, Insurance, and Real Estate. For our analysis, real estate is not included, as it has different dynamics and characteristics.

[2] GWL Realty Advisors and CBRE, Banking and the New Digital Era: What's Next for Financial Services in Canada? A Commercial Real Estate Perspective, 2016, p. 12.

[3] GWL Realty Advisors and CBRE, Banking and the New Digital Era, 2016, p. 13.

[4] Blais, Planning for Prosperity, 2015.

[5] Palladini, Spotlight on Services, 2015, Chart 1, p. 2. This ranking uses price deflators to adjust for inflation. Using nominal price growth rates over 2003-2013, the fastest-growing exports are (in order): metals and mineral products, agricultural products, finance and insurance services, primary metal products, energy products, management services, and computer and information services.

[6] GWL Realty Advisors and CBRE, "Banking and the New Digital Era," 2016. This revenue comes mostly through foreign affiliates, with an estimated $75 billion finance and insurance services (not including banking) sold abroad through foreign affiliates in 2012, versus $9 billion in directly exported services. See also Palladini, Spotlight on Services, 2015, p. 26.

[7] Oschinski and Wyonch, Future Shock? 2017.

[8] GWL Realty Advisors and CBRE, "Banking and the New Digital Era," 2016, p. 10.

[9] Ibid.

[10] Ibid.

[11] Lamb, Munro, and Vu, "Better, Faster, Stronger," 2018, p. 82.