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Intangible Assets | 12 Months Ended
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Dec. 31, 2018
Intangible Assets |
Intangible Assets | 15. Intangible Assets: (a) Changes in intangible assets during the 2016, 2017 and 2018 periods are as follows:
|  |  |  | Intangible assets arising |  | Software or |  |
|  |  |  | from business |  | computer |  |
|  | Goodwill (1) |  | combinations (2) |  | programs |  | Total
|  | MCh$ |  | MCh$ |  | MCh$ |  | MCh$
Gross Balance |  |  |  |  |  |  |  |
Balance as of January 1, 2016 |  | 16,714 |  | 56,249 |  | 100,000 |  | 172,963
Acquisitions |  | — |  | — |  | 11,248 |  | 11,248
Disposals |  | — |  | — |  | (1,757) |  | (1,757)
Balance as of December 31, 2016 |  | 16,714 |  | 56,249 |  | 109,491 |  | 182,454
Acquisitions |  | — |  | — |  | 18,779 |  | 18,779
Disposals |  | — |  | — |  | (5,790) |  | (5,790)
Balance as of December 31, 2017 |  | 16,714 |  | 56,249 |  | 122,480 |  | 195,443
Acquisitions |  | — |  | — |  | 23,512 |  | 23,512
Disposals |  | — |  | — |  | (1,024) |  | (1,024)
Balance as of December 31, 2018 |  | 16,714 |  | 56,249 |  | 144,968 |  | 217,931
Accumulated Amortization |  |  |  |  |  |  |  |
Balance as of January 1, 2016 |  | — |  | (34,982) |  | (73,281) |  | (108,263)
Amortization for the year |  | — |  | (2,286) |  | (8,595) |  | (10,881)
Disposals |  | — |  | ― |  | 1,726 |  | 1,726
Balance as of December 31, 2016 |  | — |  | (37,268) |  | (80,150) |  | (117,418)
Amortization for the year |  | — |  | (2,285) |  | (9,075) |  | (11,360)
Disposals |  | — |  | ― |  | 5,790 |  | 5,790
Balance as of December 31, 2017 |  | — |  | (39,553) |  | (83,435) |  | (122,988)
Amortization for the year |  | — |  | — |  | (10,496) |  | (10,496)
Disposals |  | — |  | — |  | 1,024 |  | 1,024
Balance as of December 31, 2018 |  | — |  | (39,553) |  | (92,907) |  | (132,460)
Net balance as of December 31, 2016 |  | 16,714 |  | 18,981 |  | 29,341 |  | 65,036
Net balance as of December 31, 2017 |  | 16,714 |  | 16,696 |  | 39,045 |  | 72,455
Net balance as of December 31, 2018 |  | 16,714 |  | 16,696 |  | 52,061 |  | 85,471
| (1) |  | Goodwill corresponds mainly to business combination with Citibank Chile whose amount is of MCh$12,576 that represents the value of synergies to be generated in the combination process and the acquisition of know-how.
| (2) |  | Intangible assets arising from business combinations include assets with indefinite useful lives acquired in the business combination with Citibank Chile.
As of December 31, 2017 and 2018, the Bank had made the following commitments for technological developments:
|  | Amount of Commitment
|  | 2017 |  | 2018
|  | MCh$ |  | MCh$
Software and licenses |  | 5,129 |  | 11,806
(b) Impairment testing of Goodwill For goodwill impairment purposes, testing is carried out at the level of business segments described above and in Note No. 6 to the financial statements. This methodology is in line with IAS 36, where business segments represent the lowest level within the entity at which the goodwill is monitored for internal management purposes. Accordingly, for impairment testing purposes, goodwill acquired through business combinations has been allocated to four individual business segments, as follows:
|  | 2017 |  | 2018
Business Segments |  | MCh$ |  | MCh$
Retail |  | 5,928 |  | 5,928
Wholesale |  | 2,135 |  | 2,135
Treasury and money market operations |  | 4,513 |  | 4,513
Subsidiaries |  | 4,138 |  | 4,138
Total |  | 16,714 |  | 16,714
Below are the key assumptions used for determining the value in use for impairment testing purposes:
| · |  | The Bank determines the recoverable amount of its business segments on the basis of value in use and employs a discounted cash flows (“DCF”) valuation model. The DCF model reflects the characteristics of the banking business for every segment, the country’s expected macroeconomic performance, the bank’s market position and risk appetite while considering both the business and regulatory environment. Based on this backdrop, the model determines the present value of the estimated future earnings that would be distributed to shareholders, once the respective regulatory capital requirements are satisfied.
| · |  | For purposes of the goodwill impairment testing, the DCF model uses earnings projections for a ten-year period. Estimating future earnings requires judgment based on the bank’s past and current performance as well as expected developments in the industry, related markets and main macroeconomic variables such as GDP growth, nominal interest rates and inflation, lending spreads and expected credit losses.
| · |  | A ten-year period is deemed as the Bank assumes that over that period it is possible to achieve the goals set in the long-term business strategy.
| · |  | Earnings projections result from business growth, particularly associated with projected expansion rates for the local economy, the industry’s loan book and the Bank’s strategic goals. Then, based on historical data and a linear regression analysis, the Bank determines a multiplier of loan expansion (real terms) over GDP growth for the local economy. Currently, this multiplier is approximately 1.9 times and is expected to decrease overtime as long as banking penetration increases across the diverse business segments. For GDP growth forecasting, the Bank applies judgment based on publicly available information, such as Central Bank’ estimates and market analysts’ projections.
| · |  | Following the estimation of growth rates for the economy and the banking industry, expansion rates of the Bank’s loan book are determined by considering the achievement of the Bank’s long-term strategic goals. Therefore, real growth rates are considered to be slightly higher than the industry rates within the ten-year period, assuming that a market share of 17.8% is achieved at year three and remains constant onwards. According to the Bank’s assessment this market share should permit it to obtain economies of scale while ensuring profitable growth by preserving the Bank’s balance between risk and return.
| · |  | Earnings projections beyond the ten-year period are involved in the terminal value, which considers a perpetual cash flows growth rate within the long-run set at 4.5% in the baseline scenario. This is in line with the compounded average growth rate of cash flows over the ten-year period deemed for evaluation.
| · |  | For purposes of business segments valuation, the DCF model considers discount rates that are determined by carrying out a linear regression analysis based on historical data of monthly stock returns for the Bank and the market portfolio or overall stock index (IGPA index in Chile). In order to do this, an index linear model is applied, which is widely used in finance for these purposes. After estimating the model parameters (alpha and beta), the Capital Asset Pricing Model (“CAPM”) is utilized in order to determine the cost of equity or discount rate for shareholders’ cash flows. When using CAPM, equilibrium scenarios are also assumed for risk-free rates and inflation. Based on this analysis, an 8.4% discount rate was computed by using CAPM and, therefore the Bank determined a cost of equity of 9.0% as a baseline scenario for discount rates used for valuation purposes. The Bank also carries out a sensitivity analysis by setting discounts rates of 8.0% and 10.0%.
| · |  | The value in use of every business segment is sensitive to earnings projections, discount rates and, to a much lesser extent, long-term growth rates. Changes in market factors may affect the calculation of discount rates.
(c) The annual goodwill impairment tests for the years ended December 31, 2017 and 2018 did not result in an impairment loss on the goodwill of the Bank’s business segments as their economic values were higher than their carrying amounts.

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